As Australia continues to be affected by inflationary pressures and global headwinds, Dr John Hawkins has emerged as a prominent voice offering insight into the nation’s outlook.

Dr John Hawkins is the head of the Canberra School of Government at the University of Canberra. He was formerly a senior economist at the Reserve Bank of Australia, the Australian Treasury, and the Bank for International Settlements, and he also served as secretary to the Senate Economics Committee.

In an exclusive interview with International Finance, Dr John Hawkins discusses the economic outlook for Australia, cost-of-living crisis affecting the country, and the Reserve Bank of Australia’s rate hikes. Additionally, he shares his views on economic resilience, the stability of small and medium enterprises, and the debt burden on Australian households.

International Finance: What trends are currently shaping consumer confidence in Australia, and how might they influence spending patterns?

Dr John Hawkins: Consumer confidence is well below its long-term average. The main cause is ‘cost of living’ pressures. The Reserve Bank of Australia’s decision to increase interest rates again at its March meeting, and conjecture that it is likely to move again, could well see consumer confidence slump further.

How is Australia balancing economic growth with sustainability and climate-related challenges?

Australia had introduced an emissions trading scheme, which operated from 2012 to 2014 with a temporary fixed price. It would have allowed greenhouse gas emissions to be reduced in the most efficient manner, but was scrapped following a change of government at the 2013 election. Australia now has a target of reducing emissions by 43% from 2005 levels by 2030 and achieving net zero by 2050. It is being implemented by a range of sectoral plans. Treasury modelling in 2025 concluded the transition is consistent with the Australian economy growing by around 80% from 2025 to 2050.

What impact are recent trade developments having on Australian exporters and importers?

The United States takes less than a tenth of Australian exports, so the direct impact of higher US tariffs is modest. More important will be the impact of US tariffs on China and our other major trading partners.

How resilient is the Australian economy to fluctuations in global commodity prices?

Iron ore, coal and gold are significant sources of export revenue, so commodity price movements are important. But the floating exchange rate serves as a buffer as the Australian dollar tends to depreciate when commodity prices fall.

In what ways are small and medium-sized businesses faring in the current economic climate?

Liaison by the Reserve Bank in 2025 found that, while improving, business conditions for small businesses are weaker than for large businesses. Most small businesses, however, remain profitable and can readily access credit.

How is household debt affecting economic stability and purchasing power in Australia?

Household debt remains high by historical standards. But the debt is concentrated on households that can manage it. Less than 1% of households with home mortgage loans are significantly in arrears.

Are there sectors in Australia that are positioned for growth despite broader economic uncertainty?

Most areas of the economy are likely to keep growing as, unlike some OECD countries, the Australian population is still expanding.

How are wage growth and cost-of-living pressures shaping the everyday experience of Australians?

As evidenced by its being the dominant concern in opinion polls, cost-of-living pressures are weighing heavily on many Australian households. With consumer prices currently growing by 3.8% while wage growth is 3.4%, many Australian households are finding it harder to afford everyday purchases.

What role is technological innovation playing in transforming traditional industries in Australia?

Business investment and firms’ investment intentions have picked up recently. The renewable energy transition and construction of data centres are examples of technological innovations driving this investment.

Looking ahead, what are the most significant challenges and opportunities for Australia’s economic future?

Geopolitical uncertainty is a major challenge. Domestically, Australian productivity growth has been weak in recent years. But the recent re-election of the government with a comfortable majority increases the opportunity for productivity-enhancing economic reforms.

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“Japanese Minister of Finance Satsuki Katayama and South Korean Minister of Economy and Finance Koo Yun-cheol expressed serious concern over the sharp depreciation of the Korean won and the Japanese yen. Furthermore, they reaffirmed that they will closely monitor foreign exchange markets and continue to take appropriate actions against excessive volatility and disorderly movements in exchange rates,” said a media note after the officials met in Tokyo.

The yen touched its lowest in 20 months on 13th March, nearing the line of 160.00 to the dollar that the market analysts think might prompt Tokyo to intervene to support the currency. ‌The ⁠won, on the other hand, breached a psychological barrier of 1,500 per dollar this month for the first time since March 2009.

The Iran war has also driven ⁠the dollar higher on safe-haven demand, apart from battering the currencies of countries heavily reliant on imported oil.

The currency is also gaining as traders reduce expectations for how much the US Federal Reserve might cut borrowing costs in 2026, as worries over rising inflation have reduced the likelihood of interest rate cuts from two before the war to none now.

Tokyo and Seoul shared the view that significant volatility had emerged in financial markets, including foreign exchange, Satsuki Katayama told a press conference after the meeting.

“The Japanese government ⁠is fully prepared to respond at any time, bearing in mind the impact that currency moves may have on people’s livelihoods amid surging oil prices, and I believe both ⁠sides share that understanding,” she added.

Yen, due to its huge trade surplus and enormous net international investment positions, was once used to enjoy unconditional safe-haven status.

However, that position is under threat now, as Joey Chew, head of Asia FX research at HSBC, told Reuters, “The yen can be vulnerable to potential oil supply shocks – it also weakened last year in mid-June amid Israel-Iran tensions.”

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Across global banking systems, artificial intelligence is moving from back-office optimisation to the heart of credit decision-making. The shift is subtle. There are no public announcements declaring that machines now approve mortgages. Yet increasingly, algorithms analyze income, spending patterns, behavioural signals, and even alternative data before a human ever sees an application.

So, the question is unavoidable: Are machines deciding who gets loans? And if so, what happens to human judgement?

The Quiet Expansion Of AI In Lending

Artificial intelligence is already deeply embedded in financial services.

“AI is transforming banking quite significantly, and the pace of adoption is fast,” Wahyu Jatmiko, Assistant Professor in Banking and Finance at the University of Southampton Business School, told International Finance.

He points to data from the Bank of England and Financial Conduct Authority showing that around 75% of UK financial institutions were using AI by 2024, up from 58% just two years earlier.

However, he explains, the heavy use remains concentrated in internal optimisation, cybersecurity and fraud detection. In underwriting specifically, adoption is more measured.

“Roughly around 15% of firms use AI directly in credit underwriting,” he estimates.

That figure may sound modest. But the deeper shift is structural.

“Even where it is not fully taking over, AI is increasingly embedded in the process,” Jatmiko says.

Instead of relying entirely on traditional credit bureau scores, systems now analyse real-time transaction data, behavioural patterns, and alternative datasets.

The result is not necessarily that machines approve all loans. Underwriting is becoming faster, more data-driven, and far more granular.

James Ekpa, an AI researcher at the Blockchain Technology Association for Black & Minority Ethnic Engineers (AFBE-UK), did not mince words.

“Yes, machines are increasingly deciding who gets loans today,” he told International Finance.

He sees a transformation from slow, manual processes to rapid, automated systems powered by machine learning algorithms.

Speed, consistency and scalability are among AI’s biggest advantages. Decisions can be made quickly. Models apply the given criteria uniformly. And, algorithms can analyse thousands of variables at a scale humans simply cannot match.

Efficiency, in other words, is no longer the differentiator. It is the baseline expectation.

Enhancement Or Replacement?

But, does faster mean better? And more importantly, does faster mean human judgement is fading?

“At the moment, I clearly see AI as enhancing human judgement rather than replacing it,” Jatmiko says.

He cites UK data suggesting that while about 55% of AI applications involve some automated decision-making, only around 2% are fully autonomous.

Creditworthiness, he argues, is not merely about predicting default probabilities. It involves context, borrower circumstances, regulatory constraints, and sometimes ethical considerations.

AI excels at analysing large datasets, document reading, income verification, and affordability calculations. In that sense, Jatmiko says, it acts like a powerful analyst. But final approvals, particularly for complex or high-value loans, still rest with humans.

Ekpa agrees that the human role is evolving rather than disappearing. Loan officers today increasingly review edge cases and borderline applications. They handle complex deals. They explain decisions to customers. They monitor model outputs and escalate anomalies.

The job is changing. It is becoming supervisory. That may be the real transformation.

When Context Meets Code

The limits of automation become clearer when qualitative factors enter the picture.

Jatmiko describes a hypothetical but realistic scenario: a small business reporting temporary losses due to a supply chain shock while holding strong long-term contracts. A human underwriter may interpret the broader narrative and take a forward-looking view. An algorithm trained primarily on historical default data might simply detect recent losses and flag high risk.

“There is research showing a mismatch between what AI models consider important and what human loan officers see as meaningful indicators of creditworthiness,” he explains.

Humans can contextualise. They can sometimes account for structural disadvantages when justified by circumstances. AI, by design, optimises patterns found in historical data. That difference is subtle. But in lending, subtle differences affect livelihoods.

The Question Of Bias

Advocates of AI argue that machines eliminate prejudice. Algorithms do not discriminate intentionally. They do not favour friends. They apply rules consistently. And that consistency is powerful.

But, consistency applied to flawed historical data can create new problems.

“AI can reduce certain types of human bias, but it can also embed and even amplify systemic bias,” Jatmiko explains.

If past lending patterns reflected unequal treatment of certain demographic groups, models trained on that data may internalise those patterns as objective signals of risk.

Ekpa echoes this concern. One of the primary risks, he notes, is bias amplification. If historical data contains discrimination, models may encode and intensify it.

Transparency is another issue. Complex models can be difficult to explain. Borrowers denied credit may receive little more than a generic explanation.

“Opacity raises regulatory and consumer trust concerns,” Ekpa warns.

Then there is model drift, when changing economic conditions gradually degrade model performance. Without continuous monitoring, systems may misprice risk during volatile periods.

In short, bias does not disappear. It changes form.

Accountability In An Algorithmic Age

If an AI-driven system denies a borrower unfairly, who is responsible? The answer is not always clear. Multiple actors are involved – AI manufacturers, developers, third-party providers, and lenders themselves.

However, both experts converge on one principle: accountability ultimately rests with the financial institution.

Ekpa says AI is a tool, not a legal entity. Financial institutions remain responsible for the models they deploy, the data they use, and the governance frameworks they maintain.

Jatmiko does not overcomplicate it. If a loan decision turns out to be unfair, the algorithm cannot be the one blamed. The bank chose to use it, so the bank carries the responsibility. That means senior leaders cannot hide behind technical language. They have to stand behind the outcomes.

