{"id":1151895,"date":"2025-10-30T07:00:40","date_gmt":"2025-10-30T14:00:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2026-04-06T12:13:20","modified_gmt":"2026-04-06T19:13:20","slug":"aiei","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/aiei\/","title":{"rendered":"AI Economy Institute\u200b"},"content":{"rendered":"
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AI Economy Institute\u200b<\/h1>\n\n\n\n
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AIEI Corporate Social Responsibility<\/a><\/div>\n<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n
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About Us \u2013 Microsoft AI Economy Institute <\/h2>\n\n\n\n
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Who We Are<\/h3>\n\n\n\n

The AI Economy Institute (AIEI) is Microsoft\u2019s flagship think tank dedicated to shaping an inclusive, trustworthy AI economy. We building a network of scholars and convening that network with our subject matter experts to explore how artificial intelligence is transforming work, education, and productivity \u2013 and making this knowledge base available to policy-makers, educators, and leaders for informed-decision-making. Our north star is an economic future by design. And one we design together.<\/p>\n\n\n\n

Our Mission<\/h3>\n\n\n\n

We advance actionable research and policy guidance that helps societies, governments, and organizations adapt intentionally to AI-driven change.<\/p>\n<\/div>

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What We Do<\/h3>\n\n\n\n

Research & Insights<\/strong>
We sponsor interdisciplinary studies on AI\u2019s economic and social impact, producing peer-reviewed articles, policy playbooks, and practical frameworks.<\/p>\n\n\n\n

Collaborative Network<\/strong>
Through calls for proposals, workshops, and global partnerships, we convene diverse voices to accelerate knowledge sharing and innovation.<\/p>\n\n\n\n

Real-World Impact<\/strong>
Our work informs Microsoft\u2019s strategy and public policy engagement, shaping education, workforce development, and equitable AI adoption worldwide.<\/p>\n<\/div><\/div>\n\n\n\n

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Why It Matters<\/h3>\n\n\n\n

AI is reshaping economies faster than any prior technology. AIEI exists to ensure this transformation strengthens opportunity, trust, and shared prosperity.<\/p>\n\n\n\n

Interested in becoming an advisor, share research question ideas or have general questions – contact us (opens in new tab)<\/span><\/a>!<\/p>\n\n\n\n

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Global AI Adoption in 2025 \u2013 A Widening Digital Divide<\/h1>\n\n\n\n
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Download AI Diffusion report<\/a><\/div>\n<\/div>\n\n\n\n
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Executive Summary<\/h2>\n\n\n\n

Global adoption of artificial intelligence continued to rise in the second half of 2025, increasing by 1.2 percentage points compared to the first half of the year, with roughly one in six people worldwide now using generative AI tools, remarkable progress for a technology that only recently entered mainstream use.  <\/p>\n\n\n\n

To track this trend, we measure AI diffusion as the share of people worldwide who have used a generative AI product during the reported period. This measure is derived from aggregated and anonymized Microsoft telemetry and then adjusted to reflect differences in OS and device-market share, internet penetration, and country population. Additional details on the methodology are available in our AI Diffusion technical paper.[1] <\/p>\n\n\n\n

No single metric is perfect, and this one is no exception. Through the Microsoft AI Economy Institute, we continue to refine how we measure AI diffusion globally, including how adoption varies across countries in ways that best advance priorities such as scientific discovery and productivity gains. For this report, we rely on the strongest cross-country measure available today, and we expect to complement it over time with additional indicators as they emerge and mature. <\/p>\n\n\n\n

Despite progress in AI adoption, the data shows a widening divide: adoption in the Global North grew nearly twice as fast as in the Global South. As a result, 24.7% of the working age population in the Global North is now using these tools, compared to only 14.1% in the Global South.  <\/p>\n\n\n\n

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Countries that have invested early in digital infrastructure, AI skilling, and government adoption, such as the United Arab Emirates, Singapore, Norway, Ireland, France, and Spain, continue to lead. The UAE extended its lead as the #1 ranked country, with 64.0% of the working age population using AI at the end of 2025, compared to 59.4% earlier in the year. The UAE has opened a lead of more than three percentage points over Singapore, which continues in second place with 60.9% adoption.<\/p>\n\n\n\n

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AI Diffusion by Economy H2 2025<\/strong><\/p>\n\n\n\n

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The second half of the year in the United States shows that leadership in innovation and infrastructure, while critical, does not by themselves lead to broad AI adoption. The U.S. leads in both AI infrastructure and frontier model development, but it fell from 23rd to 24th place in AI usage among the working age population, with a 28.3% usage rate. It lags far behind smaller, more highly digitized and AI-focused economies. <\/p>\n\n\n\n

South Korea stands out as the clearest end-of-year success story. It surged seven spots in the global rankings, climbing from 25th to 18th, driven by government policies, improved frontier model capabilities in the Korean language, and consumer-facing features that resonated with the population. Generative AI is now used in schools, workplaces, and public services, and South Korea has become one of ChatGPT\u2019s fastest-growing markets, leading OpenAI to open an office in Seoul.[2]   <\/p>\n\n\n\n

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A parallel development reshaping the global landscape in 2025 was the rapid rise of DeepSeek, an open-source AI platform that has gained significant traction in markets long underserved by traditional providers. By releasing its model under an open-source MIT license and offering a completely free chatbot, DeepSeek removed both financial and technical barriers that limit access to advanced AI. Its strongest adoption, not surprisingly, has emerged across China, Russia, Iran, Cuba, and Belarus. But perhaps even more notable is DeepSeek’s surging popularity across Africa, where it is aided by strategic promotion and partnerships with firms such as Huawei.[3] <\/p>\n\n\n\n

This rapid evolution underscores an increasingly important dimension of AI competition between the United States and China, involving a race to promote adoption of their respective national models. DeepSeek\u2019s success reflects growing Chinese momentum across Africa, a trend that may continue to accelerate in 2026. DeepSeek\u2019s ascent also underscores a broader truth: the global diffusion of AI is influenced by accessibility factors, and the next wave of users may come from communities that have historically had limited access to technological progress. The challenge ahead is ensuring that innovation spreads in ways that help narrow divides rather than deepen them. <\/p>\n\n\n\n

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Changes in the second half of 2025<\/h2>\n\n\n\n

New data from the second half of 2025 shows the world is using artificial intelligence at record levels, but it also reveals a widening divide. Global adoption of generative AI tools reached 16.3% of the world\u2019s population, up from 15.1% in the first half of 2025, a meaningful gain for technologies still in their early years. Today, roughly one in six people are using AI to learn, work, or solve problems.<\/p>\n\n\n\n

Yet this progress is uneven. Adoption in the Global North grew almost twice as fast as in the Global South, widening the gap from 9.8 to 10.6 percentage points. In short, AI\u2019s benefits are expanding, but they are not expanding equally.<\/p>\n\n\n\n

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AI User Share in the Global South and Global North<\/strong><\/p>\n\n\n\n

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When looking at the economies driving the fastest gains, the imbalance becomes even clearer. Of the ten countries with the largest increases in AI adoption share, all are high-income economies. South Korea and the United Arab Emirates stand out, each posting growth rates above four percentage points, underscoring how concentrated recent momentum has been among already AI-established economies.<\/p>\n\n\n\n

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Among the top 30 countries, the overall rankings remained steady. Nations that have invested early and consistently in digital infrastructure continue to lead. The United Arab Emirates and Singapore again hold the top two positions, followed by Norway, Ireland, France, and Spain. Most other countries shifted little, reinforcing how saturated the top of the list has become.<\/p>\n\n\n\n

A few changes stand out. <\/strong>South Korea made the largest move of the half, rising seven spots from 25th<\/sup> to 18th<\/sup>, a clear signal of accelerated national investment and adoption. Belgium moved ahead of Canada, and the Netherlands passed the United Kingdom, but these were modest adjustments in an otherwise stable group. The United States maintained strong usage in absolute numbers, but dropped from 23rd<\/sup> to 24th<\/sup> place, reflecting the fact that a smaller proportion of the US population uses AI compared to several smaller highly digitized nations.<\/p>\n\n\n\n

Taken together, the data shows a world embracing AI at remarkable speed, even as the divide between leading and lagging regions grows. The challenge ahead is ensuring that this next wave of innovation benefits more people, in more places, and not fewer.<\/p>\n\n\n\n

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South Korea\u2019s AI Surge: Policy, Models, and a Viral Cultural Moment<\/h2>\n\n\n\n

South Korea stands out in H2 2025 as the only country to make a dramatic leap in global AI adoption. In just three months, it climbed seven positions, from 25th<\/sup> to 18th<\/sup>, the largest rise of any nation this half. Generative\u2011AI usage grew from ~26% to over 30% of the population, bringing total growth since October 2024 to more than 80%, far outpacing the global average (35%) and the U.S. (25%). South Korea is now the world\u2019s second\u2011largest ChatGPT subscriber market, behind only the U.S. [4] The drivers for this increase include: 1) national policies accelerating AI integration, 2) frontier model improvements for the Korean language, and 3) consumer-facing features that resonated with the population.<\/p>\n\n\n\n

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AI user base growth H1 2025 to H2 2025<\/strong><\/p>\n\n\n\n

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National Policies Accelerating AI Integration<\/h3>\n\n\n\n

From July through November 2025, South Korea moved from high-level strategic vision to concrete, institutionalized action on AI. In September, the government reconstituted its national AI coordinating body as the National AI Strategy Committee, a cross-ministerial decision-making group.[5] It also enacted the AI Basic Act, legislation that balances innovation with AI governance.[6] Together, these moves created formal mechanisms to scale AI infrastructure, regulatory coordination, and public\u2011sector deployments.<\/p>\n\n\n\n

In late 2025, the government also announced plans to expand AI-focused science high schools in regional areas and strengthen partnerships between major universities and regional institutes, widening the AI talent pipeline beyond metropolitan centers.[7] Together, these decisions between July and November 2025 establish governance, planning, and education measures that support broad-based AI adoption across institutions and the general population.<\/p>\n\n\n\n

