Keynote by Mathias Cormann OECD Secretary-General India AI Impact
20 Feb 2026 15:00h - 16:00h
Keynote by Mathias Cormann OECD Secretary-General India AI Impact
Summary
The session opened at the India AI Impact Summit, where OECD Secretary-General Mathias Cormann highlighted the organization’s role in guiding global AI policy and thanked India for its leadership [1][2][3]. He emphasized that the OECD provides evidence-based analysis to promote responsible AI innovation while managing risks [4]. Cormann said AI could raise labour productivity by up to one percentage point annually across OECD and G20 economies over the next decade [9], and linked this potential to massive private investment, citing roughly three-quarters of a trillion dollars planned by major tech firms this year [10]. Emphasising the need for public policy, he argued that foundational technologies such as internet connectivity and semiconductors were shaped by earlier policy interventions [11-12].
The OECD’s current work includes mapping the AI ecosystem, tracking public compute capacity and global AI venture-capital flows, which now account for 61 % of worldwide VC investment [14-16]. Its recent report on AI agents found that half of developers intend to use them, but highlighted gaps in security, privacy and accuracy that must be addressed [19]. To monitor risks, the OECD recorded a rise in reported AI incidents from 92 to 324 per month between 2022 and 2025 and promotes a common incident-reporting framework [21-22]. Policymakers are given benchmarking tools such as the newly released OECD AI Index and an upcoming interactive toolkit that will showcase international best practices [24-25].
The organization also coordinates international cooperation through its Global Partnership on AI, recently expanding membership to 46 countries [26-28]. For the private sector, the OECD issued a due-diligence guide and is updating the Hiroshima AI Process Code of Conduct to aid small- and medium-sized enterprises [30-32]. Recognising labour impacts, Cormann estimated that 27 % of jobs are at high risk of automation and pointed out that only 23 % of adults with low literacy receive AI training, underscoring the need for flexible, targeted upskilling [35-38]. In partnership with the ILO, the OECD released an Equitable AI Transitions Playbook to help governments, industry and workers manage the shift responsibly, and the session concluded with Speaker 2 thanking the Secretary-General and introducing the next panel on data sovereignty [39][41-44].
Keypoints
Major discussion points
– AI’s transformative economic potential – The OECD estimates AI could raise labor productivity by up to one percent annually across OECD and G20 economies, driving greater efficiency, lower costs and higher living standards, while private-sector investment in AI infrastructure approaches three-quarters of a trillion dollars this year[8-10].
– OECD’s data-driven support for policymakers – The organisation tracks the global AI ecosystem, including public compute capacity and venture-capital flows (now 61 % of worldwide VC, $259 bn, with the U.S. capturing 75 % of AI deal value) and publishes analyses such as the “Artificial II landscape” report to keep governments abreast of emerging technologies[14-19].
– Systematic monitoring of AI-related risks – By collecting incident data (rising from 92 to 324 reports per month between 2022-2025) and offering a common reporting framework, the OECD helps countries classify and manage safety, privacy and accuracy hazards[20-23].
– Workforce impacts and equitable transition – About 27 % of jobs are in occupations at high automation risk; participation in AI training is markedly lower for adults with low literacy (23 % vs 61 %). The OECD, together with the ILO, has produced an “Equitable AI Transitions Playbook” to guide up-skilling, reskilling and policy measures for a fair AI-driven shift[34-40].
– Practical tools and international coordination – Recent releases include the OECD AI Index, an interactive toolkit of global best practices, the integrated global partnership on AI, and guidance for companies (e.g., the AI Due Diligence Guidance and the updated Hiroshima AI Process Code of Conduct) to foster responsible adoption across governments, industry and civil society[24-28][30-33].
Overall purpose / goal
The speech aims to showcase how the OECD leverages evidence-based analysis and international cooperation to help governments, businesses and workers harness AI’s benefits while mitigating its risks. By presenting data, risk-monitoring mechanisms, policy tools and collaborative frameworks, the OECD seeks to steer a responsible, inclusive AI transition worldwide.
Tone of the discussion
The tone is largely optimistic and forward-looking, emphasizing the “great opportunities” and “transformative” impact of AI. It remains evidence-driven and collaborative, highlighting the OECD’s role as a facilitator. Mid-speech the tone shifts to a more cautionary note when addressing risks such as incident spikes and job displacement, but it stays constructive, stressing the need for coordinated policy, training and equitable measures rather than expressing alarm. Overall, the discourse moves from confidence in AI’s promise to a balanced call for responsible stewardship.