He stresses that human oversight is not optional, especially for complicated or sensitive cases. Models need regular checks. They need to be tested for bias. They need proper audit trails. Otherwise, problems build quietly.

He also worries about something bigger. If many banks start depending on the same AI providers, risk can pile up across the system. One flaw could affect more than just one institution. Efficiency is important. But, it cannot come before accountability.

The Islamic Finance Lens

From an Islamic finance point of view, this is not just a technical debate. It goes deeper than that. Islamic banking is guided by Maqasid al-Shariah, ideas around justice, fairness, and social welfare. Lending is not only about numbers on a balance sheet. It carries a social responsibility.

Yes, AI can make processes smoother. Faster approvals. Cleaner risk models. That part is clear. But Jatmiko flags something more subtle. If the data used to train these systems reflects a past where small businesses were routinely sidelined, the algorithm may quietly repeat that history.

And if that happens, the technology could end up working against the very goals Islamic finance is supposed to protect. Not intentionally, but just by following patterns.

Aligning AI with ethical principles requires intentional intervention in model design and governance. It may require bringing social scientists into AI development processes. It may demand stronger oversight, particularly when tools are sourced from third-party providers.

Technology alone does not guarantee fairness. Design choices matter.

Possibility Of A Hybrid Future

So, where is banking headed? Fully automated lending systems may emerge in low-risk, low-value segments. Routine cases can be processed at speed and scale. But both experts see the broader future as hybrid.

Ekpa believes competitive advantage will come from institutions that combine AI’s analytical power with human judgement, rather than eliminating one in favour of the other.

Jatmiko similarly expects automation to expand, but insists that human supervision will remain essential, especially for complex or high-impact decisions.

Human-in-the-loop processes are already becoming common. Algorithms analyse. Humans validate. Decisions are checked before final approval. Perhaps, the future banker will not be replaced, but repositioned.

The Big Question

For borrowers, the shift may be invisible. Applications are approved faster. Rejections arrive more quickly, too. What changes quietly, beneath the surface, is how those decisions are made.

Is human judgement fading? Or simply moving further upstream, designing and supervising the systems that now perform the analysis?

The rise of the AI loan officer is not dramatic. No headlines are announcing the end of human bankers. Instead, there is gradual integration, more data, faster models, and shorter decision times.

Machines are increasingly involved. That much is clear. But whether they ultimately decide, or merely assist, depends less on technological capability and more on governance choices.

Banks can treat AI as an efficiency engine. Or, they can treat it as a tool that augments, rather than overrides, human responsibility. The distinction may determine not only how loans are approved, but how trust in the financial system evolves in the years ahead. And trust, unlike data, cannot be automated.

The post Are humans making way for AI loan officers? appeared first on International Finance.

In 2026, the real question is not whether the dollar dominates; it obviously does. The real question is whether governments are preparing for a future where they rely on it, just a bit less. A shift, yes. A revolution? Not really.

According to Bidisha Bhattacharya, economist and columnist at ThePrint, what we are seeing is not some financial revolution. It is much slower than that. Almost cautious.

“De-dollarisation is real, but it is evolutionary rather than revolutionary. The US dollar continues to account for roughly 60% of global foreign exchange reserves, down from over 70% in the early 2000s. That decline reflects diversification at the margins, not displacement at the core,” Bhattacharya told International Finance.

The fundamentals still favour the dollar – deep financial markets, extremely liquid US Treasury bonds, strong institutional trust, and powerful network effects. The more people use the dollar, the harder it becomes to replace.

“Currency hierarchies do not flip suddenly. They evolve, slowly,” she said.

The world is not abandoning the dollar; it is just becoming less dependent on it.

The gold rush — again

If there is one clear signal of this caution, it is gold. Central banks have been buying massive amounts of gold, levels not seen in decades. Annual purchases have exceeded 1,000 tonnes in recent years. This is not about returning to the gold standard or romanticising the past. It is about protection.

“Gold accumulation has become strategically significant. This is less about replacing the dollar, and more about hedging geopolitical and sanctions risk. Gold carries no counterparty risk and functions as a balance-sheet stabiliser in a fragmented global order,” Bhattacharya said.

However, markets play a role too. Mike McGlone of Bloomberg Intelligence argues that central bank demand has been pushing prices higher.

“Central banks purchased about 1,000 tonnes annually in 2022, 2023 and 2024, roughly double the previous decade’s average,” McGlone told International Finance, pointing to geopolitical tensions, including Russia’s invasion of Ukraine, as a key driver.

Yet, McGlone suggests, markets may be overheating. Gold could approach major peaks around 2026, similar to historic highs seen in 1980 and 2011. Some reserve diversification, he says, may reflect in rising gold prices rather than a fundamental move away from the dollar.

He added that most of the statistics on gold outpacing dollar reserves are due to the rapid rise in gold prices.

“Demand is notably driven by geopolitics rather than inflation concerns,” he said, suggesting easing global tensions could weaken momentum. So yes, gold is rising. But it is not replacing the dollar.

Sanctions, control, and financial vulnerability

Politics also plays a big role. Maybe more than markets.

Elnara Omarova, who works on BRICS-related policy issues, says many governments are mainly concerned about control, or the lack of it.

“The key issue is access. When central bank reserves can be frozen, or access to dollar clearing becomes politically contingent, governments start reassessing how much exposure they are comfortable carrying. Diversification then becomes less about ideology and more about insurance,” Omarova told International Finance.

This has taken several forms: larger gold reserves, more holdings in non-dollar currencies, and bilateral trade settled in local currencies. And, it has been especially seen in energy markets. But these changes remain limited. The dollar still wins on liquidity, convertibility, and market depth.

“Diversification is happening, but it is incremental,” Omarova said, describing it as risk management in a more fragmented geopolitical environment rather than an abrupt shift away from the dollar. Omarova calls it a recalibration, not a rupture.

The BRICS Debate: More noise than disruption

Much of the public discussion focuses on BRICS, and whether the group could reshape global finance. Analysts urge caution.

The influence of BRICS comes mostly from coordination, encouraging trade in national currencies, experimenting with alternative financing mechanisms, and building regional frameworks. It signals exploration, not replacement.

Lawrence Ngorand of Busara Advisors sees BRICS as pushing the world toward a more multi-polar financial system.

“The BRICS play a catalytic role, accelerating the transition toward a more multi-polar financial architecture,” Ngorand told International Finance.

Their role lies in building alternative infrastructure and gradually shifting expectations. But structural problems remain. There is no widely trusted BRICS reserve currency. Institutional cohesion varies. Therefore, the shift is evolutionary. It is slow, uneven, and incomplete.

Global trade moves beyond the dollar

This may be the toughest question. Commodity markets still revolve around dollar pricing, largely because the liquidity, benchmarks, and risk-management systems behind them are already deeply built around it.

Omarova suggests bilateral trade settlement could diversify, especially among politically aligned countries. But changing global pricing norms would require deep financial markets, credible alternatives, and global participation. That is a very high barrier.

Ngorand agrees that the dollar’s dominance is not just about politics; it is structural power: capital markets, institutional trust, and global network effects.

Regional diversification is happening, particularly in energy trade and infrastructure financing. But full displacement? Unlikely.

“The most likely outcome is not the replacement of the dollar, but the emergence of a more fragmented system where multiple currencies co-exist,” Ngorand said.

When gold stops being a safe haven

Yet the gold story is also becoming more complicated. For years, gold has been treated almost instinctively as the ultimate reserve hedge. No counterparty risk, no dependence on another country’s financial system, and no sanctions exposure. In a fragmented geopolitical world, that logic sounds almost irresistible. But, not everyone is convinced the current gold surge reflects long-term stability.

According to Mike McGlone, gold’s behaviour in markets has started looking less like a traditional store of value and more like a volatile financial asset.

“Gold has shifted toward a speculative asset from a store of value,” McGlone told International Finance, noting that its 180-day volatility has surged to about 2.4 times that of the S&P 500, the highest relative level in two decades. That is not what investors typically expect from a stability anchor.

In fact, McGlone suggests that in many financial stress scenarios, gold might not behave the way policymakers hope. Instead of rising as a stabiliser, it could actually fall when measured in dollar terms.

“In most scenarios, gold declines in USD terms,” he said.

That observation complicates the narrative that central banks are simply replacing dollar reserves with bullion. In reality, gold still trades in a dollar-dominated financial ecosystem. Its pricing, liquidity, and global trading infrastructure remain deeply tied to the very system some countries are trying to hedge against.

So, the question becomes less about whether gold can hedge geopolitical risk and more about whether it can truly function as a substitute for dollar liquidity during a crisis. So far, the answer remains uncertain.

The signalling game of ‘central bank gold’

There is another dimension to the gold story: signalling. Central banks do not build reserves only for their own balance sheets. Sometimes, what they hold also sends a signal outward to markets, to investors, to anyone watching closely.

For emerging economies in particular, the mix of reserves can quietly influence how strong or stable a country looks from the outside.

Some analysts say the recent gold buying could partly be about that, projecting resilience in a world where capital can move very quickly.

Still, McGlone is not entirely convinced that signalling explains everything.

When asked whether emerging economies might be building gold reserves partly to reassure international investors, his answer was simple: it is not entirely clear.

“I don’t know,” he said.

However, what he does emphasise is the geopolitical context that triggered the surge in demand.

Russia’s invasion of Ukraine and the subsequent freezing of foreign reserves forced policymakers everywhere to rethink financial vulnerability. The episode highlighted how even large sovereign reserves could suddenly become inaccessible under sanctions. That shock pushed many countries toward alternative assets, including gold.

But geopolitical dynamics are constantly evolving. And in McGlone’s view, the political drivers behind the gold rally may already be fading.

“The geopolitical bid is diminishing,” he said, pointing to shifting political developments in countries often aligned against US influence, including changes in Syria and evolving political pressures in Venezuela, Iran, and Cuba.

If the geopolitical momentum behind gold weakens, the rally could slow as well. Which raises an uncomfortable possibility for central banks: they may have increased their gold exposure precisely when the market was reaching peak enthusiasm.

When reserve diversification goes too far

Gold accumulation has been dramatic. In some ways, it is historically dramatic. But there is also a point where diversification strategies begin to face diminishing returns. For McGlone, that point may already have been reached.

