Context

KPMG International hosted an online roundtable in February 2026 as part of the Global Responsible Tax Program. Participants from business, academia, policy and civil society discussed how tax systems might respond to the growing impact of artificial intelligence, robotics and automation on the economy and labor market and what role tax can and should play in meeting social and business goals.

Despite growing attention, there remains little consensus among economists, policymakers or businesses on how AI and automation will affect economies over time. Some expect significant labor displacement; others anticipate productivity gains that complement human labor and generate new forms of work. The scale, timing and distribution of these impacts remain uncertain. Against this backdrop, what role could — or should — tax policy play? Should tax seek to influence the pace of transition towards more machine-intensive economies, or remain largely neutral? How should trade-offs between innovation, competitiveness and fairness be approached? And to what extent should tax policy differentiate between sectors, regions or demographic groups experiencing different impacts because of AI?

The conversation was held under the Chatham House Rule and included perspectives from multiple regions and sectors. The write-up below summarizes the personal views expressed and does not necessarily represent the position of any particular organization, including KPMG International Limited or any KPMG member firm.

Executive summary

  • Labor taxation may face the greatest long-term pressure: In many advanced economies, payroll taxes and personal income taxes form a significant share of public revenue, raising questions about fiscal sustainability if labor income declines relative to capital. Demographic change may compound this pressure, as aging populations reduce the share of workers relative to retirees.
  • AI may intensify existing international tax challenges rather than create entirely new ones: Issues around profit allocation, value creation and cross-border taxation are already central to the digital economy debate.
  • Direct “robot taxes” attracted significant skepticism: Participants questioned whether robots or AI systems could meaningfully be defined as taxable entities in complex digital production systems.
  • Competitiveness considerations constrain national policy choices: Unilateral taxes on automation risk discouraging investment or accelerating the relocation of high-value economic activity. Capital and intellectual property linked to AI are often highly mobile and therefore susceptible to national rather than global agreements.
  • Adapting existing tax frameworks may prove more practical than creating new ones: Several participants emphasized strengthening corporate, consumption and property tax systems rather than designing entirely new forms of taxation around AI.
  • AI could strengthen tax administration itself: Machine learning and advanced analytics may help tax authorities reduce compliance gaps and improve enforcement efficiency if adopted efficiently and effectively.
  • The debate extends beyond taxation: Education, workforce retraining, industrial strategy and social policy were seen as equally important as tax in managing technological transitions.

A future without consensus

Deep uncertainty about AI’s long-term economic effects complicates the narrative.

A central theme of the discussion was the degree of uncertainty surrounding the economic impact of AI and robotics. While public debate often assumes widespread job displacement, participants noted that empirical evidence remains limited and contested. Some companies have already announced workforce reductions linked to anticipated AI adoption. However, participants suggested these decisions are often based on expectations about future technological capabilities rather than current substitution of labor.

At the same time, demographic trends complicate the picture. In many developed economies the working-age population is projected to decline over the coming decades. In that context, automation may help offset labor shortages rather than displace large numbers of workers.

The shifting tax base

Potential vulnerability of labor-based tax revenues.

The discussion frequently returned to the composition of government revenues. In many advanced economies, payroll taxes and personal income taxes represent a large share of public finances.

If automation eventually reduces labor income relative to capital income, this could place pressure on these revenue streams. At the same time, consumption taxes may prove more resilient provided overall spending remains stable.

Corporate taxation presents a more complex picture. Automation could increase profitability and therefore expand the corporate tax base. However, the location of those profits (and therefore where they are taxed) remains a longstanding challenge in international taxation.

Participants observed that these issues largely mirror earlier debates about the taxation of digital businesses. AI may intensify these questions but does not fundamentally change the underlying policy challenges.

The “robot tax” dilemma

Can robots realistically be defined as taxable entities?

The idea of taxing robots directly has attracted attention in policy debates over the past decade. Some proposals suggest treating robots as if they were workers and taxing them based on an imputed wage or productivity equivalent. Others have proposed automation taxes linked to corporate metrics such as profits per employee.

However, participants expressed significant skepticism about these approaches. Modern AI systems operate across complex digital infrastructures involving multiple software layers, data inputs and human oversight. As a result, attributing value creation to a discrete “robot” is conceptually difficult.

Assigning legal or tax personality to AI systems would therefore raise significant technical and philosophical challenges. Many participants suggested that focusing on robots themselves risks overlooking the more fundamental issue: how the economic value generated through automation is ultimately distributed between labor, capital and jurisdictions.

Competitive constraints

National tax responses must consider global competition for investment and innovation.

Participants also highlighted the constraints facing governments considering new taxes on automation. If one country introduces additional taxation on AI or robotics while others do not, companies may shift investment to more favorable jurisdictions. This risk is particularly relevant for sectors where capital and intellectual property are highly mobile.

For this reason, several participants argued that governments should avoid policies that might discourage technological adoption or place domestic industries at a competitive disadvantage. Instead, some suggested that policy should focus on enabling innovation and supporting workforce adaptation to new technologies.

AI for the tax authority

Technology may help tax authorities close compliance gaps and improve enforcement.

While much of the discussion focused on how AI could affect tax systems, participants also emphasized the potential for AI to improve tax administration itself. Machine learning tools can analyze large datasets to identify patterns of non-compliance, improve risk assessment and automate routine processes within tax authorities.

Participants highlighted the scale of existing compliance gaps (such as VAT shortfalls in some jurisdictions) and suggested that advanced analytics could help authorities collect revenues more effectively. In this sense, AI could strengthen the operation of existing tax systems even as it raises new policy questions.

Beyond fiscal tools: Managing technological transition

Managing technological change will require broader policy responses.

Finally, participants emphasized that taxation alone cannot address all the consequences of technological transformation. Education systems, workforce retraining programs and industrial strategy were seen as central to managing economic transitions. Governments may need to support workers moving between sectors and ensure that new technologies are adopted in ways that support broad-based economic participation.

Some participants also raised environmental considerations, including the energy and resource demands associated with large-scale AI infrastructure. Taken together, these issues suggest that debates about the taxation of AI form part of a wider conversation about how societies adapt to rapid technological change.

Conclusions

The roundtable illustrated both the promise and the uncertainty surrounding AI’s economic impact. While automation has the potential to reshape labor markets and shift the balance between labor and capital, participants generally favored adapting existing tax systems rather than introducing entirely new taxes on robots or AI systems.

For policymakers, the challenge will be maintaining tax frameworks that remain flexible, competitive and capable of capturing value in evolving economic structures, while avoiding measures that could unintentionally slow innovation.

As AI technologies continue to develop, continued dialogue between policymakers, industry, academics and civil society will be essential in shaping tax systems that remain effective, legitimate and resilient in an increasingly automated economy.

Contributors:

  • Rory Daniels, Head of Emerging Technology and Innovation, techUK
  • Raluca Enache, Head of KPMG’s EU Tax Centre, KPMG in Romania
  • Raj Gill, Group Tax Director, Grosvenor
  • Becky Holloway, Programme Director, Jericho
  • Ali Kennedy, Finance Director & Chair of Pension Board at BAE Systems and Chair, CBI Tax Committee
  • Neal Lawson, Partner, Jericho
  • Benita Mathew, Lecturer in AI and Fintech, University of Surrey
  • Dominic Mathon, Head of Tax & Treasury, RELX
  • Chris Morgan, Head of In-House Tax, KDN
  • Ser-Huang Poon, Professor of FinTech and AI, Manchester Business School
  • Tim Sarson, Partner, UK Head of Tax Policy, KPMG in the UK
  • Conrad Turley, Head of Global Tax Policy, KPMG International