Frontier Model Improvements for the Korean Language<\/h3>\n\n\n\n

While South Korea\u2019s public and government appetite for AI was strong, the capabilities of large language models in Korean had not kept pace. That changed in April 2025, when OpenAI released its 4o model for all users, which had greatly increased capability in the Korean language, and again with the August 2025 release of GPT-5. Model performance on the Korean SAT (CSAT) benchmark \u2013 a widely used measure of scholastic aptitude for university applicants \u2013 rose dramatically: GPT-3.5 (the best model available on the free tier at the time) scored 16, GPT-4o reached 75, and GPT-5 achieved 100.[8] This represented a shift from below adult reading proficiency to performance on par with top\u2011tier college students.<\/p>\n\n\n\n

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Percentile-equivalent comparison on college admissions exams (English vs Korean)<\/strong><\/p>\n\n\n\n

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Data source: Benchmark results compiled from [8]-[11]<\/figcaption><\/figure>\n\n\n\n
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For Korean\u2011speaking users, GPT\u20114o was the turning point, making everyday tasks- conversation, drafting, translation, and analysis- practical and reliable with large language models for the first time. ChatGPT-5 extended this improvement further, adding deeper reasoning, sharper linguistic precision, and stronger context handling. These advances unlocked reliable support for complex instructions, specialized domain queries, education, professional workflows, and small\u2011business applications. Though Korean is not a low-resource language, this rapid improvement in Korean-language performance offers an encouraging signal for countries whose languages are underrepresented in LLM training data: as models expand and deepen linguistic coverage, usage is likely to follow.<\/p>\n\n\n\n

A Viral Image-Generation Moment That Captured Public Imagination <\/h3>\n\n\n\n

A third driver of South Korea\u2019s AI surge was triggered by a cultural phenomenon in April 2025, when Ghibli\u2011style images generated with ChatGPT\u20114o went viral across Korean social platforms.[12] The feature\u2019s simplicity- no technical skills required, instantly shareable results- introduced AI to millions of first\u2011time users and triggered a spike in image\u2011generation activity.[13] Engagement data suggests many continued exploring additional AI capabilities after the trend faded, turning a viral moment into lasting adoption. Combined with national policy action and major improvements in Korean\u2011language model performance, this consumer\u2011level spark helped propel South Korea to the largest increase in AI usage worldwide, led to rapid growth in the ChatGPT market, and resulted in expanded integration of AI across public services by late 2025.<\/p>\n\n\n\n

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The UAE\u2019s Deliberate AI Strategy<\/h2>\n\n\n\n

The United Arab Emirates’ AI advantage didn’t materialize overnight. It was built deliberately and with years of foresight. In October 2017, five full years before ChatGPT captured the world’s attention, the UAE appointed the world’s first Minister of State for Artificial Intelligence, His Excellency Omar Sultan Al Olama. That same year, the UAE launched a national AI strategy covering 9 priority sectors establishing governance frameworks while many governments were still debating whether AI warranted dedicated policy attention at all.[14] This sequencing proved consequential. When the current generative AI wave arrived, UAE residents encountered a familiar technology, one their government had been deploying in public services and discussing in national conversations for half a decade. The foundation was already in place. The results show up clearly in the data. The 2025 Edelman Trust Barometer places UAE AI trust at approximately 67%. The United States, by contrast, registers just 32%.[15] Western European nations average the same. That’s a 35 percentage point gap, one of the starkest cross-national differentials in technology attitudes we can measure today.<\/p>\n\n\n\n

Regulatory pragmatism has also advanced the UAE’s global AI leadership. The UAE was forward-thinking in creating sandbox environments that enabled controlled experimentation.[16] It created special visa programs to attract AI talent.[17] It adopted principles-based guidelines that provided clear direction without creating compliance paralysis. The approach generated trust in a timeless fashion: through demonstrated outcomes, and through AI that actually works in daily transactions.<\/a><\/p>\n\n\n\n

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DeepSeek\u2019s Dramatic Rise: Open-Source AI Gains Ground in New Markets<\/h2>\n\n\n\n

One of 2025\u2019s most unexpected developments was the rise of DeepSeek, a new AI entrant that surprised the industry with a flagship model capable of competing with top U.S. systems. Its defining feature was openness: DeepSeek released its model weights under an MIT license, giving developers global access to inspect, adapt, and build on its core engine, an approach that immediately resonated with open\u2011source communities.<\/p>\n\n\n\n

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DeepSeek Market Share H2 2025<\/strong><\/p>\n\n\n\n

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DeepSeek coupled this with an entirely free\u2011to\u2011use chatbot on web and mobile. The absence of subscription fees or payment requirements lowered the barrier for millions of users, especially in price\u2011sensitive regions. Reflecting this open ethos, the company invited independent researchers in September 2025 to rigorously test the model\u2019s performance, aiming for publication in Nature, an unusually transparent move for an emerging AI player.[18]<\/p>\n\n\n\n

This combination of openness and affordability allowed DeepSeek to gain traction in markets underserved by Western AI platforms. Adoption remained low in North America and Europe, but surged in China, Russia, Iran, Cuba, Belarus, and across Africa, places where U.S. services face restrictions or where foreign tech access is limited. In Africa in particular, DeepSeek usage is estimated to be 2 to 4\u00d7 higher than in other regions. By contrast, countries where entrenched alternatives already meet local needs, such as Israel and South Korea, show minimal uptake.<\/p>\n\n\n\n

Several factors explain this pattern. DeepSeek\u2019s free service eliminated the cost barriers (requiring credit cards or paid upgrades) associated with Western models.[19] In addition, Chinese technology companies, including DeepSeek and infrastructure partners like Huawei, actively promoted and deployed the platform in African markets through partnerships, outreach, and integration with telecom services.[20] DeepSeek benefited from being open, free, and strategically distributed in regions often excluded from the first wave of AI adoption. This dynamic also highlights how open\u2011source AI can function as a geopolitical instrument, extending Chinese influence in areas where Western platforms cannot easily operate.[21]<\/p>\n\n\n\n

From a governance standpoint, DeepSeek\u2019s rise shows that global AI adoption is shaped as much by access and availability as by model quality. Users gravitate toward platforms that fit their economic, linguistic, and political context. The rapid spread of an open model also raises questions about standards and safety, as open-source systems can propagate widely with limited oversight. Still, DeepSeek has clearly lowered entry barriers for millions, suggesting that the next billion AI users may emerge not from traditional tech hubs but from the Global South, enabled by open-source innovation.<\/p>\n\n\n\n