He argues that gold prices have stretched far beyond their historical norms, reaching the largest premium relative to their 60-month moving average ever recorded, and also hitting unprecedented levels relative to the broader Bloomberg Commodity Spot Index.

In other words, markets may have already priced in much of the geopolitical risk. Gold has seen this kind of moment before.

The last time prices became this detached from historical norms was around 1980. That peak held for nearly three decades before being surpassed again during the 2000s commodity boom.

History, McGlone suggests, does not rule out a similar pattern repeating itself. Gold may simply have gone up too much.

“It faces the curse of going up too much,” he said, suggesting the market could be approaching a long-term peak like earlier historical cycles.

If that happens, central banks could find themselves holding larger gold positions at precisely the moment when prices begin stabilising or retreating. This would not invalidate diversification strategies, but it might reduce their immediate financial benefits.

What could push gold even further?

History shows that major geopolitical events can dramatically reshape reserve strategies. Russia’s invasion of Ukraine already triggered one such shift.

That event accelerated discussions about sanctions exposure, financial sovereignty, and alternative reserve assets. But what could push gold even further into the centre of global reserve strategy?

McGlone believes the catalyst would have to be similarly dramatic.

Russia’s invasion created the current surge. Replicating that shock would require a comparable geopolitical rupture. And, for now, he believes the gold momentum may already be reaching its limit.

“The risk is that the bid for gold has reached its apex,” he said.

Inside BRICS: Between unity and rivalry

If gold represents one hedge against the dollar system, BRICS represents another kind of experiment altogether. But even within the BRICS grouping, the financial dynamics are more complicated than they appear from the outside.

According to Lawrence Ngorand, China plays an unmistakably central role in shaping many of the bloc’s financial initiatives.

“China is the central gravitational force within BRICS financial initiatives,” Ngorand told International Finance. That influence stems from simple economics.

China is the largest economy in the group, the biggest trading partner for most other members, and the only one with a fully developed cross-border payments infrastructure capable of supporting large-scale alternative settlement systems.

As a result, efforts to expand local-currency trade often gravitate naturally toward the Chinese renminbi. But that influence comes with political limits.

India, Brazil, and several other BRICS members remain cautious about allowing any single currency to dominate the bloc’s financial architecture. Concerns about dependency and geopolitical balance remain strong, which is why many BRICS initiatives are carefully framed as multi-polar rather than renminbi-centric.

China brings the scale and liquidity, but the set-up of the system still tries to make sure each member keeps the sense that its own financial sovereignty remains intact.

Is a unified ‘BRICS currency’ difficult?

Even setting politics aside, BRICS financial integration runs into a simpler reality. The member economies are very different from each other.

China maintains a tightly managed capital account. India operates with partial controls. Brazil and South Africa run fairly open financial systems compared with some of the others. Russia’s financial system has been reshaped by sanctions and partial isolation. These differences complicate coordination.

Exchange-rate regimes vary. Inflation dynamics differ. Fiscal policy frameworks are not aligned. Even trade structures diverge significantly.

China’s economy is manufacturing-driven. Several other BRICS members depend heavily on commodities. Others rely more on services. These asymmetries make deeper monetary integration extremely difficult.

According to Ngorand, meaningful integration would require convergence across multiple dimensions: inflation targeting frameworks, exchange-rate policy co-ordination, reserve pooling mechanisms, and credible lender-of-last-resort structures. None of those currently exist.

“The bloc lacks the institutional cohesion that underpinned the euro project,” Ngorand said.

Commodity and currency power

Still, one area where BRICS expansion could make a difference is commodities. The inclusion of major commodity exporters within the group has strengthened the theoretical foundation for alternative trade settlement systems.

Countries like Saudi Arabia, Brazil, and Russia sit at the centre of global energy and resource flows. And commodities anchor a significant portion of global trade. If even a small share of these transactions began shifting toward non-dollar settlement, new liquidity corridors could gradually emerge. That possibility matters.

“If even a modest share of oil or critical mineral trade shifts to local currencies, it creates liquidity pools and hedging demand outside the dollar system,” Ngorand said.

However, commodity power alone does not automatically translate into monetary dominance. Even if some commodities start trading in other currencies, the money does not always stay there. In many cases, it quietly circles back to dollar assets anyway.

Take oil revenues. No matter what currency the trade begins with, a large share often ends up parked in United States Treasuries. So, commodities might open alternative payment routes, but that alone does not really dismantle the dollar system. For that, a deeper financial infrastructure would be required.

The shock that could change everything

Ultimately, the speed of any monetary transition depends on shocks. Gradual diversification can go on for years, even decades, without shaking the foundations of global finance. Systems like this rarely change overnight. But, history shows that faster shifts usually come after disruption.

Ngorand suggests that a real acceleration in de-dollarisation would likely require confidence to crack across several pillars of the current financial system at the same time. That could include large-scale sanctions affecting multiple mid-sized economies, a major disruption to global payment networks, such as SWIFT, or a severe dollar liquidity crisis.

Another possibility would be sustained fiscal instability in the United States that undermines confidence in Treasury markets, the backbone of global reserve management. In the absence of such shocks, inertia favours continuity.

“Reserve currency transitions historically occur over decades, not years,” Ngorand said. Which means the dollar system may evolve, diversify, and fragment at the edges without collapsing at the centre, at least for now.

Not the end, just an adjustment

What emerges from all this is not a collapse. It is an adjustment. Central banks are hedging. Governments are managing risk. The world feels more uncertain, thanks to geopolitical, economic, financial, and reserve strategies that reflect that anxiety. The system is becoming more hedged, more political, and slightly more multipolar.

Bhattacharya summed it up thus: “We are not witnessing the end of dollar dominance, but rather the end of unquestioned dollar comfort.”

The dollar remains at the centre. Just no longer alone in commanding unquestioned trust.

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The 2012-13 bailout had left its scars. There were bank haircuts, capital controls, and a new international infamy for economic secrecy. From Riga to Rome, every finance minister complained about the plight of its smaller neighbour and included a mention of “Cyprus” in their geopolitical shorthand.

Fast-forward to 2026, and the footnote has become a case study. The recent update to the real GDP growth forecast sees the pace of expansion slowing to 3.1% this year from 3.8% in 2025. Yes, it is slower than the previous year, but still remarkable for a nation to pull off during all this geopolitical volatility.

Take the latest data, for example. In Q4 2025, Cyprus’ economy expanded 4.5% on a year-on-year basis, up from 3.6% in the previous period. The milestone also marked the strongest economic expansion since Q4 2022, with the main drivers being the wholesale and retail trade, repair of motor vehicles, information and communication, and hotels and restaurants (+7.2%). Construction also recorded strong growth, rising 9.2%, while manufacturing increased by 4.7%.

In another piece of good news, tourist inflows (which skyrocketed to €3.7 billion in 2025) from the United Kingdom, Germany, Poland, Israel, Greece, France, and Sweden played a solid hand in propelling Cyprus to its historic GDP growth, while the Mediterranean island emerged as one of Europe’s most sought-after destinations. The boom also benefited the airline and hospitality industries, with airlines like British Airways, easyJet, and Ryanair expanding their services to accommodate the ever-growing number of visitors. Hotels and resorts in the island region, on the other hand, responded by ramping up their offerings, from luxury accommodations to eco-friendly resorts, ensuring a diverse range of options for all types of travellers.

Remarkable fiscal story

In 2025, Cyprus recorded a budget surplus of €939.2 million. Let that sink in for a moment. We are talking about a small island country with its own unique set of problems and challenges. The country is located in a volatile region, subject to tensions between Greece and Turkey. There are also costs associated with meeting EU targets for reducing carbon emissions and the costs of bringing salaries for government workers in line with those in the private sector. The employee salaries peaked at €4.13 billion in 2025. And yet, a budget surplus of €939.2 million was still recorded.

The ceiling for next year’s state budget is €10.7 billion, or €11.3 billion without interest costs. It is a political and economic price that was set with considerable care. In a eurozone periphery country such as Cyprus, this is something seen rarely and achieved even more rarely, as the fiscal discipline required is not always accompanied by the same degree of political consensus. The fiscal leeway was available, but action only followed as the debt crisis escalated and a new government came into power at the end of 2023, when public debt was at 73.6% of GDP. Now it is projected to fall to 52.9% of GDP by the end of 2026. This is no small reduction. It is a reduction of a historical and almost revolutionary character.

According to Cyprus’ Deputy Finance Minister Irene Piki, “Multi-year planning, more predictable policy, and fiscal space earned through responsible and reform-based ways rather than increased borrowing ensures high household, business, and investor confidence.”

She is right. And the timing of this issue must also be taken into consideration. With the war in Ukraine, energy-price volatility, and the costs of achieving the EU’s ambitious climate and digital agendas, Europe’s overall fiscal situation is extremely difficult. Most member states are feeling the strain, though a few, such as Poland, are coping better than expected. Others, like Bulgaria and Slovenia, will hardly notice any short-term impact from the EU’s fiscal rules for the next few years.

Cyprus is not in this group, but it will no longer be in the minority either. It will assume the EU Council presidency in the first half of 2026, at a time when all other member states with higher budget deficits will be trying to keep a low fiscal profile in advance of a potential EU debt-mutualisation discussion, while others will be more than happy to oblige by not questioning the fiscal prudence of the presidency. Cyprus’s economic model, which has proven itself in recent years to be sustainable despite high inflation and even though the country is heavily indebted, should attract worldwide attention during its presidency and generally face appreciation for its achievements.

The tech revolution

Here’s an honest take. Tourism is the story that gets the headlines, but tech is stealing the show, and that’s where the smart money is heading.

By the end of 2025, Cyprus’s Information and Communications Technology (ICT) sector contributed roughly 16% to national Gross Value Added (GVA). That is approximately €8.5 billion. The island now ranks second in the EU for ICT’s share of national GVA, ahead of economies with ten times the population and four times the infrastructure investment. The workforce in tech has more than tripled over the past decade, now exceeding 26,000 professionals. Cyprus ranks fifth in the EU for GVA per ICT employee. In productivity, in other words, not just headcount.