Speakers
– Mathias Cormann – Secretary General, OECD; expertise in international policy and AI governance. [S4]
– Speaker 2 – Moderator/Host of the session; specific expertise not mentioned. [S1]
Additional speakers:
– Sunil Gupta – Managing Director and Chief Executive Officer, Yota Data Services; expertise in data services and AI.
– Nisubo Ongama – Chief Operating Officer, Kala; expertise in operations within the AI/technology sector.
– Kala Sonia Vaigando – Founders Associate, Kala Limited; expertise in startup development and AI initiatives.
– Seema Ambasta – Chief Executive Officer, L & T, Vioma; expertise in AI technology leadership.
– Orgo Sengupta – Founder and Research Director, WIDI Center for Legal Policy; expertise in legal policy and AI governance.
The India AI Impact Summit opened with OECD Secretary-General Mathias Cormann thanking India for its leadership in convening the global AI community after successful meetings in the United Kingdom, Korea and France, and reaffirming the OECD’s commitment to support policymakers, businesses and citizens worldwide with evidence-based analysis and guidance on responsible AI innovation [1-4].
Cormann then quantified AI’s macro-economic promise, noting that the OECD estimates a strong level of adoption could lift labour productivity by up to one percent per year across OECD and G20 economies over the next decade. He linked this potential to the unprecedented scale of private-sector investment, pointing out that almost three-quarters of a trillion dollars in AI infrastructure is slated to be spent by major technology firms this year alone [8-10]. He argued that such rapid technological change cannot be left to market forces alone; effective public policy is essential to capture the benefits and manage the risks, just as earlier policy interventions underpinned the development of the internet, semiconductors and global supply chains [11-13].
To help governments navigate the fast-evolving AI landscape, the OECD provides a data-driven service that maps the AI ecosystem. It tracks the global distribution of public AI compute capacity to inform industrial-strategy decisions and to assess supply-chain security, and it monitors worldwide AI venture-capital flows – now accounting for 61 % of total VC investment ($259 bn) and dominated by the United States, which captures 75 % of AI deal value [14-18]. These analyses are refreshed regularly; for example, the recent “Artificial Intelligence landscape” report found that half of surveyed developers intend to use AI agents, while highlighting the need for progress on security, privacy and accuracy before broader adoption can occur [19].
Risk monitoring is another pillar of the OECD’s work. Between 2022 and 2025 the number of AI-related incidents reported in the media rose sharply from an average of 92 to 324 per month, prompting the organisation to develop a common framework for AI-incident reporting that promotes global consistency and interoperability [20-23]. This systematic data collection enables policymakers to classify emerging hazards and to design targeted mitigation measures.
Building on the incident data, the OECD has released practical tools for policy benchmarking. The OECD AI Index provides an evidence-based instrument for assessing national progress against the OECD Recommendation on AI; later this year an interactive toolkit will launch, offering a curated repository of international best practices for peer learning [24-25].
International coordination is pursued through the Integrated Global Partnership on AI (G-PI). The partnership, which convenes governments, industry and civil society, recently welcomed Malta and Saudi Arabia, expanding its membership to 46 countries across six continents and reinforcing a multilateral framework for responsible AI development, grounded in the OECD’s landmarks [26-28].
For the private sector, the OECD supports responsible adoption via the Hiroshima AI Process Code of Conduct, originally launched at the OECD AI Action Summit in Paris last year and now being updated to accommodate small and medium-sized enterprises. In addition, the organisation issued a due-diligence guidance for responsible AI, helping companies navigate an increasingly complex landscape of regulations, voluntary standards and stakeholder expectations [30-33].
The OECD also provides recommendations for governments, business, labour and other stakeholders to ensure inclusive participation in AI [29].
Cormann addressed the labour-market implications of rapid AI diffusion. He estimated that roughly 27 % of current employment is in occupations at the highest risk of automation, and highlighted a stark disparity in AI-training participation: only 23 % of adults with low literacy engage in relevant training compared with 61 % of those with higher literacy. He argued that upskilling must become more flexible, modular and tailored to individual circumstances to ensure inclusive access [34-38].
In partnership with the International Labour Organisation, the OECD produced the “Equitable AI Transitions Playbook”, which offers concrete policy examples for updating skills frameworks and for up-skilling and reskilling workers to harness AI’s benefits while mitigating displacement and other social risks [39-40].
The session concluded with Speaker 2 thanking the Secretary-General, expressing appreciation for the remarks, and introducing the next panel on data sovereignty, moderated by Mr Orgo Sengupta and featuring Mr Sunil Gupta (Yota Data Services), Nisubo Ongama (Kala Limited), Ms Seema Ambasta (Vioma), among others [41-47].