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AI Diffusion Data Source<\/h2>\n\n\n\n
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Economy<\/strong> <\/th>H1 2025 AI Diffusion<\/strong><\/th>H2 2025 AI Diffusion<\/strong> <\/th>Change<\/strong> <\/th><\/tr><\/thead>
United Arab Emirates <\/td>59.4% <\/td>64.0% <\/td>4.5% <\/td><\/tr>
Singapore <\/td>58.6% <\/td>60.9% <\/td>2.3% <\/td><\/tr>
Norway <\/td>45.3% <\/td>46.4% <\/td>1.1% <\/td><\/tr>
Ireland <\/td>41.7% <\/td>44.6% <\/td>2.9% <\/td><\/tr>
France <\/td>40.9% <\/td>44.0% <\/td>3.1% <\/td><\/tr>
Spain <\/td>39.7% <\/td>41.8% <\/td>2.1% <\/td><\/tr>
New Zealand <\/td>37.6% <\/td>40.5% <\/td>2.9% <\/td><\/tr>
Netherlands <\/td>36.3% <\/td>38.9% <\/td>2.6% <\/td><\/tr>
United Kingdom <\/td>36.4% <\/td>38.9% <\/td>2.5% <\/td><\/tr>
Qatar <\/td>35.7% <\/td>38.3% <\/td>2.6% <\/td><\/tr>
Australia <\/td>34.5% <\/td>36.9% <\/td>2.4% <\/td><\/tr>
Israel <\/td>33.9% <\/td>36.1% <\/td>2.2% <\/td><\/tr>
Belgium <\/td>33.5% <\/td>36.0% <\/td>2.5% <\/td><\/tr>
Canada <\/td>33.5% <\/td>35.0% <\/td>1.5% <\/td><\/tr>
Switzerland <\/td>32.4% <\/td>34.8% <\/td>2.5% <\/td><\/tr>
Sweden <\/td>31.2% <\/td>33.3% <\/td>2.2% <\/td><\/tr>
Austria <\/td>29.1% <\/td>31.4% <\/td>2.2% <\/td><\/tr>
South Korea <\/td>25.9% <\/td>30.7% <\/td>4.8% <\/td><\/tr>
Hungary <\/td>27.9% <\/td>29.8% <\/td>1.9% <\/td><\/tr>
Denmark <\/td>26.6% <\/td>28.7% <\/td>2.1% <\/td><\/tr>
Germany <\/td>26.5% <\/td>28.6% <\/td>2.1% <\/td><\/tr>
Poland <\/td>26.4% <\/td>28.5% <\/td>2.1% <\/td><\/tr>
Taiwan <\/td>26.4% <\/td>28.4% <\/td>2.0% <\/td><\/tr>
United States <\/td>26.3% <\/td>28.3% <\/td>2.1% <\/td><\/tr>
Czechia <\/td>26.0% <\/td>27.8% <\/td>1.8% <\/td><\/tr>
Italy <\/td>25.8% <\/td>27.8% <\/td>2.0% <\/td><\/tr>
Bulgaria <\/td>25.4% <\/td>27.3% <\/td>1.9% <\/td><\/tr>
Finland <\/td>25.6% <\/td>27.3% <\/td>1.7% <\/td><\/tr>
Jordan <\/td>25.4% <\/td>27.0% <\/td>1.6% <\/td><\/tr>
Costa Rica <\/td>25.1% <\/td>26.5% <\/td>1.4% <\/td><\/tr>
Slovenia <\/td>24.6% <\/td>26.5% <\/td>2.0% <\/td><\/tr>
Saudi Arabia <\/td>23.7% <\/td>26.2% <\/td>2.5% <\/td><\/tr>
Lebanon <\/td>24.8% <\/td>25.7% <\/td>0.9% <\/td><\/tr>
Oman <\/td>22.6% <\/td>24.2% <\/td>1.6% <\/td><\/tr>
Portugal <\/td>22.4% <\/td>24.2% <\/td>1.8% <\/td><\/tr>
Slovakia <\/td>22.1% <\/td>23.8% <\/td>1.7% <\/td><\/tr>
Croatia <\/td>21.8% <\/td>23.7% <\/td>1.9% <\/td><\/tr>
Vietnam <\/td>21.2% <\/td>23.5% <\/td>2.3% <\/td><\/tr>
Dominican Republic <\/td>22.0% <\/td>22.7% <\/td>0.8% <\/td><\/tr>
Uruguay <\/td>20.9% <\/td>22.5% <\/td>1.6% <\/td><\/tr>
Lithuania <\/td>21.0% <\/td>22.4% <\/td>1.3% <\/td><\/tr>
Jamaica <\/td>22.2% <\/td>22.1% <\/td>-0.1% <\/td><\/tr>
Colombia <\/td>20.4% <\/td>22.0% <\/td>1.6% <\/td><\/tr>
Panama <\/td>20.3% <\/td>21.5% <\/td>1.2% <\/td><\/tr>
Serbia <\/td>19.7% <\/td>21.5% <\/td>1.8% <\/td><\/tr>
South Africa <\/td>19.3% <\/td>21.1% <\/td>1.8% <\/td><\/tr>
Chile <\/td>19.6% <\/td>20.8% <\/td>1.2% <\/td><\/tr>
Malaysia <\/td>18.3% <\/td>19.7% <\/td>1.4% <\/td><\/tr>
Argentina <\/td>17.8% <\/td>19.6% <\/td>1.8% <\/td><\/tr>
Bosnia And Herzegovina <\/td>18.2% <\/td>19.5% <\/td>1.3% <\/td><\/tr>
Kuwait <\/td>17.7% <\/td>19.1% <\/td>1.4% <\/td><\/tr>
Greece <\/td>17.7% <\/td>19.1% <\/td>1.4% <\/td><\/tr>
Japan <\/td>16.7% <\/td>19.1% <\/td>2.4% <\/td><\/tr>
Philippines <\/td>17.1% <\/td>18.3% <\/td>1.2% <\/td><\/tr>
Georgia <\/td>17.3% <\/td>18.2% <\/td>0.9% <\/td><\/tr>
Mexico <\/td>16.7% <\/td>17.8% <\/td>1.1% <\/td><\/tr>
Ecuador <\/td>17.0% <\/td>17.7% <\/td>0.8% <\/td><\/tr>
Brazil <\/td>15.6% <\/td>17.1% <\/td>1.5% <\/td><\/tr>
Moldova <\/td>16.6% <\/td>17.0% <\/td>0.4% <\/td><\/tr>
Albania <\/td>15.8% <\/td>16.5% <\/td>0.7% <\/td><\/tr>
China <\/td>15.4% <\/td>16.3% <\/td>0.9% <\/td><\/tr>
Romania <\/td>15.3% <\/td>16.2% <\/td>0.9% <\/td><\/tr>
El Salvador <\/td>14.6% <\/td>16.2% <\/td>1.6% <\/td><\/tr>
India <\/td>14.2% <\/td>15.7% <\/td>1.4% <\/td><\/tr>
Azerbaijan <\/td>14.2% <\/td>15.5% <\/td>1.3% <\/td><\/tr>
Guatemala <\/td>13.7% <\/td>14.8% <\/td>1.1% <\/td><\/tr>
Peru <\/td>13.4% <\/td>14.7% <\/td>1.2% <\/td><\/tr>
T\u00fcrkiye <\/td>13.4% <\/td>14.6% <\/td>1.2% <\/td><\/tr>
Mongolia <\/td>12.6% <\/td>14.3% <\/td>1.7% <\/td><\/tr>
Namibia <\/td>13.0% <\/td>13.8% <\/td>0.9% <\/td><\/tr>
Libya <\/td>12.7% <\/td>13.7% <\/td>1.1% <\/td><\/tr>
Kazakhstan <\/td>12.7% <\/td>13.7% <\/td>1.1% <\/td><\/tr>
Botswana <\/td>12.8% <\/td>13.7% <\/td>0.9% <\/td><\/tr>
Gabon <\/td>12.3% <\/td>13.4% <\/td>1.1% <\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div>\n\n\n\n
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Economy<\/strong><\/th>H1 2025 AI Diffusion<\/strong><\/th>H2 2025 AI Diffusion<\/strong><\/th>Change<\/strong> <\/th><\/tr><\/thead>
Egypt <\/td>12.5% <\/td>13.4% <\/td>0.9% <\/td><\/tr>
Honduras <\/td>12.4% <\/td>13.1% <\/td>0.7% <\/td><\/tr>
Nepal <\/td>12.3% <\/td>13.0% <\/td>0.8% <\/td><\/tr>
Senegal <\/td>12.4% <\/td>12.9% <\/td>0.5% <\/td><\/tr>
Indonesia <\/td>11.7% <\/td>12.7% <\/td>1.1% <\/td><\/tr>
Tunisia <\/td>12.3% <\/td>12.7% <\/td>0.4% <\/td><\/tr>
Zambia <\/td>11.7% <\/td>12.3% <\/td>0.5% <\/td><\/tr>
Algeria <\/td>11.3% <\/td>12.0% <\/td>0.8% <\/td><\/tr>
Cote D’Ivoire <\/td>10.8% <\/td>11.7% <\/td>0.8% <\/td><\/tr>
Bolivia <\/td>10.9% <\/td>11.6% <\/td>0.7% <\/td><\/tr>
Iraq <\/td>10.3% <\/td>11.2% <\/td>0.9% <\/td><\/tr>
Paraguay <\/td>10.1% <\/td>11.0% <\/td>0.9% <\/td><\/tr>
Morocco <\/td>10.5% <\/td>10.9% <\/td>0.3% <\/td><\/tr>
Gambia <\/td>10.6% <\/td>10.9% <\/td>0.2% <\/td><\/tr>
Thailand <\/td>9.1% <\/td>10.7% <\/td>1.6% <\/td><\/tr>
Nicaragua <\/td>10.0% <\/td>10.7% <\/td>0.7% <\/td><\/tr>
Iran <\/td>9.6% <\/td>10.7% <\/td>1.1% <\/td><\/tr>
Pakistan <\/td>9.7% <\/td>10.3% <\/td>0.7% <\/td><\/tr>
Angola <\/td>8.9% <\/td>9.7% <\/td>0.8% <\/td><\/tr>
Madagascar <\/td>8.9% <\/td>9.7% <\/td>0.8% <\/td><\/tr>
Malawi <\/td>8.9% <\/td>9.7% <\/td>0.8% <\/td><\/tr>
Mozambique <\/td>8.9% <\/td>9.7% <\/td>0.8% <\/td><\/tr>
Benin <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Burkina Faso <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Ghana <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Guinea <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Guinea-Bissau <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Liberia <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Mali <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Mauritania <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Niger <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Nigeria <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Sierra Leone <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Togo <\/td>8.7% <\/td>9.3% <\/td>0.6% <\/td><\/tr>
Lesotho <\/td>8.8% <\/td>9.1% <\/td>0.4% <\/td><\/tr>
Myanmar <\/td>8.4% <\/td>9.1% <\/td>0.7% <\/td><\/tr>
Ukraine <\/td>9.1% <\/td>9.0% <\/td>-0.1% <\/td><\/tr>
French Guiana <\/td>8.3% <\/td>9.0% <\/td>0.7% <\/td><\/tr>
Guyana <\/td>8.3% <\/td>9.0% <\/td>0.7% <\/td><\/tr>
Suriname <\/td>8.3% <\/td>9.0% <\/td>0.7% <\/td><\/tr>
Venezuela <\/td>8.3% <\/td>9.0% <\/td>0.7% <\/td><\/tr>
Belarus <\/td>7.6% <\/td>8.4% <\/td>0.8% <\/td><\/tr>
Kyrgyzstan <\/td>7.6% <\/td>8.2% <\/td>0.7% <\/td><\/tr>
Kenya <\/td>7.8% <\/td>8.1% <\/td>0.3% <\/td><\/tr>
Russia  <\/td>7.6% <\/td>8.0% <\/td>0.4% <\/td><\/tr>
Cameroon <\/td>7.0% <\/td>7.8% <\/td>0.7% <\/td><\/tr>
Central African Republic <\/td>7.0% <\/td>7.8% <\/td>0.7% <\/td><\/tr>
Chad <\/td>7.0% <\/td>7.8% <\/td>0.7% <\/td><\/tr>
Congo <\/td>7.0% <\/td>7.8% <\/td>0.7% <\/td><\/tr>
Congo (DRC) <\/td>7.0% <\/td>7.8% <\/td>0.7% <\/td><\/tr>
Haiti <\/td>7.1% <\/td>7.6% <\/td>0.5% <\/td><\/tr>
Zimbabwe <\/td>6.9% <\/td>7.6% <\/td>0.6% <\/td><\/tr>
Papua New Guinea <\/td>7.2% <\/td>7.3% <\/td>0.2% <\/td><\/tr>
Syria <\/td>6.7% <\/td>7.1% <\/td>0.4% <\/td><\/tr>
Bangladesh <\/td>6.5% <\/td>7.1% <\/td>0.6% <\/td><\/tr>
Burundi <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Eritrea <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Ethiopia <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Somalia <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
South Sudan <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Sudan <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Tanzania <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Uganda <\/td>6.4% <\/td>6.8% <\/td>0.4% <\/td><\/tr>
Laos <\/td>6.0% <\/td>6.7% <\/td>0.8% <\/td><\/tr>
Armenia <\/td>6.2% <\/td>6.6% <\/td>0.4% <\/td><\/tr>
Sri Lanka <\/td>6.2% <\/td>6.6% <\/td>0.4% <\/td><\/tr>
Uzbekistan <\/td>5.7% <\/td>6.3% <\/td>0.6% <\/td><\/tr>
Rwanda <\/td>6.0% <\/td>6.3% <\/td>0.2% <\/td><\/tr>
Cuba <\/td>5.7% <\/td>6.1% <\/td>0.4% <\/td><\/tr>
Afghanistan <\/td>5.1% <\/td>5.6% <\/td>0.4% <\/td><\/tr>
Tajikistan <\/td>5.1% <\/td>5.6% <\/td>0.4% <\/td><\/tr>
Turkmenistan <\/td>5.1% <\/td>5.6% <\/td>0.4% <\/td><\/tr>
Cambodia <\/td>4.6% <\/td>5.1% <\/td>0.5% <\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div>\n<\/div>\n\n\n\n
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Download AI Diffusion Report H1 2025<\/a><\/div>\n<\/div>\n\n\n\n
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References<\/h2>\n\n\n\n