The talent pipeline is being deliberately engineered. Non-resident professionals earning over €55,000 annually get a 50% income-tax exemption. There is also a Digital Nomad Visa and streamlined residency for spouses of international workers. The type of person this attracts is mobile, high-earning, plugged into global networks, and likely to bring their employer with them or start something new once they are settled. In March 2026, the Research and Innovation Foundation sent a national pavilion to the 4YFN summit in Barcelona, showcasing eight companies in AI, robotics, and agritech. One Cypriot portfolio company, Threedium, was selected as one of only ten firms globally to present on the main NVIDIA GTC 2026 stage. That’s not luck.

TechIsland, the sector’s coordinating platform, has done the unglamorous but essential work of bridging local entrepreneurs with international executives. The ecosystem is self-reinforcing now, which is the point where you stop worrying about whether it is sustainable and start worrying about whether the housing stock can keep up.

What are the key factors helping the country’s tech sector? Let’s start with Cyprus’ geographical location. The Mediterranean island sits at the intersection of Europe, the Middle East, and Africa, giving companies access to huge markets if they prefer using the nation as their manufacturing and R&D hubs. Imagine businesses keen on maximising their prospects in the European market but also want outreach to Israel’s $100 billion tech sector, along with emerging Middle Eastern and North African (MENA) countries, Cyprus can become the base camp. Also, the country’s legal system is rooted in English common law, making it instantly familiar for those used to British or commonwealth standards.

Then comes the 12.5% corporate tax rate, one of the lowest in the European Union (EU). To sweeten things further, there is an “IP Box Regime” that results in qualifying intellectual property income being taxed at an effective rate of just 2.5%. Businesses holding IP in domains like software, AI, fintech patents, or video games get massive leverage for reinvestment and expansion in the Mediterranean island, as taxation remains simplified and pocket-friendly, compared to high-tax countries. The administration is actively courting the cause of the island nation becoming a regional tech hub by backing initiatives such as “Startup Cyprus” and the “Youth Entrepreneurship Scheme.”

Promise of energy utopia

Shipping accounts for more than 7% of the country’s GDP and often receives insufficient attention in debates that focus on new sectors. Now, though, the evidence is plain to see. The shipping sector is a major source of revenue. Cyprus alone accounts for around 4% of the global merchant fleet, while more than 20% of worldwide third-party ship-management activities are carried out from here. The figure for ship-management revenues for the first half of 2025 was €978 million, an increase of 6.7% on the previous quarter.

And that’s a lot of concentration! The top 27% of the companies account for 85% of total sales. Germany and Greece are the number one and two trading partners, respectively, accounting for 30% and 13% of sales.

In November 2023, the One-Stop Shipping Centre was established, which currently serves more than 300 shipping companies benefiting from the tonnage-tax regime. Almost all shipping companies based in Cyprus benefit from this, apart from the four historical ship-owning companies, which, in accordance with the current tonnage-tax legislation, are not allowed to gain an advantage through the new policies.

The overall gross tonnage of the Cyprus ship registry has increased by 20% over the last two years, reaching the highest level in the last two decades. A real and tangible effort is being made to modernise shipping further through the sponsorship of robotics and digital-technology-related scholarships and the upgrading of the associated educational infrastructure, as well as research into alternatives and new methods to support the greening of shipping. Shipping contributes significantly to the island’s employment sector, both in terms of direct and indirect on-shore employment (over 9,000 people) and the huge number of seafarers (80,000 and more) employed onboard vessels managed by companies based in Cyprus and therefore also indirectly contributing to the economies of the ports of call. Cyprus wants to maintain and further develop this very important sector.

Gas fields have been “coming soon” for years, and one can excuse the sarcasm. But now, for the first time in more than a decade, all indications are that 2026 will actually see the start of production of two giant offshore fields in Eastern Mediterranean gas. The Aphrodite gas field in Block 12, estimated to hold between 3.9 and 4.5 trillion cubic feet of gas, is slowly but surely moving towards its commercial development, following the recent memorandum of understanding signed by Egypt, Cyprus, and Chevron over the proposed pipeline project that will transport the gas from Cyprus to Egypt. The Kronos field in Block 6, operated by Eni, is also expected to reach a final investment decision this year, with first gas scheduled for 2028. The fact that the distance between the field and the Zohr field in Egypt, where the necessary infrastructure has already been built and is currently being used, will be largely compensated for by the intended infrastructure that will be built for the purposes of transporting Aphrodite’s gas to Egypt.

The energy situation in Cyprus is quite tough domestically. The EU carbon-allowance price is projected to reach €95 per tonne by 2026, and there is no exception for Cyprus in terms of compliance with the EU ETS, which will cost €490 million this year and will also be transferred to consumers through energy bills. The LNG terminal of Vasilikos, which has been delayed for many years, is expected to enter operation during the second half of 2026. The Great Sea Interconnector, which connects the Cypriot electricity grid with the Greek grid via Israel, is still considered a strategic investment, but is more at the level of intentions so far.

The offshore gas story is truly a major issue for the Eastern Mediterranean region’s energy future. In the meantime, however, Cypriots are forced to endure among the highest energy prices in the region. That is where the current government’s otherwise respectable record falls short.

Tax exemptions to the rescue

The story of the revival of the banking system in Cyprus is a very long and fascinating one. We are talking about a sector where non-performing loans (NPLs) comprised 49% of the total outstanding loans in 2016. It was not so much a sector with problems that required remedial action; it was a complete banking crisis that had been frozen in time. Today, the total of NPLs as a percentage of total outstanding loans is 3.2% at the end of 2025. The downward trend of NPLs, following a period of stagnation that coincided with the imposed capital-control regime of 2013, reflects in part the huge quantities of NPLs that have been sold and in part the successful completion of a large number of restructuring plans of exposures.

There was a big change in Cypriot tax law, and we believe it is the first significant change in tax laws introduced in the last two decades. The new laws took effect on 1 January 2026. Under the catch-phrase of meeting the OECD Pillar Two global minimum-tax rate, we are talking about a drastic increase in the corporate-tax rate from 12.5% to 15%. As such, it has been a very controversial move, and one can very easily understand why. But it was an inevitable decision.

Dividend tax has increased. The deemed-dividend distribution rules for profits earned after 2026 have been abolished. The special defence contribution on the actual dividends paid out from profits earned after 2026 reduces from 17% to 5%. The personal-income-tax-free threshold has increased to €22,000 from €19,500. The 8% flat tax on cryptocurrency gains and the 120% super-deduction for qualifying research and development expenditure are a couple of steps taken towards the future. A couple of things to note regarding the recent corporate-tax-rate increase and how it is being applied in the professional-services sector. Companies in the sector are already shifting toward digital assets, AI-related regulation, and wealth-mobility advisory services in response to the tax-rate increase. The pace of change can be dramatic.

Misfortune of thriving real estate

The consequences of rapid expansion are inevitable. As reported earlier, property transactions in January 2026 reached their highest level since 2008, with 1,411 contracts being deposited, an 11% increase on the corresponding period last year. Annual price rises in Paphos and Famagusta reached 25% and 23% respectively. The value of transactions in the Limassol premium market accounts for a third of the total.

As we already know, the rate at which property prices increase is around 5%–7% annually, and salaries in the country are still not high enough to absorb even remotely the current rental rates. Rent accounts for a staggering 32.3% of the average household’s monthly income in Limassol. The average monthly rental price for a one-bedroom apartment in the city centre of Limassol is around €1,300.

The government plans to complete 244 affordable residential properties allocated to low-income families in all major municipalities across the country by the end of 2026, while a private partnership is expected to deliver 1,000 affordable rental homes, with the municipality also expected to set aside €16 million for a new subsidised project in Limassol and €12 million for a similar scheme in Strovolos. This is not bad, but there are still very few measures to curb the problem of affordable housing. Remember, however, that problems related to affordability usually go unnoticed for years until they hit the headlines and cause mayhem.

Tourism income has reached €3.69 billion, up 15.2% year-on-year, with visitor numbers exceeding 4.5 million for the first time, and tourism’s share of GDP standing at around 14%. A services surplus of over €2.8 billion was recorded in the third quarter of 2025 alone, in large part due to the goods-trade deficit being a structural feature of the economy.

Tourism is trendy but is cyclical, weather-dependent, geopolitically volatile, and above all requires low-cost air travel. In the technology and shipping space, the trends are more structural. We are not diminishing the success of tourism, which remains very strong, but policymakers need to remember that it is just a base that needs to be expanded upon rather than a plateau to be sat out on.

The bottom line

The future looks promising, but it is not without challenges. The job market is extremely tight, with unemployment at just 4.5%. It means everyone who needs a job has a job, but there aren’t enough workers to boost spending power any further.

Cyprus has 1.38 million people and is one of the EU’s smaller member states, with most of them residing in cities like Nicosia and Limassol.

Though the population is growing through immigration, the median age is around 40 years, which means that people are ageing quickly and productivity is decreasing. On top of that, birth rates are really low, with around 1.5 children per woman.

Cyprus is struggling to find fresh talent. And it is in a race against time. If they cannot find enough working population to support their rapidly ageing population, their economy could suffer greatly.

Moreover, foreign firms invest heavily in Cyprus but pull back profits. The repatriation of profits contributed to around 7% of the GDP account deficit. The Fiscal Council notes that domestic reinvestment is weak and FDI seems “transient” without deeper local ties.

To combat this, Cyprus introduced new screening rules. From April 2, 2026, non-EU and Swiss investors need pre-approval for €2 million plus deals that require a 25% or more stake in strategic sectors such as AI, tech, health, and energy. If they do not comply, they risk fines up to €50,000 or a shutdown due to non-compliance. The bureaucracy adds two to three months of delay, increased legal fees, and various uncertainties for companies that want to invest in the island. Investors might want to look for other nations with better ease of doing business.

Cyprus has historically attracted FDI through lax rules, but is now forced to align these standards with the EU. However, this oversight often leads to increased friction through red tape, and geopolitical checks (Investigating Russian and other controversial links). Foreign investors were drawn to low taxes and golden passports, which ended in 2020. Massive FDI, especially from Russian companies, peaked at $33 billion in 2015 and fueled the real estate boom. Russian investments reached 80% of the total FDI of Cyprus. However, it also enabled round-tripping and sanction evasion after the Ukrainian crisis.

