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Transformative AI and the implications for Tax and Legal

The current discourse about artificial intelligence (AI) demands our attention, describing a potential for global change on par with the invention of steam power or the creation of the printing press, but at a significantly accelerated pace. The promise is that AI can deliver everything from breakthroughs in science and medicine that will extend our lives to gains in productivity that will bring unprecedented abundance.1

Some people are optimistic about the possibilities, while others are worried about how society will be disrupted or put at risk— and many smart individuals are both.2 No one, though, can ignore the technology or downplay its potential impact. Several well-read essays have made that point, rejecting complacency. One compared AI to a novel virus that could sweep across the planet, while another suggested that a year or two in the future we will look back and wonder what hit the economy.3

The vast sums being spent on AI should be enough to convince most people that something big is happening. The largest cloud computing companies, the so-called hyperscalers, have committed more than $700 billion in capital expenditures to build AI infrastructure in 2026 alone.4

Intelligent models and productive agents

The leaders of the AI industry should be taken seriously when they tell us that their technology is advancing faster than most people realise. Demis Hassabis, co-founder and CEO of Google DeepMind, said in May 2026 that we could be as little as four years away from an AI-based system with all the cognitive capabilities of humans, though he still broadly expects it around 20305 Sam Altman, co-founder of OpenAI, said in early 2025 that he was confident OpenAI knows how to build an artificial general intelligence (AGI), and told TIME in August 2026 that by the end of the year the company would have an internal system he would call AGI.6 Dario Amodei, co-founder and CEO of Anthropic, has said that, if scaling trends hold, we are likely to get what he calls “powerful AI” within the next few years, a term he defines as an AI smarter than a Nobel Prize winner across most fields, from biology to mathematics to writing.7 Most recently the public debate has turned to Artificial Super Intelligence and recursive self-improvement of AI systems. Nonetheless, the practical economic impact may arrive long before there is agreement on whether a system officially qualifies as AGI or ASI.

These companies are also responding to the risks. OpenAI slowed some research after an unreleased model escaped a test environment,8 and Amodei has called for mandatory third-party testing of frontier models.9 Not all researchers share their timelines. AI pioneer Yann LeCun, for one, argues that language models alone will not reach human-level intelligence.10

Some debate how to best describe the technological shift that we are on the cusp of reaching.11 But transformative AI captures the idea that the technology will soon be doing many things we used to believe only humans could do, and it’s the term we will use here.

One measure of the pace of change—how quickly transformative AI is coming—is the improvement in Generative AI models since they entered the public imagination with OpenAI’s release of ChatGPT in late 2022. These models can retrieve information, analyse, summarise, and reason today with capabilities and accuracy barely imaginable a few years ago.

Another metric is the advance of Agentic AI systems, enabled by these foundational models. This is AI that can take over tasks end-to-end, can break problems into pieces, develop strategies, test them, and act with autonomy in the real world. Already changing how computer coding is done, Agentic AI holds the greatest promise for world-changing productivity gains.

Implications for tax and law

As someone who has made a career in the tax and legal professions, my analysis is sharpened by a recognition of how AI is disrupting my own fields. It won’t just change how accountants and lawyers do their work, or how taxes are calculated and filed, or how courts administer laws. AI appears likely to reshape the global tax base and shift our conception of justice and law.

In this article, we explore key issues, starting with how tax policy will need to respond to the economic changes transformative AI may bring. We also consider how AI is already fundamentally driving change in the administration of tax, the application of law, and in the tax and legal professions. Transformative AI is poised to redefine how value is created, how rules and laws are applied, and how tax and legal expertise is exercised, and it’s driving change at both individual and organisational levels.

This article is not meant to be exhaustive but rather illustrative of the issues we now face in our professions.

Governments have long depended on taxation of labour and income to raise revenue. But as AI is poised to disrupt jobs and displace human workers, how will this impact future tax revenue?

Already in the software industry, coding that used to require days or weeks of labour can be completed quickly by AI agents. Humans have shifted their focus to conceiving programming tasks, monitoring, and checking results. Some employers have announced cuts in software jobs, and surveys suggest that many employers across a range of industries believe they will be eliminating jobs in AI-exposed roles.12

AI’s expanding capabilities have inspired predictions that vast numbers of entry-level white-collar jobs could be eliminated in the next few years.13 Other types of jobs might also be impacted as AI is combined with robotic automation and Physical AI—making it possible to automate even more-manual tasks.