[1] A. Misra, J. Wang, S. McCullers, K. White, and J. L. Ferres, \u201cMeasuring AI Diffusion: A Population-Normalized Metric for Tracking Global AI Usage,\u201d Nov. 04, 2025, arXiv<\/em>: arXiv:2511.02781. doi: 10.48550\/arXiv.2511.02781.<\/p>\n\n\n\n

[2] \u201cOpenAI Korea set to launch next month – The Korea Times.\u201d https:\/\/www.koreatimes.co.kr\/business\/companies\/20250828\/openai-korea-set-to-launch-next-month<\/p>\n\n\n\n

[3] S. Rai, L. Prinsloo, and H. Nyambura, \u201cChina\u2019s DeepSeek Is Beating Out OpenAI and Google in Africa (1).\u201d Bloomberg News. https:\/\/news.bloomberglaw.com\/artificial-intelligence\/chinas-ai-ambitions-reach-africa-with-deepseek-push<\/p>\n\n\n\n

[4] M. Joon-hyun, \u201cS. Korea is global No. 2 in paid ChatGPT users, OpenAI says. But does that mean anything?,\u201d The Korea Herald. https:\/\/www.koreaherald.com\/article\/10500190<\/p>\n\n\n\n

[5] \u201cPress Releases: Korea.net\u202f: The official website of the Republic of Korea.\u201d https:\/\/www.korea.net\/Government\/Briefing-Room\/Press-Releases\/view?articleId=8243&insttCode=A110439&type=O&utm_source=chatgpt.com \u202f <\/p>\n\n\n\n

[6] \u201cAI Basic Act of the Republic of Korea.\u201d https:\/\/aibasicact.kr\/<\/p>\n\n\n\n

[7] \u201cSouth Korea investing $1.2 billion to teach AI from elementary school to the workplace,\u201d The Straits Times. https:\/\/www.straitstimes.com\/asia\/east-asia\/south-korea-investing-1-2-billion-to-teach-ai-from-elementary-school-to-the-workplace\u202f <\/p>\n\n\n\n

[8] Marker-Inc-Korea\/Korean-SAT-LLM-Leaderboard. https:\/\/github.com\/Marker-Inc-Korea\/Korean-SAT-LLM-Leaderboard<\/p>\n\n\n\n

[9] N. Canelakes, \u201cThe latest version of ChatGPT is passing formal exams left and right.\u201d https:\/\/theamericangenius.com\/housing\/real-estate-tech\/chatgpt-passing-exams\/<\/p>\n\n\n\n

[10] \u201cChatGPT-4\u2019s SAT Score Prompts Discussion on Responsible AI Use in Education.\u201d https:\/\/collegeprep.study.com\/sat-exam\/chatgpt-sat-score-prompts-discussion-on-responsible-ai-use.html  <\/p>\n\n\n\n

[11] K. Leswing, \u201cOpenAI announces GPT-4, claims it can beat 90% of humans on the SAT,\u201d CNBC. https:\/\/www.cnbc.com\/2023\/03\/14\/openai-announces-gpt-4-says-beats-90percent-of-humans-on-sat.html<\/p>\n\n\n\n

[12] \u201c\u2018Ghibli-style\u2019 images drive ChatGPT usage surge in Korea, setting daily record.\u201d The Korea Times. https:\/\/www.koreatimes.co.kr\/lifestyle\/trends\/20250401\/ghibli-style-images-drive-chatgpt-usage-surge-in-korea-setting-daily-record<\/p>\n\n\n\n

[13] \u201cChatGPT image generation fuels user surge in S. Korea,\u201d https:\/\/www.donga.com\/en\/article\/all\/20250402\/5529166\/1<\/p>\n\n\n\n

[14] \u201cUAE Strategy for Artificial Intelligence | The Official Platform of the UAE Government.\u201d https:\/\/u.ae\/en\/about-the-uae\/strategies-initiatives-and-awards\/strategies-plans-and-visions\/government-services-and-digital-transformation\/uae-strategy-for-artificial-intelligence<\/p>\n\n\n\n

[15] \u201c2025 Edelman Trust Barometer_Insights Technology Sector_FINAL.pdf.\u201d https:\/\/www.edelman.com\/sites\/g\/files\/aatuss191\/files\/2025-02\/2025%20Edelman%20Trust%20Barometer_Insights%20Technology%20Sector_FINAL.pdf#page=5.00<\/p>\n\n\n\n

[16] \u201cRegulatory sandboxes in the UAE | The Official Platform of the UAE Government.\u201d https:\/\/u.ae\/fi\/about-the-uae\/digital-uae\/regulatory-framework\/regulatory-sandboxes-in-the-uae\u202f <\/p>\n\n\n\n

[17] \u201cGolden visa | The Official Platform of the UAE Government.\u201d https:\/\/u.ae\/pt\/information-and-services\/visa-and-emirates-id\/residence-visas\/golden-visa <\/p>\n\n\n\n

[18] \u201cA look under the hood of DeepSeek\u2019s AI models doesn\u2019t provide all the answers.\u201d  https:\/\/www.sciencenews.org\/article\/ai-model-deepseek-answers-training<\/p>\n\n\n\n

[19] \u201cDeepSeek vs ChatGPT: Which LLM is Better?\u201d https:\/\/explodingtopics.com\/blog\/deepseek-vs-chatgpt<\/p>\n\n\n\n

[20] \u201cChina\u2019s DeepSeek Is Beating Out OpenAI and Google in Africa,\u201d Bloomberg. https:\/\/www.bloomberg.com\/news\/features\/2025-10-22\/china-s-deepseek-pushes-into-africa-making-ai-accessible-to-millions<\/p>\n\n\n\n

[21] \u201cDeepSeek R1: Implications of a New AI Era for Africa,\u201d Carnegie Endowment for International Peace.  https:\/\/carnegieendowment.org\/posts\/2025\/03\/deepseek-ai-implications-africa?lang=en<\/p>\n<\/div>\n\n\n\n

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Meet the newest cohort of AIEI senior fellows <\/h3>\n\n\n\n

As AI continues to transform economies and societies, understanding how its adoption spreads is critical to shaping an inclusive future. The AI Economy Institute\u2019s second research cohort builds on this mission by focusing on Education in the AI Economy<\/em>\u2014examining how AI diffusion impacts classrooms, educators, and workforce pathways worldwide. With researchers from eight countries and leading institutions, this multidisciplinary team explores national strategies, educational innovation, and labor market transitions to ensure AI-driven change benefits all. Their work will provide actionable insights for policy, education reform, and global collaboration across academia, industry, and government.<\/p>\n\n\n\n

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Cohort 2<\/h5>\n\n\n\n
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\"Dr.<\/figure>\n\n\n\n

Andrew Stokols, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

MIT\/Singapore Management University, Singapore<\/em> <\/em><\/p>\n\n\n\n

Andrew Stokols is Assistant Professor of urban studies at Singapore Management University. Dr. Stokols research examines the geopolitics of digital infrastructure, including smart cities, data platforms, cloud computing, and data regulation in China and Southeast Asia.  <\/p>\n\n\n\n

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Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Examining National Strategies for AI Diffusion in East and Southeast Asia: Policies, Networks, and Early Adopters<\/p>\n\n\n\n

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\"Carolina<\/figure>\n\n\n\n

Carolina Calvo, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

National Center for AI (CENIA), Chile<\/em> <\/em><\/p>\n\n\n\n

Carolina Calvo is an economist with 15 years of experience in program and policy evaluation, innovation systems, and strategic trade controls. Specializing in econometric analysis and impact evaluation, she focuses on R&D, productivity, and trade, bridging applied research with evidence-based policymaking. Her work centers on promoting innovation, advancing technology transfer, and generating evidence for effective public policy. <\/p>\n\n\n\n

Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Explaining AI Diffusion in Latin America: Human Capital, Institutions, and Infrastructure <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Xin Skye Zhao, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Manchester, England<\/em> <\/em><\/em><\/p>\n\n\n\n

Xin Zhao (Skye) is a Lecturer in Generative AI for Education at the Manchester Institute of Education and a partner in UNESCO\u2019s AI competency frameworks. Dr. Zhao also serves on the UN expert panel for Generative AI. Her research focuses on ethical, inclusive uses of AI in education. <\/p>\n\n\n\n

<\/p>\n\n\n\n

Theme:<\/strong> AI and National Diffusion Differences 
Subtheme:<\/strong> Global Pathways of AI Diffusion: Skills, Governance, and Policy Strategies Across Regions <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Arun Sundararajan, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

New York University (AIEI Cohort 1 Senior Fellow<\/em>) <\/em><\/p>\n\n\n\n

Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Professor of Technology, Operations, and Statistics at NYU Stern School of Business, where he also serves as Director of the Fubon Center for Technology, Business, and Innovation. Dr. Sundararajan is widely recognized as an expert on the economics of digital goods and network effects, the regulation of AI and digital platforms, and the future of work. His award-winning book, \u201cThe Sharing Economy,\u201d has been translated into multiple languages. He co-chairs the World Economic Forum\u2019s Global Future Council on Data Frontiers. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Mapping High-Impact AI Transitions: Linking Occupations, Retraining Pathways, and Educational Institutions <\/p>\n\n\n\n

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\"Robert<\/figure>\n\n\n\n

Robert Seamans, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

New York University (AIEI Cohort 1 Senior Fellow<\/em>) <\/em><\/em><\/em><\/p>\n\n\n\n