The 2024 data from the Central Bank of Cyprus reveals that Russian FDI stock in Cyprus hovers at €83.46 billion and has plummeted drastically from €135.7 billion in 2022. The €52 billion drop is attributed to Western sanctions and geopolitical tension.

Look, small open economies are always vulnerable to things they cannot control, such as energy shocks, regional conflict, shifts in EU policy, and global capital-flow reversals. Cyprus is not immune. But the combination of fiscal discipline, a diversified sectoral base, a sophisticated banking system, and a government that has made genuinely difficult structural decisions creates a degree of resilience that was not there a decade ago. These are not vanity metrics. They are signals that the growth dividends are being reinvested rather than extracted.

Is everything perfect? No. Energy costs remain a drag. Housing affordability is a genuine social tension. And the gas fields, however promising, have a long way to go before they change balance-of-payments arithmetic.

But Cyprus in 2026 is a fundamentally different proposition than it was in 2013. It has earned the right to be taken seriously. Definitely not as a tax-haven footnote or a bailout cautionary tale, but as a small economy that looked hard at what it wanted to be and built its way toward it with more discipline than most expected. That’s a story worth telling.

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And yet, up to three-quarters of companies are still using paper checks, for example, despite inefficiencies and increasing costs. While traditional document handling and processing might seem familiar and reliable, they are fast becoming outdated and potentially hazardous for companies and customers.

Digitalisation, of course, can be complex, and there is considerable planning and execution involved that can take months to complete. However, one key step finance companies (and those processing paper transactions en masse) should take immediately is to switch to digital signatures across all their documents.

Why digital signatures matter

Digital signatures have emerged as a natural successor to the well-worn paper-based standard. Through digital contract signing and payment authorisation, key transactions are easier to attach to certain parties, and it’s a quick route towards ensuring complete compliance with data retention and processing.

Learning how to sign documents online is, in the mid-2020s, a simple process that’s easy to train on and roll out across payment handling teams. We now have the systems and software to embed digital signatures into legacy tools and documents, too, meaning it can easily become part of existing processes at minimal cost.

Shockingly, reports show that 63% of companies surveyed by the AFP experienced some form of physical check fraud in 2024. If we’re to face transaction fraud head-on, we need to move more efficiently away from paper documents and legacy signage.

Key benefits

Beyond the obvious benefits of digitalisation in general, there are key benefits of digital signatures in financial transactions worth considering.

Digital signatures allow for faster processing and decision-making. The time it takes for physical checks and financial documents to get signed, authorised, and marked off can be cut down dramatically with automation and streamlined workflows. There are fewer checking steps, and reviews take seconds, not days.

They are more securely stored. Using a leading e-signature platform and data backup system means you can always be sure client signatures are encrypted and kept away from bad actors. Physical documents are always at the mercy of being lost and stolen, which can cause fraud and administrative headaches for all parties involved.

Another security benefit to digital signatures is that, with the right platform, they are easy to create and store so that they can’t be tampered with by third parties. Again, a digital paper trail can effectively verify signing intent and payment processing without confusion. Digital signatures also benefit compliance. In an age where companies face millions of dollars in potential fines for not complying with data protection laws, digital signatures can effectively prove that a company is doing enough to meet certain standards.

Ultimately, digital signatures remove the costs of physical document processing and the checks required along the way. Therefore, this form of digital streamlining frees up administrative hours that can be used more cost-effectively elsewhere.

The future of digital signatures

There are many ways that digital signatures will continue to evolve in finance in the years to come. For one, artificial intelligence can learn to recognise signatures from data to automatically approve payments, calculate money received and sent, and search for anomalies.

What’s more, companies may also use blockchain technology to create records and contracts with even more irrefutability. Digitally signed documents, established on the blockchain, will be even harder to counterfeit or dispute.

Up to 80% of US businesses are already using digital signatures in some shape or form, with that number likely to grow exponentially by the start of the next decade. However, now is the time to start taking steps towards making signage digital, regardless of what trends suggest.

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Finance teams rarely struggle because they lack discipline or effort. They struggle because revenue, lease obligations, approvals and reconciliations sit across disconnected systems, often stitched together by spreadsheets and manual handoffs. As transaction volumes grow and monetisation models become more complex, those seams begin to show.

In this environment, automation is not about speed alone. It is about reducing opacity, strengthening governance and enabling finance to scale without increasing risk.

Research from the American Productivity & Quality Centre (APQC) shows that top-performing organisations close in four to five days, while others may take 10 days or more. As standards such as ASC 842 and IFRS 16 increase reporting complexity, spreadsheet-driven processes introduce higher exposure to error and compliance gaps. For senior finance leaders, the question is no longer whether to automate, but how to do so in a way that embeds control directly into the operating model.

Drivers of close fatigue

Manual month-end activities create predictable pressure points: intercompany reconciliations, revenue recognition adjustments, lease accounting calculations and journal approvals that span multiple platforms. Each manual transfer of data increases the likelihood of delay, inconsistency or error.

Regulatory expectations continue to rise. Frameworks such as the COSO Internal Control – Integrated Framework emphasise documented controls, segregation of duties and traceable audit trails. In many organisations, these controls still depend on manual review and post-close validation.

The result is a reactive closed cycle. Issues surface at the end of the period, when timelines are tight and corrective action is costly. Automation, when designed correctly, shifts finance from reactive correction to continuous control.

Finance automation best practices

Automation works best when processes are simplified and clearly defined. Finance leaders should map month-end activities end-to-end, identifying dependencies and eliminating unnecessary steps. Standardisation reduces variability and creates the foundation for scalable automation across business units and geographies.

Disconnected ERP, billing, contract and lease systems are a primary cause of reconciliation delays. Integration at the data layer ensures transactions, adjustments and contract changes flow automatically and consistently, giving teams a single source of truth.

Recurring activities such as accruals, amortisation schedules and lease calculations should be governed by predefined system rules. This reduces manual intervention and strengthens audit trails. More advanced automation flags unusual transactions or anomalies during the period rather than after close. By surfacing exceptions early, finance teams avoid last-minute surprises. Increasingly, advanced platforms use embedded intelligence to flag anomalies mid-cycle rather than after close.

Regulatory standards require not only accurate calculations but documented controls. Automated approval flows, version tracking, and role-based access controls ensure that changes to contracts or accounting treatments are captured transparently. When compliance is built into the workflow, audit readiness becomes continuous rather than cyclical.

Dashboards that display reconciliation status, outstanding approvals and exception trends provide finance leaders with visibility throughout the month. Instead of discovering bottlenecks at the end of the cycle, teams can address issues proactively. The shift from periodic reporting to continuous monitoring reduces risk and improves predictability.

Automation as a strategic lever

For organisations with complex revenue models, large lease portfolios or multinational operations, the stakes are higher. Each new pricing structure, geographic expansion or regulatory requirement adds reconciliations and control points to the close. Without automation, headcount and spreadsheet dependency grow alongside complexity.

Well-designed automation enables scale without proportional increases in cost or risk. Systems can absorb higher transaction volumes while maintaining consistent controls and audit trails. Finance teams spend less time gathering and validating data and more time analysing performance, forecasting outcomes and advising the business.

In a regulatory environment that demands transparency and precision, automation is not simply an operational enhancement. It is a governance decision. Finance leaders who take a structured approach create a close process that is faster, more resilient and better aligned to strategic growth.

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This comprehensive research report provides an exhaustive analysis of the current state of Financial Crime Compliance. It synthesises the seismic operational impacts of the European Union’s implementation of the 6th Anti-Money Laundering Directive and the activation of the Anti-Money Laundering Authority in Frankfurt. It scrutinises the United Kingdom’s controversial centralisation of professional services supervision under the Financial Conduct Authority. Across the Atlantic, it dissects the aggressive extraterritorial reach of the US Department of Justice, exemplified by the historic asset cap and multi-billion-dollar penalties levied against TD Bank and the criminal convictions of cryptocurrency giants like KuCoin.

Furthermore, this report analyses emerging laundering typologies that exploit the very digitalisation intended to modernise finance, including the misuse of white-label banking infrastructure, the layering capabilities of virtual IBANs, and the terrifying efficacy of AI-enabled deepfake fraud. These vectors have necessitated a complete architectural overhaul of transaction monitoring systems, forcing institutions to abandon static rule-based systems for dynamic, AI-driven behavioural analytics. The “compliance-as-an-afterthought” model, which fuelled the fintech unicorn boom of the 2010s and early 2020s, has effectively collapsed. The forced exit of founders from major neobanks like N26 and the bankruptcy of embedded finance providers like Railsr demonstrate that regulatory resilience is now the primary determinant of commercial survival.

EU’s regulatory revolution

The operationalisation of the EU’s AML Package in 2024 and 2025 represents the most significant restructuring of the bloc’s financial defence architecture since the introduction of the Euro. Now comes the new way of handling rules, with fewer top-down orders and one clear book for everyone. It means firms across Europe face different demands than before, shaped by deeper political goals. The aim? To avoid gaps so large that they let trouble sneak through, just like what happened at Danske Bank.

Nowhere else does history shift so clearly. The AMLA era replaces the old ways of isolated national bodies working apart. Based in Frankfurt, this authority is moving fast, staffing up through 2027 while gaining real oversight tools by 2028, especially for higher-risk cases. Unlike the EBA before it, which shares advice but lacks enforcement teeth, here power flows directly, bypassing local authorities entirely. Straight oversight goes to selected risky overseas finance units, setting strict rules and major monetary penalties that target them specifically, blocking any attempt to dodge through loopholes.

Across the wider market still within national oversight, AMLA takes on a firm monitoring role, working closely with state agencies to maintain uniform enforcement of the Single Rulebook. Its funding structure reflects self-sufficiency in operations, shielded from fluctuations in political funding allocations.

From 2028 onwards, approximately 70% of its €92 million annual budget will be funded by fees levied directly on the obliged entities it supervises. The fee structure ensures that institutions creating the highest systemic risk bear the financial burden of their supervision.

The legislative twin pillars, the 6th Directive and the AML Regulation, have harmonised definitions and drastically expanded the perimeter of regulated activities. The 6th Directive codifies a unified list of twenty-two predicate offences across all member states, now explicitly including cybercrime, environmental crime covering illegal logging and waste trafficking, and tax crimes. For multinational corporations, this harmonisation removes the dangerous ambiguity where an act considered a predicate offence in one jurisdiction might not have triggered money laundering reporting in another.