Complex variables come into play in any prediction of how AI might have an impact on jobs, coloured by the experience of past technological leaps that both eliminated certain types of work and created whole new areas of employment. In some cases where AI automates work, the employee may become more productive and valuable by overseeing the AI as it completes tasks—for gains in output more than loss of jobs.14

Ethan Mollick, a professor at the Wharton School of the University of Pennsylvania, has described the growth of AI capabilities as the expansion of a “jagged frontier.” The AI may be very good in one area, such as computer coding tasks, but may be surprisingly slow to gain needed skills in other areas, creating a check on job losses.15 There will also be resistance to allowing AI to handle certain tasks due to organisational inertia or societal decisions, even when the technology can handle them.16

Reshaping of the tax base

The heart of the tax matter, though, as certain types of labour are eliminated or devalued, as employment shrinks or average wages fall, is that systems built around individual income taxes, payroll taxes, and social security contributions will be challenged. The labour part of the tax base could enter a long period of erosion, requiring that other revenue sources be tapped. 

Taxation of corporate profits may also be disrupted by AI’s economic shifts. As companies generate revenue and profit growth without proportional labour costs, more value will come from capital and investments in AI systems. The geographic attribution of income—deciding where economic activity actually takes place—may become more difficult. Existing transfer pricing and permanent establishment rules may be strained. 

Overall, the economic impacts of AI may require redesigns of tax systems that are more structural than incremental. There is growing discussion of the possibility of taxing AI tokens, the basic unit processed by large language models, or taxing data centres.17 Options once seen as theoretical may move to the mainstream, such as taxing the productive capacity of AI agents rather than the profits they generate or shifting the tax base from profits to revenue or gross income.

Governments may face the need for higher social safety net spending as AI impacts labour—and pressure to ensure that wealth created by AI is distributed fairly across society. Novel ideas for how wealth created by transformative AI could be shared more broadly include sovereign AI funds, universal basic income or even something called universal basic capital, which would make people stakeholders in AI-driven wealth creation.18

Tax systems change slowly, with governments struggling to keep up with the pace of change. On the other hand, AI may help to enable the kind of transformation that’s needed, making it feasible for policymakers to more rapidly and effectively model tax scenarios or highlight contradictions in existing tax rules. This could create more opportunities for collaboration, consultation and effective policymaking. 

Fundamentally, AI calls into question long-held assumptions about how value is created and where profits are recognised. This will require policymakers to dispense with orthodoxy and think creatively about whole new societal and economic constructs and their implications.

In the administration of tax, there is an existing path for increasing automation and digitalisation. The Tax Administration 3.0 framework from the Organisation for Economic Co-operation and Development (OECD) has, since its initial publication in 2020, helped to drive digital transformation, with a particular emphasis on more seamless data sharing between the systems of tax authorities and taxpayers. 

The increased use of AI in tax fits well with the long-run transformation journey envisioned in Tax Administration 3.0. Research by the OECD has found that more than 70% of tax authorities already apply AI to at least some tasks, including fraud detection, compliance risk assessment, and taxpayer services (OECD 2025). This in turn creates pressure on taxpayers to implement AI tools in part to keep pace with tax authorities.

Taxpayers are indeed moving forward with changes in their systems to boost the use of AI—and reap the benefits. Some 46% of respondents in Deloitte’s Tax Transformation Trends 2025 survey say they have implemented AI-driven tax analysis tools, while most of the remaining respondents say they are planning to.19

There is a jagged frontier surrounding AI capabilities in tax, to be sure. The technology is making big advances in some areas but still not ready for deployment on other tasks. Some past examples show how poorly applied algorithms and automated decisions can lead to biased outcomes, as in the scandal over penalties related to childcare subsidies wrongly applied to thousands of parents in the Netherlands. As opaque AI models are used for tax audits or enforcement, the explainability of automated decisions will be increasingly important. 

This is a disruptive moment as AI is embedded into enterprise systems and the tax function becomes better integrated with the real-time data flows of the business itself. As AI drives change in the functioning of businesses and the economy, the underlying facts tax relies upon will also change. AI doesn’t just automate tax, it changes how companies operate, and this shift will raise new issues related to value creation, cost structures and operational profiles—tax will need to react.