Robert Seamans is a Professor at NYU’s Stern School of Business, Director of the Stern Center for the Future of Management, and a nonresident Senior Fellow at the Brookings Institution. His research focuses on the economic impact of AI, robotics, and advanced technologies. His work has been published in top academic journals and cited by outlets like The Atlantic, The Economist, and The New York Times. In 2015, he served as the senior economist for technology and innovation on President Obama’s Council of Economic Advisers. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Mapping High-Impact AI Transitions: Linking Occupations, Retraining Pathways, and Educational Institutions <\/p>\n\n\n\n

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\"Dr.\u202fJason<\/figure>\n\n\n\n

Jason Jabbari, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Washington University, St. Louis <\/em><\/p>\n\n\n\n

Jason Jabbari is an Assistant Professor at the Brown School at Washington University in St. Louis and leads the Center for Education Research, Practice, and Policy Partnerships (CERP3). His research focuses on improving outcomes for vulnerable populations, with a current emphasis on AI\u2019s impact in education and workforce development. He also directs the Clark-Fox Policy Institute and leads research in career education, student mental health, and neighborhood effects. Dr. Jabbari serves as a Captain in the US Army Reserves. <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> Stacking AI Skills through Education-Industry Partnerships: Case Studies and Causal Evidence on Technology Training, Non-Degree Credentials, and Apprenticeships<\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Sarah Rodriguez, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Virginia Tech Foundation<\/em><\/em><\/p>\n\n\n\n

Sarah Rodriguez is an Associate Professor of Engineering Education at Virginia Tech. Her research focuses on the engineering and computing identity development of historically marginalized populations in higher education. Dr. Rodriguez is currently involved in large-scale interdisciplinary projects on institutional environments and STEM identity, sponsored by the National Science Foundation (NSF) and the Kapor Center.  <\/p>\n\n\n\n

Theme:<\/strong> AI and Opportunities for Community, Technical and Vocational College
Subtheme:<\/strong> A Study of Community Colleges and GenAI Diffusion: Understanding Innovation, Workforce Development, & Regional Pathways <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Bashar Alhafni, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Mohamed bin Zayed University of AI (MBZUAI), UAE<\/em> <\/em><\/p>\n\n\n\n

Bashar Alhafni is an Assistant Professor of Natural Language Processing at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). His research focuses on Arabic NLP, particularly in developing human-centered language technologies. He leads the Arabic AI Modeling (Aram) Lab, working on areas like grammatical error detection, text simplification, and controlled natural language generation. Dr. Alhafni is dedicated to creating Arabic NLP applications that support education and contribute to social good. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Barriers and Opportunities for Generative AI in K-12 Arabic Education <\/p>\n\n\n\n

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\"Carolina<\/figure>\n\n\n\n

Carolina Lopez, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

World Bank<\/em><\/p>\n\n\n\n

Carolina Lopez is a Research Economist in the Poverty, Inequality, and Human Development Team at the World Bank\u2019s Development Research Group. Her research focuses on education, human capital, and behavioral economics, particularly how beliefs influence behavior and welfare. <\/p>\n\n\n\n

<\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> AI in the Classroom: Evaluating the Impact of Teacher Training on Teaching Practices and Student Outcomes  <\/p>\n\n\n\n

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\"Dr<\/figure>\n\n\n\n

Joseph Onderi Orero, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Strathmore University, Kenya<\/em> <\/em><\/p>\n\n\n\n

Joseph Onderi Orero is a Senior Researcher in AI at Strathmore University\u2019s School of Computing and Engineering Sciences. His internationally recognized research explores AI applications in education and health, and he has published extensively in these fields. Currently, Dr. Orero is exploring the use of Generative AI in game-based learning in Africa, aiming to integrate AI into education with an emphasis on ethical, human-centered design. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> AI in the Classroom: Evaluating the Impact of Teacher Training on Teaching Practices and Student Outcomes  <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Tingting Li, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Washington State University (Microsoft 50 for 50 awardee<\/em>)  <\/em><\/p>\n\n\n\n

Tingting Li\u2019s research focuses on human-AI collaboration, science assessment, and rural education policy. She leads projects on generative AI in K\u201312 classrooms, particularly in underserved schools, and co-directs CAiRE at WSU, where she collaborates with educators to design AI tools for classroom use. Dr. Li has published 37+ peer-reviewed articles and has received several prestigious fellowships. <\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> RAISE (Rural AI for Societal Equity): A Roadmap Linking Classrooms and Workforce Equity in the AI Economy<\/p>\n\n\n\n

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\"Sarayu<\/figure>\n\n\n\n

Sarayu Sundar, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Colorado Boulder<\/em> (Affiliate Fellow) <\/em><\/p>\n\n\n\n

Dr. Sarayu Sundar is a Higher Education Faculty Research Associate at the Center for Technology Workforce Innovation (formerly NCWIT) at the University of Colorado – Boulder. In this role, Dr. Sundar focuses on leveraging quantitative and qualitative data to understand trends and patterns in computing student outcomes. She also oversees the collection and analysis of longitudinal enrollment, retention, and degree completion data from member institutions.”<\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Exploring the Preparation of AI-literate, AI-skilled, and AI-ethical college students in the US    <\/p>\n\n\n\n

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\"Wendy<\/figure>\n\n\n\n

Wendy DuBow, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Colorado Boulder<\/em> (Affiliate Fellow)<\/em><\/p>\n\n\n\n

Dr. Wendy DuBow is Director of Strategies for Education Research & Evaluation at the Center for Technology Workforce Innovation (formerly NCWIT) and affiliate faculty member in Women and Gender Studies at the University of Colorado – Boulder. DuBow conducts mixed methods social science research, with a focus on systemic levers that can broaden participation in technology for historically marginalized and excluded populations.<\/p>\n\n\n\n

Theme:<\/strong> AI and the Impact on K-12 Teaching 
Subtheme:<\/strong> Exploring the Preparation of AI-literate, AI-skilled, and AI-ethical college students in the US    <\/p>\n\n\n\n

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Bharat Chandar, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Stanford University <\/em><\/p>\n\n\n\n

Bharat Chandar is a postdoctoral researcher at the Stanford Digital Economy Lab, part of the Institute for Human-Centered AI. Dr. Chandar\u2019s research focuses on AI’s impact on the labor market and productivity using a combination of big data and company partnerships. Bharat is a co-author on the recent \u201cCanaries in the Coalmine\u201d paper from Stanford.<\/p>\n\n\n\n

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Theme:<\/strong> The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> The Labor Market Impacts of Business AI Adoption  <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Manuel Hoffmann, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of California, Irvine <\/em><\/p>\n\n\n\n

Manuel Hoffmann is an Assistant Professor at the University of California, Irvine, at the Paul Merage School of Business and is also affiliated with Stanford University. Dr. Hoffmann\u2019s research focuses on the social and behavioral aspects of open source software and artificial intelligence, with a broader interest in innovation and technology management. His work aims to deepen understanding of strategic issues facing large, medium-sized, and entrepreneurial firms. <\/p>\n\n\n\n

Theme: <\/strong>The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> How Mentorship Affects AI Adoption and Usage – The Generative AI Gender Puzzle <\/p>\n\n\n\n

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\"Frank<\/figure>\n\n\n\n

Frank Nagle, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Massachusetts Institute of Technology <\/em><\/p>\n\n\n\n

Frank Nagle is a Research Scientist at MIT where he studies AI, open source, cybersecurity, and technology strategy. He is also the Chief Economist for The Linux Foundation. <\/p>\n\n\n\n

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Theme: <\/strong>The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> How Mentorship Affects AI Adoption and Usage – The Generative AI Gender Puzzle <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Inbal Talgam-Cohen, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Tel Aviv University, Israel<\/em> <\/em><\/p>\n\n\n\n

Inbal Talgam-Cohen is an interdisciplinary researcher focused on incentives, algorithms, and learning, drawing from the fields of computer science, economics, and law. Dr. Talgam-Cohen is a faculty member at Tel Aviv University and a visiting faculty at the Technion, where she began her academic career before moving to TAU. Her research group spans both institutions.  <\/p>\n\n\n\n

Theme: <\/strong>The Impact of AI on Entry-Level Jobs
Subtheme:<\/strong> Contracts for AI-Empowered Online Labor Markets <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Laura Nurski, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Centre for European Policy Studies (CEPS)<\/em>, Belgium<\/em>  <\/em><\/p>\n\n\n\n

Prof. Dr. Laura Nurski is Head of Program on the Future of Work at the Centre for European Policy Studies (CEPS) in Brussels, where she leads policy research on the impact of artificial intelligence on labor markets, work organization and job quality. She is also Assistant Professor in the Work and Organizations Studies department at KU Leuven (Belgium) where she leads the Acerta Chair AI at Work, conducting experimental (workplace) research on AI and job design.  <\/p>\n\n\n\n

Theme:<\/strong> The Impact of AI on Entry-Level Jobs
Subtheme:<\/strong> First European evidence on AI and entry-level jobs: replicating the Canaries in the Coal Mine <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Michael Impink, PhD (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

HEC Paris, France<\/em> <\/em><\/p>\n\n\n\n

Michael Impink is an Assistant Professor of Strategy at HEC Paris and a research affiliate at Hi! Paris (AI for Society and Business) and Boston University TPRI. His research focuses on how digitization impacts firm structure and performance. Prior to the PhD, Michael was a senior manager at Microsoft based in Seattle and Singapore and a fellow at Harvard University’s Weatherhead Center for International Affairs <\/p>\n\n\n\n

Theme:<\/strong> The Impact of AI on Entry-Level Jobs 
Subtheme:<\/strong> Does the growing use of digital tools pave the way for white-collar apprenticeship programs? <\/p>\n\n\n\n