The AML Regulation significantly broadens the definition of “obliged entities,” those required to perform Customer Due Diligence and file Suspicious Activity Reports. The regulatory perimeter now captures crypto-asset service providers, high-value goods traders in precious metals and cultural artefacts, professional football clubs and agents, and crowdfunding platforms facilitating peer-to-peer financing. Transparency of beneficial ownership remains a cornerstone of the EU strategy, with the new framework mandating a unified ownership threshold of 25%. A critical “risk-based” provision empowers the European Commission to lower this threshold to 15% for high-risk sectors. The directive mandates the interconnection of national beneficial ownership registers via a central European platform, closing the loophole whereby cross-border corporate structures could obscure the Ultimate Beneficial Owner. To curb the anonymity provided by physical currency, the AML Regulation introduces a Europe-wide cap of €10,000 on cash payments in business transactions.

The 6th Directive introduces stringent corporate liability provisions that directly impact the C-suite. Legal persons can be held criminally liable if a “lack of supervision or control” by a person in a leading position made the money laundering possible. For Chief Financial Officers and Corporate Treasurers, the expansion of definitions regarding aiding and abetting means executives can be prosecuted for facilitating laundering through negligence or wilful blindness. The requirement to verify beneficial ownership for all suppliers and partners necessitates a massive overhaul of vendor management systems.

UK’s supervisory consolidation

While the European Union centralises authority in a new supranational body, the United Kingdom is dismantling the fragmented supervisory regime criticised for its inefficiency. The government’s decision to appoint the Financial Conduct Authority as the Single Professional Services Supervisor marks a watershed moment for lawyers, accountants, and trust and company service providers. The move represents a fundamental shift away from professional self-regulation toward a statutory, state-controlled model of AML oversight.

The catalyst for this radical reform was the consistent underperformance of the Professional Body Supervisors, the twenty-two self-regulatory bodies responsible for overseeing AML compliance in the legal and accountancy sectors. The Office for Professional Body Anti-Money Laundering Supervision issued a damning report in September 2024 that effectively sealed the fate of the self-regulatory model. The report found that none of the assessed supervisors were fully effective in all areas of supervision; the majority showed no material improvement, with some even regressing; and there was systemic reluctance to issue fines or take enforcement action. This highlighted the inherent conflict of interest between the bodies’ representative roles and their supervisory duties.

Under the new SPSS model, the FCA will assume sole responsibility for AML supervision of professional services firms, with full operational transfer projected by 2028. The legal profession has vehemently opposed this move, viewing it as an erosion of professional independence. Concerns centre on whether a statutory regulator rooted in financial markets culture will respect the nuances of Legal Professional Privilege, the significant fees the FCA is expected to levy, and the clash between the FCA’s “rules-based” approach and the “principles-based” regulation to which the legal sector is accustomed. However, the government’s stance remains firm. The risk of professional enablers facilitating high-end money laundering outweighs the preference for self-regulation.
US’ enforcement doctrine

The United States is enforcing the existing rulebook with unprecedented aggression. Enforcement actions of 2024 and 2025 have shattered the notion that global banks are “too big to jail.” The focus has shifted from monetary penalties to structural constraints that threaten the very growth of non-compliant institutions. The guilty plea by TD Bank in October 2024 serves as a definitive case study for the modern AML failure. The bank agreed to pay over $3 billion in penalties to resolve investigations by the DOJ, the Financial Crimes Enforcement Network, and the Office of the Comptroller of the Currency.

The TD Bank case was a systemic collapse of defences, facilitated by a corporate culture that prioritised speed and cost-cutting over compliance. Court documents revealed laundering networks that operated with impunity, including one that physically dumped piles of cash on bank counters in Queens and a sophisticated network that utilised the bank to withdraw funds via ATMs in Colombia through complicit bank employees. The DOJ explicitly cited the bank’s prioritisation of growth over compliance controls, noting that for nearly a decade, the bank failed to update its transaction monitoring scenarios.

While the $3 billion fine was historic, the arguably more damaging penalty was the asset cap imposed by the OCC, preventing TD Bank’s US retail subsidiaries from growing their assets beyond the October 2024 level of $434 billion. The penalty structure represents a profound shift in regulatory strategy, as fines can be absorbed, but asset caps stagnate the business, depress stock value, and invite shareholder litigation. For a bank, the inability to grow its balance sheet is a slow-motion death sentence for its strategic ambitions. The US approach has set the tone for global enforcement, with the DOJ and FinCEN targeting not just institutions but individuals and infrastructure, with reach extending far beyond US borders.

The crisis of architecture

The years 2025 and 2026 have been a reckoning for the fintech sector. The “move fast and break things” ethos has collided violently with AML regulations, exposing vulnerabilities inherent in Banking-as-a-Service and white-label models. The result has been bankruptcies, license revocations, and forced leadership changes. White labelling allows non-bank entities to offer financial products using the license and infrastructure of a regulated provider. An EBA report published in October 2025 identified this model as a critical money laundering vulnerability, with risk stemming from the structural disconnect between the customer-facing brand and the regulated entity holding the license.

The bankruptcy of Railsr remains the cautionary tale of the sector. Railsr’s subsidiary, PayRNet, had its license revoked by the Bank of Lithuania in mid-2023 for serious AML violations, including the failure to safeguard client funds and inadequate due diligence. The revocation revealed that PayRNet had effectively lost control of its resellers and could not identify the end users of its virtual IBANs, allowing illicit flows to move unchecked through its rails.

German neobank N26 provides a vivid case study in the friction between hyper-growth and regulatory containment. Following repeated AML failures, the German regulator BaFin imposed a draconian cap on new customer acquisitions in 2021. The cap was lifted in mid-2024, but by late 2025, BaFin had reimposed restrictions, specifically banning N26 from issuing mortgages in the Netherlands due to continued compliance deficiencies. The sustained regulatory pressure culminated in a governance crisis, with investors pushing for the exit of the bank’s founders by early 2026, marking the end of the founder-led era.

The digital frontier

By 2026, the cryptocurrency landscape had transformed significantly compared to the chaotic environment of 2020. The introduction of the Markets in Crypto-Assets (MiCA) regulation in Europe, along with the global implementation of the Travel Rule, tightened privacy measures. In the United States, there was a strong crackdown on cryptocurrency exchanges through criminal cases based on financial laws. One notable exchange, KuCoin, took responsibility in early 2025 for managing unreported funds and faced charges related to the Bank Secrecy Act. The total penalties amounted to nearly $300,000,000. A federal court case revealed that KuCoin operated without the necessary permissions, marketing itself to American users while completely bypassing identity verification checks. Labelled as a “No-KYC” exchange, it allowed anonymous traders to participate from across the country. As a result of circumventing regulations, more than five billion dollars flowed in from unclear, potentially criminal sources.

A penalty of $100 million handed to BitMEX in 2025 marks another shift toward personal responsibility, with its founders ordered to serve time in a criminal capacity. It was determined that the platform deliberately ignored anti-money laundering requirements to increase earnings, handling vast sums, trillions, without any customer verification. Even as traditional exchanges grow stricter, new paths for illicit finance begin to take shape. Funds tied to Tornado Cash face US restrictions, which weakened their purpose, since major trading platforms now reject deposits linked to named mixing routes. Instead of vanishing, privacy altcoins such as Monero lose access to major platforms, shrinking the trader activity needed for broad-scale illicit flows. Lurking beneath old tactics, launderers now lean on “chain hopping,” shifting value across network borders using the latest bridge technology. These moves blur transaction links simply because paths between blocks go unnoticed for longer.

By 2026, the Financial Action Task Force’s “Travel Rule” will have become a global operational standard. In the EU, regulations mandate that all transfers of crypto-assets must be accompanied by identifying information of the originator and beneficiary, effectively applying SWIFT-style wire transfer transparency to the blockchain. This has forced Virtual Asset Service Providers to implement complex messaging protocols, creating a closed loop of regulated entities.

The new typologies of financial crime

The 2026 threat landscape is defined by the abuse of complex payment infrastructure and the weaponisation of Generative AI. Virtual IBANs are routing numbers that redirect payments to a master physical account. While legitimate for treasury management, they are a potent tool for money laundering. A criminal opens a master account with a fintech company, then generates hundreds of virtual IBANs, assigning them to shell companies. Funds flow into these virtual accounts and are instantly commingled in the master account, obscuring the origin from transaction monitoring logic. The AML Regulation now requires issuers to link every virtual IBAN to the underlying master account in centralised registries.

The “Deepfake CFO” scam in Hong Kong, which resulted in a $25 million loss, stands as the grim milestone of AI-enabled fraud. Fraudsters used deepfake technology to recreate the company’s CFO and other colleagues in a “live video conference.” By 2026, over 42% of fraud attempts are AI-driven, with deepfake “injection attacks” increasing by over 2000%. This has rendered simple video KYC obsolete, with financial institutions rushing to implement passive liveness detection and biometric analysis capable of spotting microscopic artefacts left by generative AI.

Strategic outlook

The EU Single Rulebook and the UK’s SPSS model mean that regulatory arbitrage within Europe is effectively dead, with firms needing to adopt a “highest common denominator” approach to compliance. The extension of criminal liability to executives and the aggressive prosecution of founders means that AML compliance is a direct responsibility of the Board and C-suite. Legacy systems that cannot handle virtual IBAN transparency or detect AI deepfakes are now existential vulnerabilities, with investment in RegTech no longer an IT upgrade but a license to operate. The era of “growth at all costs” has been superseded by the era of “compliant growth or no growth.” The regulatory perimeter has expanded to encircle the entire digital economy, and the penalties for stepping outside it have become existential. For financial institutions and their leaders, the message from regulators in Frankfurt, London, and Washington is unified. Compliance is the new currency of trust.

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Starting with early rule-based programmatic trading in the 1970s and 1980s, finance firms have long applied statistics and computing to markets. In the 1990s and 2000s, machine learning and neural networks added sophistication.