Overall, the address underscored a balanced narrative: AI promises substantial productivity gains and massive investment flows, yet it also brings rising safety incidents and uneven workforce impacts. The OECD positions itself as a facilitator of evidence-based policy, offering tools such as the AI Index, incident-monitoring framework and the Equitable AI Transitions Playbook, and championing international cooperation through the G-PI Council. Unresolved challenges include improving AI-training uptake among low-literacy adults, curbing the surge in AI-related incidents, strengthening compute-capacity strategies for supply-chain security, and ensuring that new OECD tools are effectively adopted by member states. These issues set the agenda for forthcoming discussions, including the data-sovereignty panel that follows [41-47].
India AI Impact Summit. And thank you to India for your leadership in bringing together the global AI community following the successful summits in the United Kingdom, Korea, and France. The OECD is proud to work with you and support policymakers, people, and businesses all around the world in harnessing the benefits of AI. And we do so with our unique data, evidence -based analysis, and policy guidance, aiming to promote responsible innovation and adoption while managing the potential risks along the way. In yesterday’s discussions, we heard about the wide -reaching potential impacts of AI development on our economies and societies. And of course, they continue to evolve as adoption accelerates and new applications are introduced. But one thing is clear.
These impacts are already a transforming and will become more transformative going forward. At the OECD, we estimate that with a strong level of adoption, AI could boost labor productivity by up to one percentage point every year across OECD and G20 countries over the next decade. Greater efficiency, lower costs, higher living standards, and the opportunities are also reflected in the scale of investment in AI infrastructure with almost three quarters of a trillion dollars in investment planned by big tech companies this year alone. Amid the rapid technological change and the massive investment flows, effective public policy is essential to allow AI to reach its full potential. Indeed, the foundational technologies that made this technological revolution possible were very much shaped and supported by public policy, from internet connectivity to semiconductor, supply chains, and everything in between.
Today, the OECD helps policymakers develop pro -innovation, pro -adoption, and pro -safety AI policies, drawing on the lessons of these previous interventions, sharing experiences at the cutting edge of AI policy, and identifying policy best practice. First, the OECD helps policymakers understand how AI technologies and business models are evolving and who the key players are in the AI ecosystem. We are tracking the global distribution of public AI compute capacity to help countries design their industrial strategies and assess opportunities to enhance AI supply chain security. We are also tracking global AI investment, with our analysis released earlier this week showing that 61 % of all venture capital investment worldwide, or $259 billion US, now goes to AI firms, which is up from just 30 % three years ago.
We are tracking the global distribution of public AI compute capacity to help countries Firms in the United States attract the largest share of venture capital by a wide margin, comprising 75 % of global I .I. venture capital deal value. Our analysis is also helping policymakers keep up with the latest technological developments. Our new report on the Argentic I .I. landscape, published last week, highlights that half of developers in recent surveys plan to use I .I. agents in their work, while identifying the need for progress on security, privacy and accuracy of I .I. agents to support further adoption. Second, we help policymakers track and classify I .I.-related risks. Our data on I .I. incidents shows that between 2022 and 2025, in just three years, the number of I .I.
incidents and hazards reported by the media increased dramatically, from 92 to 324 per month on average. The OECD common framework for reporting IA incidents helps promote global consistency and interoperability in IA incident reporting. And thirdly, we help policymakers benchmark their IA policies relative to their peers and international standards. Just yesterday, we released the OECD IA Index, which provides policymakers with an evidence -based tool to assess their progress in implementing the OECD recommendation on IA. We will also launch an interactive toolkit this year, which will feature a repository of good practices from around the world to support evidence -based peer learning. Fourth, we help governments coordinate their efforts internationally. Our integrated global partnership on IA was designed to promote the responsible development and use of artificial intelligence grounded in the OECD’s landmarks.
Thank you. G -PI, the G -PI Council, which we meet later this morning, to officially welcome our two newest members, Malta and Saudi Arabia, bringing G -PI’s membership to 46 countries across six continents. Beyond governments, we also provide analysis and recommendations to support II adoption of companies. The reporting framework for the Hiroshima II Process Code of Conduct launched at the OECD II Action Summit in Paris last year promotes transparency and accountability for responsible II innovation. We’re now updating that framework to support adoption by small and medium -sized enterprises. And yesterday, we published the OECD due diligence guidance for responsible II, which supports companies around the world in navigating a growing landscape of rules, regulations, and voluntary frameworks.
And we support people by providing recommendations for governments, business, labor, and other stakeholders to work together and to ensure everyone has the best possible opportunity to participate in and benefit from AI technologies. While AI adoption offers many exciting opportunities, it also carries the risk of job displacement for some. We estimate that taking the effects of AI into account, about 27 % of employment is in occupations that are at the highest risk of automation. It will be particularly important to ensure access to training opportunities for those who need the most. And on that front, our analysis shows that among adults with low literacy skills, only 23 % participate in relevant AI training, compared with 61 % of adults with higher literacy skills.