<\/div>\n\n\n\n

Meet the inaugural first cohort of AIEI senior fellows <\/h3>\n\n\n\n

As AI reshapes the global economy, higher education will be crucial in preparing society for these changes. The AI Economy Institute\u2019s first research cohort is studying how colleges and universities can lead this transformation by examining shifts in university structures, curricula, professional training, and their roles in the workforce. With 14 project teams and 24 scholars from various backgrounds, the Institute seeks to\u202fprovide\u202fpractical insights for policy and collaborative action among academia, industry, and government\u202fon the future of education and workforce. <\/p>\n\n\n\n\n\n

\"Dr.<\/figure>\n\n\n\n

Dr. Adam Cannon (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University<\/em><\/p>\n\n\n\n

Dr. Adam Cannon is a computer science faculty member at Columbia University, where he develops and teaches large undergraduate courses for both majors and non-majors. He has contributed to curriculum design at the departmental, school, and university levels, and chaired the development committee for the AP Computer Science Principles Exam. His current focus is on teaching computer science and AI literacy to liberal arts and humanities students. In 2000 he joined Columbia and also served as a visiting scientist at Los Alamos National Laboratory, where his research focused on machine learning methods for building data-dependent hypothesis classes. He holds a BS and MS in aerospace engineering from the University of California and a PhD in applied mathematics from Johns Hopkins University. <\/p>\n\n\n\n

Project 1:<\/strong> The Evolution of CS Education: Integrating AI as a Foundational Element
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Vishal Misra (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University<\/em><\/p>\n\n\n\n

Vishal Misra is a Professor of Computer Science and Electrical Engineering at Columbia University and Vice Dean for Computing and AI in the School of Engineering. An ACM and IEEE Fellow, his research focuses on mathematical modeling of systems, bridging practice and analysis. As a graduate student, he co-founded CricInfo, later acquired by ESPN. In 2021, he developed one of the first commercial applications using GPT-3 for ESPNcricinfo and has since modeled LLM behavior. He played a key role in India\u2019s Net Neutrality regulation, with his definition adopted by both activists and regulators. He received Distinguished Alumnus honors from IIT Bombay (2019) and UMass Amherst (2014). <\/p>\n\n\n\n

Project 1:<\/strong> The Evolution of CS Education: Integrating AI as a Foundational Element
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Jeffrey<\/figure>\n\n\n\n

Jeffrey Oakman (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Princeton University <\/em><\/p>\n\n\n\n

Jeffrey Oakman joined the Provost\u2019s Office in September 2024 to lead the creation of the New Jersey AI Hub at Princeton. Collaborating with partners including the NJ Economic Development Authority, Microsoft, and CoreWeave, he is guiding efforts to position Princeton and New Jersey as leaders in AI innovation. The Hub will support advanced AI research, regional economic growth, workforce development, public sector guidance, and startup formation. Previously, Oakman served as a Senior Policy Advisor in Governor Murphy\u2019s Administration, focusing on economic and community development. He holds degrees from Rice University and Princeton SPIA, where he also served as Associate Director of the Graduate Program from 2016 to 2019. <\/p>\n\n\n\n

Project 2:<\/strong> Leveraging Artificial Intelligence to Transform Sectors and Reimagine Jobs Throughout the Economy
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"Jennifer<\/figure>\n\n\n\n

Jennifer Rexford (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Princeton University <\/em><\/p>\n\n\n\n

As Provost of Princeton University, Dr. Jennifer Rexford oversees the academic mission and long-term financial health of the institution. A 1991 Princeton graduate, she is the Gordon Y.S. Wu Professor in Engineering. After earning her PhD in electrical engineering and computer science from the University of Michigan, she spent over eight years at AT&T Labs, where she developed techniques used in backbone networks. She joined Princeton\u2019s Department of Computer Science as a full professor in 2005, became department chair in 2015, and received her named professorship in 2012. Her research focuses on computer networking, with a broader goal of making the Internet more trustworthy and reliable. <\/p>\n\n\n\n

Project 2:<\/strong> Leveraging Artificial Intelligence to Transform Sectors and Reimagine Jobs Throughout the Economy
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Matthew Connelly (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University <\/em><\/p>\n\n\n\n

Dr. Matthew Connelly is a Professor of International and Global History and Vice Dean of AI initiatives at Columbia University. He co-led Columbia\u2019s Institute for Social and Economic Research and Policy and directs History Lab, which uses data science to study state secrecy, focusing on intelligence, surveillance, and weapons of mass destruction. Prior to that, he directed the Hertog Global Strategy Initiative on planetary threats. His publications include \u201cA Diplomatic Revolution: Algeria\u2019s Fight for Independence and the Origins of the Post-Cold War Era,\u201d which won five prizes, and \u201cFatal Misconception: The Struggle to Control World Population,\u201d an Economist and Financial Times book of the year. His research appears in journals such as\u202fNature Human Behaviour<\/em>,\u202fAnnals of Applied Statistics<\/em>, and\u202fComparative Studies in Society and History.<\/em> <\/p>\n\n\n\n

Project 3:<\/strong> AI and the Transformation of Higher Education: An Integrated Approach
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr.\u202fSJ Beard (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Cambridge <\/em><\/p>\n\n\n\n

Dr. SJ Beard is a leading researcher in the transdisciplinary field of Existential Risk Studies, focusing on global catastrophic risks, future ethics, and building existential hope. Their work explores systemic threats from transformative technologies and environmental breakdown, and they co-authored\u202fDouble Debt Disaster<\/em>\u202fon injustice and disaster recovery. Beard has edited two volumes on existential risk and is writing a monograph on existential hope. They are a Borysiewicz Interdisciplinary Fellow, advisor to the UK\u2019s All-Party Parliamentary Group for Future Generations, BBC New Generation Thinker, and editorial board member of\u202fFutures<\/em>. Their media work includes BBC programs and appearances on\u202fNewsnight<\/em>,\u202fAnalysis<\/em>, and\u202fThe Naked Scientists<\/em>. <\/p>\n\n\n\n

Project 3:<\/strong> AI and the Transformation of Higher Education: An Integrated Approach
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Morgan Frank (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Pittsburgh <\/em><\/p>\n\n\n\n

Dr. Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh in the Department of Informatics and Networked Systems. He is interested in the complexity of AI, the future of work, and the socio-economic consequences of technological change. While many studies focus on phenotypic labor trends, Dr. Frank\u2019s recent research examines how genotypic skill-level processes around AI impact individuals and society. Combining labor research with investigations into the nature of AI research and the social or societal implications of AI adoption, he hopes to inform our understanding of AI\u2019s impact. Dr. Frank has a PhD from MIT\u2019s Media Lab, was a postdoc at MIT Institute for Data, Systems, and Society (IDSS) and the MIT Initiative on the Digital Economy (IDE) and has a master\u2019s degree in applied mathematics from the University of Vermont. <\/p>\n\n\n\n

Project 4:<\/strong> Evaluating College Education in the Age of LLMs
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n

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\"a<\/figure>\n\n\n\n

Dr. Robert Seamans (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

NYU Stern School of Business <\/em><\/p>\n\n\n\n

Dr. Robert Seamans is a Professor at New York University\u2019s Stern School of Business, where he teaches courses in game theory and strategy. His research focuses on how firms use technology in their strategic interactions with each other, and also on the economic consequences of AI, robotics, and other advanced technologies. His research has been published in leading academic journals and cited in numerous outlets, including The Atlantic, Forbes, Harvard Business Review, The New York Times, The Wall Street Journal, and others. Dr. Seamans is also Director of the Center for the Future of Management. In 2015, he was appointed as the Senior Economist for technology and innovation on President Obama\u2019s Council of Economic Advisers. He holds a PhD from UC Berkeley. <\/p>\n\n\n\n

Project 5:<\/strong> Bots and Business School: Lessons for Business Schools in the Era of Generative AI
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Business and Management Contexts <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Arun Sundararajan (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

NYU Stern School of Business <\/em><\/p>\n\n\n\n

Dr. Arun Sundararajan is the Harold Price Professor of Entrepreneurship and Professor of Technology, Operations, and Statistics at NYU Stern School of Business, where he also directs the Fubon Center for Technology, Business, and Innovation, and teaches about AI, digital strategy, and entrepreneurship. His award-winning book, \u201cThe Sharing Economy,\u201d has been translated into multiple languages. He co-chairs the World Economic Forum\u2019s Global Future Council on Data Frontiers and is an expert on the economics of digital goods, network effects, and the regulation of AI and digital platforms. He has published over 50 scientific papers and more than 40 op-eds in major outlets, and his work has earned numerous awards. <\/p>\n\n\n\n

Project 5:<\/strong> Bots and Business School: Lessons for Business Schools in the Era of Generative AI
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Business and Management Contexts <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Amy J. Ko (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Washington <\/em><\/p>\n\n\n\n

Dr. Amy J. Ko is a Professor at the University of Washington Information School and the Paul G. Allen School of Computer Science and Engineering. She co-directs the UW Center for Learning, Computing, and Imagination, where she studies computing education, human-computer interaction, and humanity\u2019s individual and collective struggle to understand computing and harness it for creativity, equity, and justice. Alongside her collaborators, she has influenced K\u201312 computer science education policy at local, state, and federal levels. Her work spans more than 140 peer-reviewed publications, with 22 distinguished paper awards and 6 most influential paper awards. She is an ACM Distinguished Member and a member of the SIGCHI Academy. She received her PhD at the Human-Computer Interaction Institute at Carnegie Mellon University and has degrees in Computer Science and Psychology with Honors from Oregon State University. <\/p>\n\n\n\n

Project 6:<\/strong> Imagining Education Futures with Generative AI
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Benjamin Shapiro (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Washington <\/em><\/p>\n\n\n\n

Dr. R. Benjamin Shapiro is an Associate Professor and the Associate Director for Community in the Paul G. Allen School of Computer Science & Engineering and in Human-Centered Design & Engineering and Learning Sciences & Human Development at the University of Washington (UW), where he is also co-director of the Center for Learning, Computing, and Imagination. Ben is a learning scientist, and his research concentrates on developing ways for youth and adults to create and use computational media for creative expression, investigation of the world around them, and making positive social change. His award-winning, inter- and trans-disciplinary research engages with topics ranging from AI education and research ethics to feminist re-imagination of science and art education. He earned his PhD in Learning Sciences from Northwestern University and his B.A. in Independent Studies from UC San Diego. <\/p>\n\n\n\n