For example, hedge funds like Renaissance Technologies hired PhDs to use AI for pattern recognition. Today, we stand at a new inflexion point with generative AI and large language models that can process massive streams of text and data and even suggest novel trading ideas. As one Wharton finance expert notes, AI’s evolution “from algorithmic trading to personalised advice” has made finance “fertile ground for AI innovation.”

Applications of AI in finance

AI is now embedded in many financial processes. Broadly, AI serves in trading, analysis, and operations. In trading, automated systems place orders faster than any human can. High-frequency trading algorithms, often powered by machine learning (ML), make thousands of small trades every second to exploit tiny price discrepancies. Many of the largest trading venues are dominated by such “automated trading” in highly liquid assets. In other domains, AI systems read and summarise information.

For example, NLP tools scan newsfeeds and social media to gauge market sentiment, a process known as sentiment analysis. A sudden burst of negative tweets about a company might trigger selling by algorithms. In risk modelling and compliance, AI churns through vast data to calculate creditworthiness or portfolio risk in real time.

Advisors and insurers use AI to predict defaults or claims, while banks deploy chatbots to handle customer queries. In short, AI touches everything from trade execution to loan approvals and is effectively “democratising” access to analytics that only big institutions once had.

The influence of AI and algorithms is clearest in a few headline-grabbing episodes. In January 2021, the GameStop saga showed the power of social sentiment and automated strategies. A surge of retail traders on Reddit’s WallStreetBets sent the share price of the video-game retailer GME skyrocketing over several days.

Hedge funds that had short positions in the stock rushed to close them. Eventually, trading apps temporarily halted trading, igniting a political firestorm. Researchers note that “retail investors using the Robinhood platform” collectively drove the sharp price swing. Although that episode was driven by human coordination online, it attracted algorithmic responses, with some trading bots detecting the rapid price trend and either piling in or pulling out, amplifying volatility.

AI-driven trading has also featured in the activity of quantitative hedge funds. Firms like Renaissance Technologies, Two Sigma, DE Shaw, and others have long used machine learning to devise strategies. A 2019 survey identified those four as pioneers in AI-driven investing. These firms process vast alternative datasets, from satellite imagery of retail parking lots to aggregated price patterns, looking for subtle predictive signals.

For example, AI can spot that a retail chain’s lawns are greener or read thousands of local news sites to update earnings estimates. In late 2022, Reuters reported Renaissance’s quant funds using models to target returns. Although strategies are secretive, experts agree that AI “provides a competitive advantage” in systematic trading.

AI and social media can also combine in troubling ways. Studies and news accounts warn of sentiment manipulation using bots. In a recent report, experts imagined hundreds of AI-generated social media profiles pushing a narrative about a stock. Real people reacting to the buzz drive the price up or down, while those who detect the narrative profit.

The danger is that neither the promoter nor some of the manipulators even realise they’re part of a larger AI-driven scheme, making enforcement hard. In practice, regulators have seen smaller-scale attempts in crypto and DeFi, where “malicious actors…deploy AI bots” on platforms like Telegram to hype assets.
These examples highlight how automated sentiment analysis and engagement can influence markets, sometimes legitimately, with bots surfacing true trends and at other times through coordinated pumping.

Speed, scale and smarter markets

The attraction of AI in finance is clear, as it does things humans cannot. Speed and automation are paramount. Machines can execute orders in microseconds and monitor markets around the clock, far faster than any trading floor. This rapid processing tightens bid-ask spreads and improves liquidity in normal times.

As the IMF notes, technology has “improved price discovery, deepened markets, and often dampened volatility” in normal periods. AI also excels at scalability and data processing. Financial markets generate enormous volumes of data on prices, news, social posts, filings, and satellite images, and AI can sift through it all.

Advanced neural networks and LLMs (Large Language Models) can turn unstructured text into structured signals. For instance, a generative model can instantly read a regulatory filing or earnings call transcript, flagging risks or opportunities. The IMF notes that generative AI lets investors “process very large amounts of unstructured, often text-based, data,” which can improve forecasts and price accuracy.

Another benefit is pattern recognition and precision. AI algorithms can spot complex statistical patterns that humans cannot see, such as nonlinear relationships or high-dimensional correlations.

In portfolio management, for example, deep-learning models and reinforcement learning (RL) can adapt trading rules over time. Quantitative analysts now use RL to optimise asset allocation dynamically, a method well-suited for constantly shifting markets.

These models “identify complex patterns in large datasets” by using millions of parameterised rules, going far beyond traditional formulae. In effect, AI can tailor strategies to ever-changing conditions, learning minute details of market microstructure.

This leads to efficiency and consistency, and routine tasks like compliance checks or customer service get automated via RegTech tools and chatbots, freeing humans for higher-level thinking. In trading, even a tiny improvement can be valuable. A recent AI pilot by HSBC reportedly found a quantum-enhanced model that improved trade-fill predictions by 34% over classical methods.

Finally, AI can open new markets and lower costs. According to the IMF, AI tools are reducing barriers to entry and making it feasible for smaller firms or even individuals to analyse less-liquid markets like emerging debt or certain commodities. By automating research, coding, and data gathering, generative AI might lower the expertise needed to trade exotic assets.

In retail finance, AI-powered robo-advisors have democratised wealth management. One report notes that about half of retail investors say they would use ChatGPT or similar AI to choose or rebalance investments.

This suggests AI is making advanced analysis available to “anyone,” not just Wall Street. Overall, proponents argue these gains, faster reactions to news, more thorough analysis, and automation, should make markets more efficient and investors more informed.

Herding, black boxes and volatility

AI in finance may sound like an interesting and exciting concept, but it is not risk-free. A key concern is model correlation or “monoculture.” When many firms use similar data and algorithms, their trades tend to move together. Regulators and economists warn that this can amplify swings.

For example, if numerous deep-learning models all see a similar signal, they might simultaneously sell stocks, creating a cascade. The Bank of England and the SEC have warned that advanced AI’s “hyper-dimensionality” and shared data sources could lead to just a few dominant models or data providers. In practical terms, a “monoculture” of strategies can increase market correlations and herding. In stressed markets, this may cause liquidity to evaporate suddenly.

A recent IMF analysis noted that many algorithmic funds include safety mechanisms that can all activate at once, causing feedback loops. The 2010 “Flash Crash” is a cautionary example of an automated sell order in one market leading to a chain reaction, briefly knocking 1,000 points off the Dow within minutes.

Though that crash predated today’s AI, it illustrates the danger of automated systems acting in unison. Experts now worry AI-driven trading could produce even faster and larger moves.

Closely related is model opacity and explainability. Modern AI models are often “black boxes” that even their designers cannot fully explain how a specific trading decision was reached. This poses problems for oversight. If an AI fund suddenly accumulates a large position in an obscure asset, regulators might not understand why.

The IMF notes that market participants insist on human oversight and explainable strategies, avoiding purely “black box” approaches. Likewise, a recent Sidley (law firm) report warns that deep-learning and reinforcement-learning systems can have “emergent behaviour” that current market rules aren’t built to catch.

For example, if an AI learnt to detect fraud or manipulate prices in some non-obvious way, standard surveillance systems might miss it. The opacity also raises ethical concerns. How do we verify that AI decisions are fair and unbiased? Finance is littered with historical biases, so an AI trained on past records might perpetuate discrimination. Wharton researchers point out that “bias in AI models is particularly pertinent” in finance, especially lending and insurance.

There are also privacy and manipulation issues. Bad actors can use AI to tailor scams or spread disinformation. SEC Chair Gary Gensler warns that AI-driven narrowcasting can facilitate fraud by zeroing in on individuals’ vulnerabilities. Indeed, regulators have already flagged concerns about AI-generated “deep fakes” of company announcements or rumours that could jolt markets.

Finally, there is the risk of systemic volatility. Many worry that AI might make crises worse by speeding up decision-making. In turbulence, when computers pile into or out of trades in milliseconds, prices can swing violently.

The Sidley report cites the IMF in noting that many AI strategies include circuit-breaker logic that all trigger together under unprecedented moves, risking a sudden freeze of liquidity. In other words, while AI may “damp down” routine volatility by making markets more efficient, it might also set the stage for faster, sharper shocks. Small errors or adversarial attacks on widely used models could propagate quickly across markets. There’s also a concentration risk, and just a few tech firms provide the most advanced AI services and cloud infrastructure, so outages or cyberattacks could disrupt financial systems more broadly.

Governance meets technology

Awareness of these issues is growing. Governments and regulators worldwide are moving to govern AI in finance. In the EU, for example, the new AI Act will classify many financial AI systems as “high-risk” and impose strict obligations.

Practices like AI-based credit scoring or risk pricing will have to meet transparency, data quality, and audit requirements. The stated goal is “consistency and equal treatment in the financial sector.”

Financial institutions are also starting to set their own AI governance. Many banks now require human sign-off on automated strategies. Investment funds maintain “model risk management” teams to test how strategies behave under stress. After the GameStop episode, social platforms began cracking down on stock-promo groups. And financial regulators update rules in light of faster trading speeds.

Still, experts say more will be needed. For example, regulators worry about a lack of transparency when nonbanks use cutting-edge AI outside full supervision. There are calls for international coordination, like the Financial Stability Board surveying AI preparedness in different countries.

Another trend on the horizon is quantum computing. While today’s AI uses classical computers, quantum machines promise even more power. If scalable quantum computers arrive, they could revolutionise optimisation and simulation problems in finance.

Banks are already experimenting. In 2025, HSBC announced a pilot with IBM showing that a quantum algorithm could predict bond trade outcomes 34% better than classical methods.

UBS, Citigroup, and others are researching quantum for portfolio optimisation and risk analysis, and analysts estimate the “quantum technology” market could reach $100 billion by 2030.

In plain terms, quantum computing could solve certain portfolio or pricing problems much faster than today’s fastest supercomputers. However, practical quantum advantage remains in early stages, and much of that promise is years away. Even so, finance leaders like HSBC’s quantum head call this a “new frontier” in computing for markets.

Tale of two traders

The AI wave affects big institutions and small investors differently. Large financial firms such as banks, hedge funds, and trading firms have the resources to develop sophisticated AI. They run vast data centres, hire machine-learning experts, and deploy cutting-edge models.

