One of the great privileges of working in economic consulting is the opportunity to see the same issue from many different perspectives.
Over the past year, I’ve had conversations with technology companies on topics ranging from AI governance and copyright to data regulation, digital competition, and semiconductor policy. They are very different debates, involving different technologies, different stakeholders, and different policy objectives. Yet they often arrive at remarkably similar economic questions.
At their core, they are often asking the same economic questions. What conditions encourage firms to invest? What determines how quickly new technologies are adopted? How do policy choices influence productivity, competitiveness, and growth? And, ultimately, what kind of policy environment allows technology to deliver its full economic potential?
That observation sits behind a new Oxford Economics series on the economics of technology policy in Asia-Pacific. I’ll be curating contributions from economists across our business, each writing from their own area of expertise. My hope is that the series does more than explore a collection of important policy issues. It is designed to connect the economic questions running through many of these debates and, in doing so, encourage a broader conversation about the role economics plays in shaping successful technology policy.
An economic perspective
Governments necessarily develop policy one issue at a time. AI governance, copyright, competition, digital infrastructure, and cross-border data flows all have their own institutions, legislative frameworks and consultation processes.
Technology companies experience the world differently.
From an investment perspective, individual policies are rarely evaluated in isolation. Decisions about where to build capability, deploy capital, or develop new products reflect businesses’ confidence in the wider economic and policy environment in which they expect to operate. It is that environment—not any single regulation—that ultimately shapes investment decisions.
That distinction matters because many of the most important economic consequences arise not from individual policy interventions, but from the way they interact.
Economics can help us ask a complementary question. Beyond the immediate objectives of individual policies, what wider trade-offs and second-order effects emerge once those policies begin interacting? Where do they reinforce one another? Where might they create unintended frictions? And how do those interactions shape the conditions for investment, innovation, technology adoption and, ultimately, economic performance?
Different policy debates often lead us back to remarkably similar questions, and it’s important to stand back and look across them rather than considering each in isolation.
From regulation to dysregulation
Recently, I came across a term from another discipline that seemed to capture the risks implied by the current AI policy environment rather well: dysregulation.
The word comes from biology. It describes the disruption of processes that normally keep a living system functioning effectively. Individual organs may remain healthy, yet the interactions between them become less coordinated and the performance of the organism as a whole begins to deteriorate.
Most policy interventions exist for good reasons, and many pursue objectives that businesses themselves support. Most policy interventions exist for good reasons, and many pursue objectives that businesses themselves support. Problems arise when individually sensible interventions begin to pull in different directions, gradually reducing the coherence of the wider policy environment. That can make it more difficult for firms to invest, innovate, and scale new technologies.
The AI boom we are living through provides a particularly useful lens through which to think about this.
The economic impact of AI depends not only on advances in the technology itself, but on the environment in which it is developed, deployed, and adopted. Data governance, digital infrastructure, energy, copyright, skills, competition policy, industrial strategy, and cross-border digital trade all influence those conditions. None of these policy areas exists in isolation. Neither do their economic consequences.
Although this series focuses on AI, the same line of thinking extends much further. Many technology policy debates ultimately raise the same underlying economic questions, even if they begin in very different places.
That is the perspective this series has been designed to explore.
The conversation ahead
Over the coming months, economists from across Oxford Economics will examine topics including sovereign AI, copyright, digital regulation, cross-border data flows, and digital infrastructure. Each article will approach its subject from a different angle, drawing on our own, original quantitative analysis. My role is to curate those perspectives into a broader conversation about the economics of technology policy, and my hope that readers come away with a greater appreciation of the common economic thread running through debates that are too often considered in isolation.
Technology companies, governments, and other stakeholders will continue to disagree—quite legitimately—about many individual policy questions. Different policy objectives involve genuine trade-offs, and reasonable people will often reach different conclusions.
What is often common, however, is the underlying economic question. How do individual policy choices shape the wider economic conditions under which technology creates value?
That is the question this series has been designed to explore.
Because the most important question may not be whether individual technology policies are well designed. It may be whether, viewed collectively, they create the conditions in which technology can deliver its full economic potential—or whether they drift, gradually and unintentionally, towards dysregulation.