Project 6:<\/strong> Imagining Education Futures with Generative AI
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Karl Gunther (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Florida <\/em><\/p>\n\n\n\n

Dr. Karl Gunther is a historian of the English Reformation. He earned his B.A. in Philosophy and History from Wheaton College (IL), and his M.A. and PhD in History from Northwestern University. His publications include the book\u202fReformation Unbound: Protestant Visions of Reform in England, 1525\u20131590<\/em>\u202f(Cambridge University Press, 2014), which was a finalist for the Royal Historical Society\u2019s Whitfield Prize and runner-up for the American Society of Church History\u2019s Brewer Prize. A fellow of the Royal Historical Society, he has also served as President of the Southern Conference on British Studies. Dr. Gunther was previously Associate Professor of History at the University of Miami, where he taught for fifteen years and held roles including Director of Undergraduate Studies, co-convener of the Medieval and Early Modern Studies Research Group, and chair of the Faculty Senate\u2019s Student Affairs Committee. <\/p>\n\n\n\n

Project 7:<\/strong> Designing Interdisciplinary AI Systems: Challenges and Collaborative Solutions
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Interdisciplinary Nature <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Daniel Maxwell (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Florida <\/em><\/p>\n\n\n\n

Dr. Daniel Maxwell is a humanist at heart, having graduated from a small liberal arts college in Eastern Washington with double majors in History and French. Although his career has focused on technology, Daniel remains committed to the idea and values of a classical liberal arts education. To that end, he positions his work at the intersection of technology and the humanities. Dr. Maxwell is skilled in research system design and open science technologies, including Python, SQL, GitHub, Linux, and deep learning frameworks (PyTorch & TensorFlow). He enjoys helping scholars improve their research workflows through the judicious application of artificial intelligence. Daniel also loves learning Italian and is a student of Italian Renaissance culture, art, and literature. <\/p>\n\n\n\n

Project 7:<\/strong> Designing Interdisciplinary AI Systems: Challenges and Collaborative Solutions
Theme:<\/strong> AI Systems Design, Fluency\u202fand Engineering 
Subtheme:<\/strong> Interdisciplinary Nature <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Xiaopeng Zhao (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Tennessee <\/em><\/p>\n\n\n\n

Dr. Xiaopeng Zhao is a Professor of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville, specializing in AI and robotics, particularly in healthcare and education. With over 20 years of academic and research experience, he has led innovative AI-driven projects developing assistive technologies to improve life for individuals with disabilities and their caregivers. As founding director of the Applied AI Program at UTK, Dr. Zhao helped establish interdisciplinary AI research and education, fostering collaboration across engineering, healthcare, and policy. He currently serves as an AAAS Congressional Science & Technology Policy Fellow, engaging in legislative work on AI, technology, education, and policy. His expertise bridges academic research, policy, and real-world AI implementation. <\/p>\n\n\n\n

Project 8:<\/strong> Bridging AI Fluency and Workforce Readiness
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI as a New Major\/College <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Mehmet Aydeniz (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Tennessee <\/em><\/p>\n\n\n\n

Dr. Mehmet Aydeniz is a Professor of STEM Education and a faculty fellow in the College of Emerging and Collaborative Studies at the University of Tennessee, Knoxville (UTK), where he leads research on innovation in teaching and learning across the K\u201316 continuum. His work focuses on equipping educators and students with the skills needed in a data-driven, AI-powered world. He has published extensively on inquiry-based science education, teacher development, and equity in STEM. He founded COLABS, a research initiative examining scientific collaboration across boundaries. His current research explores how AI integration drives skill turnover and informs curriculum and workforce strategies. He also hosts\u202fNavigating Tomorrow Today in Higher Education<\/em>, a webinar series spotlighting bold ideas for institutional innovation. <\/p>\n\n\n\n

Project 8:<\/strong> Bridging AI Fluency and Workforce Readiness
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI as a New Major\/College <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Bassel Daher (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Texas A&M Energy Institute <\/em><\/p>\n\n\n\n

Dr. Bassel Daher is Assistant Director for Sustainable Development at the Texas A&M Energy Institute, Adjunct Assistant Professor of Biological & Agricultural Engineering, and a Research Fellow at the Institute for Science, Technology, and Public Policy. His work applies systems thinking to global challenges such as food system transformation, energy transition, water management, disaster risk reduction, planetary health, and climate action. He promotes evidence-based, cross-sector collaboration to advance sustainable and equitable futures. Daher integrates research, education, network-building, and community engagement, contributing to over $8 million in funding and 70 highly cited publications. He is a frequent international speaker, including a TEDx Talk, and has held research roles at Texas A&M, Purdue, and Qatar Foundation. He serves on the Executive Board of the International Water Resources Association and co-chaired the Zero Hunger Pathways Project (2020\u20132023). <\/p>\n\n\n\n

Project 9:<\/strong> The Evolving Role of Universities in the AI Era: Opportunities for Improving AI Literacy Through Micro-credentials and Interdisciplinary Curriculum Design
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Micro-Credentials and Certifications <\/p>\n\n\n\n

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\"Dr.<\/figure>\n\n\n\n

Dr. Konstantinos Pappas (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Texas A&M Energy Institute <\/em><\/p>\n\n\n\n

Dr. Konstantinos Pappas is the Associate Director of the Texas A&M Energy Institute. In his 28-year career, he has held senior roles in program management, policy development, and research, including within the European Commission, where he integrated environmental and resource considerations into sustainable development frameworks. Since 2018, he has overseen major projects emphasizing stakeholder engagement in areas such as Carbon Capture and Renewable Technologies. Dr. Pappas\u2019s research focuses on migration economics, international development and sustainability, the societal impacts of energy transition, and stakeholder engagement. Through collaborations with the United Nations Disaster Risk Reduction Office and NATO, his work in the last four years has addressed the interconnected challenges of water, energy, and food in the context of climate change, human mobility, and security. <\/p>\n\n\n\n

Project 9:<\/strong> The Evolving Role of Universities in the AI Era: Opportunities for Improving AI Literacy Through Micro-credentials and Interdisciplinary Curriculum Design
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Micro-Credentials and Certifications <\/p>\n\n\n\n

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Dr. Kenneth R. Fleischmann (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The University of Texas at Austin <\/em><\/p>\n\n\n\n

Dr. Kenneth R. Fleischmann is a Professor in the School of Information at The University of Texas at Austin. He is the Founding Chair of the Executive Team for Good Systems, a UT Grand Challenge, and the Founding Director of Undergraduate Studies for the iSchool\u2019s B.A.\/B.S. in Informatics. His research and teaching focus on AI ethics and the role of human values in designing and using information technologies. His work has been funded by the National Science Foundation (NSF), IARPA, Microsoft Research, Cisco Research, Micron Foundation, and the Public Interest Technology University Network. His research has earned awards including the iConference Best Paper Award, ASIS&T SIG-USE Best Information Behavior Conference Paper Award, ALA Library Instruction Round Table Top Twenty Articles, ASIS&T SIG-SI Social Informatics Best Paper Award, ASIS&T SIG-AI Artificial Intelligence Best Paper Award, the Civic Futures Award, and the MetroLab Innovation of the Month Award. He is also the Founding Editor-in-Chief of the ACM Journal on Responsible Computing. <\/p>\n\n\n\n

Project 10:<\/strong> Centering Ethics in the AI Curriculum: Scaling Up AI Ethics Education Nationwide
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Shift Toward Ethics and Social Sciences <\/p>\n\n\n\n

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Dr. Leo Porter (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of California, San Diego <\/em><\/p>\n\n\n\n

Dr. Leo Porter is a Professor in the Computer Science and Engineering Department at UC San Diego. He is best known for his research on the impact of Peer Instruction in computing courses, the use of clicker data to predict student outcomes, and the development of the Basic Data Structures Concept Inventory. He co-wrote the first book on integrating LLMs into the instruction of programming with Daniel Zingaro, entitled \u201cLearn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT\u201d. He has received six Best Paper Awards, SIGCSE 50th Anniversary Top Ten Symposium Papers of All Time Award, the Outstanding Teaching Award from Warren College, and the Academic Senate Distinguished Teaching Award at UC San Diego. He is a Distinguished Member of the ACM, recently served as Secretary of the SIGCSE Board, and presently serves as Program Chair for ICER. <\/p>\n\n\n\n

Project 11:<\/strong> How Introductory Programming Students Use Generative AI While Coding
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Daniel Zingaro (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Toronto <\/em><\/p>\n\n\n\n

Dr. Daniel Zingaro\u202f<\/strong>is an Associate Teaching Professor at the University of Toronto. He has taught introductory Python programming to thousands of students over the past 15 years and has written both no-GenAI and, with Leo Porter, GenAI Python textbooks. Dan has also authored and co-authored textbooks on algorithms and competitive programming and incorporates as much research-backed instruction as he can into his writing. He is the recipient of the SIGCSE 50th Anniversary Top Ten Symposium Papers of All Time Award, an ICER Best Paper award, and the Computer Science Canada Excellence in Teaching Award. <\/p>\n\n\n\n

Project 11:<\/strong> How Introductory Programming Students Use Generative AI While Coding
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> AI Integration into CS Curricula <\/p>\n\n\n\n

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Dr. Stephanie Moore (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of New Mexico <\/em><\/p>\n\n\n\n

Dr. Stephanie Moore is an Associate Professor in the Organization, Information, and Learning Sciences program and a Barbara Bush Foundation \/ Dollar General Foundation Fellow. Her research focuses on technology use in adult reading, digital literacies, online and blended learning design, and the ethics of technology in education and the workplace, including AI. Previously, Dr. Moore was an Assistant Professor at the University of Virginia, where she taught instructional design and ethics for learning technologies. She has received multiple awards including the AACTE Innovation of the Year Award and the Leadership in Education award, led and developed award-winning programs, and held leadership roles in AECT. She is Editor-in-Chief of the\u202fJournal of Computing in Higher Education<\/em>\u202fand consults globally through the U.S. Department of State\u2019s US Speakers Program, advising embassies on effective digital learning strategies. <\/p>\n\n\n\n