These institutional players have led the AI adoption for over a decade as they’ve used automated algorithms in HFT and complex derivatives trading. They also invest in AI for risk management and compliance. Because of their scale, they have an edge in computing speed and data access.

Retail investors have lagged but are catching up. The same chatbots and analysis tools that institutions use are now available to individuals in a lighter form. As one industry report noted, about half of retail investors say they would use AI tools to pick or adjust investments, and around 13% already do. User-friendly platforms now offer AI-driven advice and portfolio screening.

For example, retail-friendly robo-advisors automate investing for individuals with modest accounts. Even individual day traders are experimenting with off-the-shelf AI bots or sentiment-tracker apps. Indeed, the widespread curiosity about ChatGPT and AI has “democratised” access to analysis once reserved for big banks. One former UBS analyst remarked that using ChatGPT for stock research was akin to “replicating many workflows” of an expensive Bloomberg terminal.

Balancing innovation and stability

AI’s role in finance is growing fast. As the IMF puts it, generative AI is the “latest stop on a journey” where technology incrementally improves markets. Its benefits in faster processing, new insights from data, and lower costs have already transformed many aspects of trading and investment.

But the journey is not without bumps. Our analysis shows that there are real risks that correlate with AI models, as they could unintentionally synchronise market behaviour, create opaque algorithms, trigger flash crashes, and mislead investors.

Addressing these issues will require vigilance and innovation on their own part. Regulators are awakening to the challenge, calling for AI governance frameworks and updating rules for our faster, more complex markets.

Financial firms are instituting controls on things like explainability requirements and kill switches for trading bots. Meanwhile, new technologies on the horizon, like quantum computing, promise even more powerful tools.

In the end, the AI transformation in finance mirrors other revolutions by creating opportunities and pitfalls. The central question will be how these systems are deployed. Used wisely, they can make markets more efficient and accessible to more people. Used recklessly, they could amplify our worst crashes or widen inequalities.

For investors and policymakers alike, the task is to harness AI’s ingenuity while keeping our collective financial system resilient. Industry leaders must ensure AI markets remain “transparent, fair, and inclusive,” even as the algorithms get ever smarter.

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Mohammed Al-Qarni, an academic and consultant on AI for business, said, “This is a quantum jump in potential productivity, yet history warns us that success hinges entirely on the political and organisational will to design frameworks capable of seizing, not squandering, this opportunity.”

The chilling reality is that this transition is arguably more disruptive than the Software-as-a-Service revolution that preceded it. But what happens when corporations lack the courage to lead? The historical record of digital transformation is littered with the corpses of once-dominant giants, and Kodak serves as the perpetual, damning example.

Despite pioneering digital technology, the company’s strategic reluctance to scale its own innovation, driven by a fear of cannibalising its immensely profitable film business, proved a fatal weakness. Such a protectionist approach and internal cultural resistance led to a catastrophic delay, allowing competitors like Canon and Sony, which had adopted flexible and responsive digital strategies, to capture significant market share.

Survival in a disruptive era demands a willingness to disrupt your own established, profitable business models actively. The transformation required is a radical and holistic overhaul.

Today, the same pattern of institutional failure is visible. While 88% of organisations report utilising AI in at least one business function, showing a clear awareness of the threat, the majority remain dangerously vulnerable. Nearly two-thirds of them confess they have yet to begin scaling the technology across the enterprise, remaining confined to the experimentation or piloting phase.

Such a gap between acknowledgement and action is the single most dangerous vulnerability, demonstrating a failure to establish the strategic and organisational frameworks necessary to manage the disruption. For those who do manage to scale, the financial verdict is already in.

Organisations report an average return on investment of 1.7x on AI and generative AI investments, alongside cost reductions ranging from 26% to 31% across core functions like supply chain and finance. Executives cite tangible improvements, reporting 10% to 20% gains in accuracy, productivity, and time-to-market.

The barriers preventing such scaled adoption are not rooted in technical limitations but in human frailty and strategic myopia. The most frequently cited obstacle is the inability to define clear use cases or establish demonstrable business value.

Such a pattern reflects a failure of imagination, rooted in trying to apply AI to traditional, inefficient problems rather than focusing on “AI-native problems,” which are challenges that become uniquely tractable or profitable only through AI-first thinking.

Compounding this strategic deficit is the internal “human firewall,” and nearly half of CEOs report that employees are resistant or even hostile to AI adoption, often driven by profound anxiety over job security. To overcome this resistance, leadership must invest in upskilling, rewire organisational culture, and establish governance that instils confidence and trust.

Furthermore, even where the will exists, the technical foundation often fails. Businesses consistently identify data quality, availability, and the management of silos as the paramount technical barriers to implementation.

“Without clean, well-organised, and accessible data, advanced models underperform, undermining the entire investment. Agentic AI systems, which require continuous refinement, are particularly dependent on real-time data pipelines and robust governance capabilities often incompatible with rigid, older legacy infrastructure,” Al-Qarni stated.

Strategic autonomy

In an era of accelerating technological competition, the AI transition is fundamentally a geopolitical contest, where national strategy is the new competitive differentiator. The global economic benefits are colossal. There is $19.9 trillion projected to be injected into the global economy through 2030, a figure accounting for 3.5% of global GDP that year.

That injection is projected to create a permanent increase in economic activity, with compounded GDP levels potentially 1.5% higher by 2035. But here is the critical economic context: global growth is projected to decelerate, slowing from 3.3% in 2024 to 3.2% in 2025, while major development finance providers are cutting aid and adopting a markedly more transactional, geopolitical approach to investment.

The United States, the United Kingdom, France, and Germany have all simultaneously cut aid for the first time in nearly thirty years. Consequently, nations can no longer rely on traditional development finance; they must secure resources and advanced infrastructure through massive, proactive investment and strategic partnerships.

Moreover, the pace of AI innovation is inextricably linked to the regulatory landscape, and flexible regulatory environments, such as that in the United States, are already projected to outperform those with more rigid frameworks, confirming that policy itself is a critical competitive lever.

Against this backdrop of global competition and shrinking fiscal space, Saudi Arabia’s comprehensive strategy, anchored in the ambitious economic diversification strategy named “Vision 2030,” provides a clear, state-led template for achieving strategic autonomy and leapfrogging competitors.

Artificial intelligence is positioned as the core technology driving economic diversification beyond oil and building a knowledge-based economy. The National Strategy for Data and AI (NSDAI), established in 2020 by the Saudi Data & AI Authority (SDAIA), sets extremely aggressive, non-negotiable targets to rank among the world’s top 15 nations in AI by 2030.

Massive financial and infrastructural commitments underpin that ambition. The Kingdom aims to attract SAR 75 billion ($20 billion) in AI investments by 2030, covering both local funding and foreign direct investment (FDI) for data and AI initiatives.

Such committed capital is necessary to secure the foundational computational power, demonstrated by strategic partnerships already accelerating the buildout, including the $10 billion, five-year collaboration between AMD and Humain to deploy up to 500 megawatts of AI infrastructure by early 2026, and a $5 billion-plus “AI Zone” partnership with Amazon Web Services (AWS) and Humain.

By aggressively attracting billions in investment from global leaders, the Kingdom is designed to mitigate dependency on transactional global aid and secure continuous access to advanced chip technology, thereby establishing critical strategic autonomy in the global AI race.

Critically, the NSDAI also prioritises policy flexibility, aiming to enact “the most welcoming legislation” for data and AI businesses and talent, including fast-track approvals and IP protections.

Furthermore, recognising that infrastructure is meaningless without talent, the strategy mandates training over 20,000 data and AI specialists to transform the national workforce. Such a comprehensive approach to investment, infrastructure, policy, and human capital serves as the blueprint for securing strategic advantage.

Human-AI value shift

To capture the true value of AI, organisations must discard incrementalism and adopt an AI-first operating model rooted in autonomy. The process begins with an “automation-first mindset,” redesigning processes to embed AI capabilities as core mission enablers, while ensuring systems are modular and interoperable to avoid vendor lock-in.

The primary goal is to streamline workflows and reduce manual effort, unlocking operational savings that can be strategically reinvested into high-value, mission-critical areas. The real disruption lies in embracing agentic AI. There are autonomous agents capable of complex decision-making and orchestrating workflows that rigid legacy systems simply cannot support.

The transition requires disciplined execution; the failure of projects like Volkswagen’s Cariad highlights the danger of strategic overreach, where an attempt is made to deliver a complete, custom technology stack without necessary sequencing and ruthless scope control.

The economic consequences of the transition are profound, resting on the fundamental restructuring of service value. As automation commoditises efficiency, the value proposition shifts dramatically. Professional services will become the most valuable service line, transitioning from transactional execution to strategy-first advisory, guiding organisations on how to architect and implement these complex, autonomous systems.

Simultaneously, managed services will ascend to focus on autonomous orchestration, while support services experience heavy automation at the core, refocusing human expertise onto the premium edges—complex diagnostics and bespoke problem-solving that require critical thinking.

For nations like Saudi Arabia, targeting the training of 20,000 specialists, this predictive shift confirms that training must prioritise advanced advisory, architectural, and integration skills, the core competencies of the high-value professional services sector, to ensure the nation captures the top tier of economic value.

Such a transformation is fundamentally about engineering a robust partnership between human judgment and machine intelligence, establishing systems that are more creative, resilient, and adaptable than either could be in isolation.

While AI excels at processing vast datasets and identifying patterns, it cannot critically apply human judgment, question assumptions, and navigate ethical complexities. Consequently, the most valuable human skills in the AI era will be critical thinking, ethical reasoning, and domain expertise, which assess, refine, and guide AI outputs.

Crucially, the strategic deployment of AI acts as a powerful mechanism for improving overall workforce performance. Studies show AI tools provided a 43% performance increase for lower-performing consultants, compared to 17% for high performers, demonstrating their power to lift the operational baseline of the entire organisation. To realise these systemic productivity gains, organisations must move beyond informal “shadow IT” use.

For chief strategy officers and chief digital officers, the path forward is clear. They must redesign for autonomy, prioritise human-AI complementarity by formalising adoption and reskilling the workforce, and govern and measure strategically.

Only by moving beyond basic ROI and aggressively tracking “Trust and Adoption Velocity” can organisations ensure they are building sustainable, resilient competitive advantage in the new economic epoch.

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