AI, disruption and financial change: is resilience built to last?

At Standard Chartered’s 2026 Lunar New Year Forum in London, one central theme framed the panel discussion: how can markets appear resilient while disruption accelerates across technology, trade and the financial system?

The session, Disruption and Resilience: Technology and the Future of the Global Economy, brought together Martin Wolf, Associate Editor and Chief Economics Commentator at the Financial Times; Prof. Keyun Ruan, Computer Scientist and Economist at Alphabet Inc; and Geoff Kot, Global Head, Corporate & Investment Banking Business Platforms at Standard Chartered.

The conversation explored whether the current wave of technological change represents durable transformation or excess exuberance, and how broader geopolitical and structural shifts are reshaping the global economic landscape.

Q: Is artificial intelligence a transformative shift, or a valuation bubble?

Martin Wolf: Transformative technologies historically take time to reshape productivity at scale. Electricity, for example, required decades before its full economic impact became evident. It would be unusual for a general-purpose technology to generate economy-wide productivity gains within only a few years. Organisational structures, skills and processes must adapt before technology delivers sustained output improvements.

Prof. Keyun Ruan: The scale of AI’s potential should not be underestimated. We are entering what could be described as an age of intelligence, where cognitive capabilities become widely accessible. However, the pace of technical advancement is far faster than society’s ability to absorb it. Investment is accelerating rapidly, yet governance frameworks, workforce adaptation and regulatory standards evolve more slowly. The question is not whether AI will reshape industries – it will – but whether institutions can adapt quickly enough to manage the transition responsibly.

Q: How sustainable is the current technology investment cycle?

Geoff Kot: From a banking and corporate perspective, AI adoption remains uneven. Many institutions are still building foundational capabilities rather than deploying fully scaled solutions. Implementation is complex, particularly within legacy systems and heavily regulated environments. While there are tangible gains in areas such as software development, client servicing and fraud detection, broader enterprise transformation takes time. The durability of the technology cycle will depend not only on innovation, but on disciplined capital allocation and measurable productivity gains. Pre-Covid, clients prioritised efficiency. Post-Covid, resilience has become the dominant theme. Today, many firms are taking a “wait and see” approach to generative AI. It is not simply a technology problem – it is a business model problem.

Q: Is disruption limited to AI, or is something broader underway?

Martin Wolf: Trade fragmentation remains a risk, but its scale should be kept in perspective. The United States is a remarkably closed economy, and its tariff policies, while inefficient, were unlikely to derail global growth. Services are not directly affected by tariffs, and as long as other countries do not follow protectionist measures, global trade can remain open. The more serious threat would come from geopolitical escalation, particularly any disruption to oil supply in the Middle East.

Geoff Kot: In finance, disruption extends beyond AI. While crypto as an asset class may be marginal, the underlying technology is significant. The financial system remains inherently inefficient, and technological change is likely to introduce new entrants and greater competition. Over time, this could reshape market structure and client interaction models.

Q: What does technological disruption mean for economic output and the workforce?

Prof. Keyun Ruan: In the short term, labour markets will experience disruption. A significant share of white-collar roles could be affected, particularly recent graduates. If left unmanaged, AI could cause large-scale disruption quickly. However, over time, new roles will emerge. Lifelong learning will become essential, as individuals adapt continuously rather than relying on one skill for an entire career.

Fundamentally, AI may shift the economy from scarcity towards greater abundance – not only economically, but socially. Metrics of success may eventually move beyond GDP, as value creation evolves towards collaboration, entrepreneurship and less material forms of wellbeing. Smaller teams could achieve far greater output, potentially expanding entrepreneurial opportunities globally, including in developing markets.

Can resilience persist amid such disruption?

The discussion suggested that disruption and resilience are not mutually exclusive. Trade has continued despite tariff tensions. Financial systems remain stable even as digital innovation accelerates. AI may prove transformative, but its impact will unfold gradually and unevenly. Markets are making large bets, institutions are still adapting, and societies are only beginning to grapple with the implications.

Resilience today reflects adaptation in progress rather than the absence of risk. The ultimate outcome will depend on how governments, businesses and institutions respond to technological and geopolitical change in the years ahead.