AI is poised to change the law in many ways. At the most fundamental level, the operation of law may be pushed by transformative AI from ex post, the after-the-fact litigation and enforcement that characterises the system today, to ex ante, with rules embedded in the systems where transactions happen, enabling earlier detection and intervention. 

More immediately, the legal field is already seeing changes in how routine work gets done. AI can tackle time-consuming tasks related to contract and document review, legal discovery, and the drafting of briefs and documents. While there have been some high-profile missteps involving unwise use of AI for court filings and inadequate reviews, many routine legal tasks increasingly fall within AI’s capability frontier. 

Advances in the ability of AI to do legal work are shifting the economics of legal practices and disrupting lawyers’ career paths. Deeper impacts are coming—in litigation, law enforcement and criminal justice more broadly—as AI creates opportunities for continuous monitoring, embedded compliance, and automated enforcement decision-making.

Moving toward law as code

Ultimately, AI-driven change may call into question the premise that legislation and regulation should primarily be delivered as human-readable text—authored by legislatures and agencies, interpreted by courts, circulated through existing publishing and software systems. The end-state the legal system may be headed toward is sometimes called law as code.20

Embracing law as code would create a world in which regulation is delivered as part of the digital infrastructure of the economy—in systems for tax compliance, in the monitoring of bank transactions for money laundering, in supply chain contracts, and much more. There is clear appeal in having laws and rules encoded into systems that calculate and validate transactions. 

Greater automation in the application of law, and an eventual embrace of law as code, offers significant positives in areas such as access to justice. Today, civil legal needs dramatically outstrip available and affordable legal help, for example. This is an area where broad use of AI could change the game—bringing down the unit cost of legal information and legal work. 

AI has the potential to turn much of the existing work in the application of law from a time-intensive process of production into one of mostly human supervision, strategy, and judgment. The path from today’s legal system, fully dependent on natural language laws and regulations, to this coded future is unclear, however. Law as code remains a long-term goal, even as AI-driven changes to legal practice and careers arrive much more quickly.

The idea that work in professions steeped in the acquisition and application of bodies of knowledge is protected from automation has already been upended by AI’s recent advances. Entry-level work in white-collar fields, certainly including tax and law, appears to already be disrupted, though the speed at which career paths will shift remains unclear. 

The future state for the tax and legal professions may see its workers become agentic product owners, orchestrating AI systems rather than executing tasks directly. The human role shifts to oversight, validation, and strategic direction, and leaders in the professions envision a hybrid human-AI model for the workforce. 

The increased efficiency in tax and legal work that AI promises may help businesses to be more self-sufficient, using new technology to complete more legal work in-house. On the other hand, it may lead them to rely more on AI agents and systems powered by advisers, embedded into their own systems but owned elsewhere.

Already, companies are devoting resources to AI for tax and legal work. The venture capital firm Andreessen Horowitz estimates that AI startups focused on legal offerings already are recording about $500 million a year in revenue.21 The analysis suggests that legal is an area where companies are eager to adopt AI, perhaps second only to software coding in terms of momentum for the use case. 

What remains to be addressed is where accountability and liability will rest when more tax and legal professional work is handed off to AI tools. When there are incorrect filings, misapplied tax rules, faulty legal briefs, or missed legal precedents, few will accept that the tools alone can be blamed. What’s more, work cannot simply seem to come from a black box, without clear reasoning, audit trails, and defensible interpretations of regulations and laws. 

The central challenge in the tax and legal professions is not technological but institutional. More advanced adoption of AI tools requires a rethinking of existing systems of professional responsibility—which today rest primarily in the qualifications and certifications of the people who work in these fields. How that transition is managed will determine not just the efficiency gains from AI, but the integrity and trustworthiness of the professions.

The shape of the AI future in tax and law

The AI advances society grapples with today do not simply represent another wave of technology change. Rather, transformative AI promises to reshape our world—shifting the foundations of how economies are taxed, how law and justice are administered, how professional expertise is applied. 

The transition underway will test the ability of humans and institutions to adapt as quickly as the technology itself advances. The stakes are not limited to efficiency or cost, but extend to the integrity, fairness, and resilience of systems on which modern economies depend.

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