To improve participation in AI training among adults, learning needs to be more flexible, modular, and targeted to individual circumstances and job experiences. For this summit, together with the International Labour Organization, we have developed the Equitable AI. AI Transitions Playbook. which provides examples of policies to update skills frameworks as well as initiatives to upskill and reskill workers for an equitable II transition in closing to fully harness the enormous benefit and benefits and opportunities flowing from II while mitigating and managing some of the associated risks and disruptions we need to ensure governments industry labor and experts work together to support responsible adoption the OECD will continue to support this cooperation guided by our II principles so that II
Thank you so much, Secretary General of OECD. These remarks, we’re very grateful for your remarks. For the next panel on data sovereignty, we have Mr. Sunil Gupta, Managing Director and Chief Executive Officer, Yota Data Services. We have Nisubo Ongama, COO, Kala Sonia Vaigando, Founders Associate, Kala Limited. We have Ms. Seema Ambasta, Chief Executive Officer, L &T, Vioma. And this session is being moderated by Mr. Orgo Sengupta, Founder and Research Director, WIDI Center for Legal Policy. May I request all the dignitaries to come up on stage, please.
“Mathias Cormann thanked India for its leadership in bringing together the global AI community after successful summits in the United Kingdom, Korea and France, and reaffirmed OECD’s commitment to support policymakers, businesses and citizens worldwide with evidence‑based analysis and guidance on responsible AI innovation.”
The keynote transcript records Cormann’s opening remarks thanking India and referencing the UK, Korea and France summits, and stating the OECD’s pride in supporting policy, confirming the report’s description.
“Almost three‑quarters of a trillion dollars in AI infrastructure is slated to be spent by major technology firms this year.”
Panel discussion notes indicate that “we’re spending a trillion dollars this year” on AI infrastructure, suggesting the figure is $1 trillion rather than $0.75 trillion as reported.
“Rapid technological change cannot be left to market forces alone; effective public policy is essential to capture benefits and manage risks, similar to earlier interventions for the internet, semiconductors and supply chains.”
Other OECD remarks emphasize that private‑sector investment is necessary because infrastructure needs exceed government capacity, underscoring the need for public policy alongside market activity.
“OECD monitors worldwide AI venture‑capital flows, now accounting for 61 % of total VC investment ($259 bn) and dominated by the United States, which captures 75 % of AI deal value.”
Analyses of AI compute capacity note the United States’ significant advantage and leading investment in data‑centre construction, providing context for US dominance in AI VC flows, though exact percentages are not specified in the source.
“OECD developed a common framework for AI‑incident reporting to promote global consistency and interoperability, in response to a rise in AI‑related media incidents from 92 to 324 per month between 2022‑2025.”
OECD discussions confirm the creation of a common AI‑incident reporting framework and a focus on interoperability, but the source does not contain the specific incident‑frequency statistics cited in the report.
The two speakers show clear alignment on the importance of AI’s economic impact, the necessity of robust public‑policy frameworks, and the value of OECD‑led international cooperation. The consensus is limited to these high‑level acknowledgements, as Speaker 2 does not introduce new substantive arguments.
Moderate consensus – agreement on overarching themes (AI transformation, policy need, and multilateral coordination) but limited depth due to the brevity of Speaker 2’s remarks. This suggests a shared baseline for future detailed discussions on AI governance and investment.
The transcript shows virtually no substantive disagreement. Mathias Cormann presents a series of data‑driven arguments about AI’s economic impact, investment scale, risk monitoring, and workforce implications. Speaker 2 merely thanks the speaker and introduces the next panel, offering no contrasting viewpoint.
Minimal – the interaction is largely complementary, indicating strong alignment on the importance of AI policy and cooperation. This suggests that, for the topics covered, consensus exists among the participants, facilitating coordinated action rather than contentious debate.
The discussion was driven by a series of data‑rich statements from Mathias Cormann that moved the conversation through distinct phases: first, a quantification of AI’s economic promise; second, an illustration of the rapid surge in private investment; third, a stark presentation of rising AI‑related incidents; fourth, an emphasis on the unequal impact on workers and the need for inclusive upskilling; and finally, the unveiling of concrete OECD tools (AI Index, compute‑capacity tracking, playbooks) to translate insight into policy action. Each pivot introduced new dimensions—risk, equity, infrastructure, and governance—that deepened the dialogue and reframed the audience’s perspective from celebrating AI’s potential to confronting its systemic challenges and collaborative solutions.
Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.
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