Project 12:<\/strong> Creating Inter-disciplinary Educational Pathways for AI Leadership
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Less Focus on Coding <\/p>\n\n\n\n

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Dr. Victor Law (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of New Mexico <\/em><\/p>\n\n\n\n

Dr. Victor Law is an Associate Professor and Program Director of the Organization, Information, and Learning Sciences (OILS) Program at the University of New Mexico. He has extensive expertise in educational psychology, instructional technology, and the application of technology in learning environments. Dr. Law holds a PhD in Educational Psychology with a concentration in Instructional Psychology & Technology from the University of Oklahoma. His research interests include artificial intelligence in education, ill-structured problem solving, computer-supported collaborative learning, self-regulation, game-based learning, and the adoption and use of technology in education. He has published in top journals and served on the editorial board of major journals such as Educational Technology Research and Development and Interdisciplinary Journal of Problem-Based Learning. <\/p>\n\n\n\n

Project 12:<\/strong> Creating Inter-disciplinary Educational Pathways for AI Leadership
Theme:<\/strong> Evolution of Computer Science 
Subtheme:<\/strong> Less Focus on Coding <\/p>\n\n\n\n

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Dr. Fabian Stephany (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Dr. Fabian Stephany is a Departmental Research Lecturer in AI & Work at the Oxford Internet Institute, University of Oxford, and a Research Affiliate at the Humboldt Institute in Berlin. He leads the SkillScale Project, exploring emerging skills and sustainable occupations amid tech disruption. He co-created the Online Labour Observatory with the ILO. His work has been published in top journals and featured in major media like The New York Times and Nikkei Asia. Dr. Stephany holds a PhD and degrees from institutions including Universit\u00e0 Bocconi and the University of Cambridge and has worked with the UNDP, World Bank, and OECD. <\/p>\n\n\n\n

Project 13:<\/strong> Bridging the AI Skills Gap: Examining AI Literacy, Reskilling Pathways, and Micro-Credentials in the US and UK
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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Dr. Ole Teutloff (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Dr. Ole Teutloff is an incoming postdoctoral researcher at the Oxford Internet Institute and is affiliated with the Copenhagen Center for Social Data Science. His research uses computational social science methods to study the impact of technological innovations on society. Ole\u2019s work particularly focuses on the labor market implications of transformative AI and the effects of technological change on inequality. He holds a PhD in Social Data Science from the University of Copenhagen, an MSc in Social Data Science from the University of Oxford, and a Master of Public Policy from the Hertie School in Berlin. Previously, he has worked in various international contexts including the Centre for the Governance of AI, the OECD, and the World Bank. <\/p>\n\n\n\n

Project 13:<\/strong> Bridging the AI Skills Gap: Examining AI Literacy, Reskilling Pathways, and Micro-Credentials in the US and UK
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> AI Fluency and Workforce Training <\/p>\n\n\n\n

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Dr. Jeffrey Nii Armah Aryee (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Kwame Nkrumah University of Science and Technology <\/em><\/p>\n\n\n\n

Dr. Jeffrey Nii Armah Aryee is a Lecturer in the Department of Meteorology and Climate Science at Kwame Nkrumah University of Science and Technology (KNUST) in Kumasi, Ghana. He holds a PhD in Meteorology and Climate Science from KNUST, completed under the European Union\u2019s 7th Framework Programme funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud-Interactions in West Africa) Project. Dr. Aryee\u2019s research interests include climate data reconstruction, boundary-layer meteorology, climate variability and change, ML\/AI applications in climate science and climate impact studies. He is the Lead for the JNAA research group (JNAA Lab) and served as the satellite data scientist for the KNUST cohort of the GCRF African SWIFT (Science for Weather Information and Forecasting Techniques) Project. Dr. Aryee is the PI for the ANDeL (Advancing Nowcasting with Deep Learning techniques), Ghana AQ Data Hub and TechAir projects. He also collaborates with an extensive scientific community on other projects such as the EW4ENERGY (Early Warning for Energy) project. He is also the group lead for PY4CA, a scientific computing solutions team involved in building science-related problem-based solutions and applications. <\/p>\n\n\n\n

Project 14:<\/strong> Revolutionizing Tertiary Education for Africa\u2019s Thriving AI Economy and Workforce (RetAIn) Project: Expanding Access to AI Education, Fluency, and Workforce Training
Theme:<\/strong> AI literacy, Professional Training and Reskilling 
Subtheme:<\/strong> Access to AI Education <\/p>\n\n\n\n\n\n

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Advising Fellows, guiding scholarship with issue-area expertise<\/h3>\n\n\n\n

The AI Economy Institute\u2019s Advising Fellows are a distinguished group of global thought researchers who have expertise in the areas of the AI economy. Their participation in AIEI helps to ensure scholarly rigor and reach across our cohorts. These experts play a pivotal role in shaping AIEI\u2019s intellectual agenda\u2014bringing deep expertise in economics, technology, and workforce transformation to guide research and amplify impact.<\/p>\n\n\n\n

Advising Fellows contribute far beyond proposal review. They participate in virtual and in-person convenings, contribute editorial insights, and help position AIEI as a trusted source of evidence-based guidance on the future of education and work in an AI-driven economy. By affiliating with AIEI, they accelerate the dissemination of research and ideas that inform policy, industry, and academia worldwide.<\/p>\n\n\n\n\n\n

Elizabeth J. Altman (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Massachusetts\u2013Lowell <\/em><\/p>\n\n\n\n

Elizabeth J. Altman is Associate Professor of Management at the University of Massachusetts\u2013Lowell\u2019s Manning School of Business. She is a Research Affiliate with the MIT Initiative on the Digital Economy and a Nonresident Fellow at Brookings, and has held visiting appointments at Harvard Business School. Altman is lead author of Workforce Ecosystems<\/em> (MIT Press, 2023), and her research explores organizational strategy and workforce transformation in the digital economy. <\/p>\n\n\n\n

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G\u00e1bor B\u00e9k\u00e9s (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Central European University <\/em><\/p>\n\n\n\n

G\u00e1bor B\u00e9k\u00e9s is Associate Professor at Central European University in the Department of Economics and Business. He is a Research Affiliate at CEPR and Senior Research Fellow at the KRTK Institute of Economics in Hungary. B\u00e9k\u00e9s co-authored Data Analysis for Business, Economics, and Policy<\/em> (Cambridge University Press, 2021), and his work focuses on applied data analysis and business economics. <\/p>\n\n\n\n

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Daniel Bj\u00f6rkegren (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Columbia University <\/em><\/p>\n\n\n\n

Daniel Bj\u00f6rkegren is Assistant Professor of International and Public Affairs at Columbia University\u2019s School of International and Public Affairs. He leads the AI & Development initiative at Columbia\u2019s Center for Development Economics and Policy and is affiliated with BREAD, J-PAL, and the Data Science Institute. Bj\u00f6rkegren\u2019s research examines the intersection of AI and development, including policy-relevant fieldwork in Africa. <\/p>\n\n\n\n

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Anders Humlum (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Chicago Booth School of Business <\/em><\/p>\n\n\n\n

Anders Humlum is Assistant Professor of Economics and Fujimori\/Mou Faculty Scholar at the University of Chicago Booth School of Business. He is a Research Affiliate at IZA and previously held a postdoctoral fellowship at the Becker Friedman Institute. Humlum\u2019s research focuses on the labor market impacts of automation and artificial intelligence. <\/p>\n\n\n\n

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Frank Nagle (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

MIT Initiative on the Digital Economy <\/em><\/p>\n\n\n\n

Frank Nagle is a Research Scientist at the MIT Initiative on the Digital Economy and advises the Linux Foundation as Chief Economist. He previously served as Assistant Professor of Strategy at Harvard Business School. Nagle\u2019s work includes widely cited research estimating the multi-trillion-dollar economic value created by open-source software. <\/p>\n\n\n\n

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Gal Oestreicher-Singer (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

Tel Aviv University <\/em><\/p>\n\n\n\n

Gal Oestreicher-Singer is Mexico Professor of Information Systems and Associate Dean for Research at the Coller School of Management, Tel Aviv University. She is an Adjunct Professor at NYU Stern and has held senior editorial roles in MIS journals. Oestreicher-Singer\u2019s research examines digital platforms, social networks, and e-commerce, and she is a recent recipient of the Kadar Family Award. <\/p>\n\n\n\n

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Daniel Rock (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The Wharton School at the University of Pennsylvania <\/em><\/p>\n\n\n\n

Daniel Rock is Assistant Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania. He is a Digital Fellow at the MIT Initiative on the Digital Economy and affiliated with NBER and Stanford\u2019s Digital Economy Lab. Rock co-authored the Science article \u201cGPTs are GPTs\u201d (2024) and the AEJ: Macroeconomics paper on the \u201cProductivity J Curve.\u201d <\/p>\n\n\n\n

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Wesley Rosslyn Smith (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Pretoria <\/em><\/p>\n\n\n\n

Wesley Rosslyn Smith is Associate Professor in the Department of Business Management at the University of Pretoria and Director of the Centre for the Future of Work. He also lectures at the Gordon Institute of Business Science. Rosslyn Smith\u2019s research and teaching focus on corporate strategy, turnaround management, business analytics, and the future of work. <\/p>\n\n\n\n

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Fabian Stephany (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

University of Oxford <\/em><\/p>\n\n\n\n

Fabian Stephany is Departmental Research Lecturer in AI and Work at the Oxford Internet Institute, University of Oxford. He is a Senior Research Fellow at the Oxford Martin School and a Fellow at Bruegel, and co-created the Online Labour Observatory with the ILO. Stephany serves on the World Economic Forum\u2019s Global Future Council on Human Capital Development. <\/p>\n\n\n\n

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Prasanna (Sonny) Tambe (opens in new tab)<\/span><\/a><\/h4>\n\n\n\n

The Wharton School at University of Pennsylvania <\/em><\/p>\n\n\n\n

Prasanna Tambe is Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania, where he co-directs AI at Wharton. He is a Digital Fellow at the MIT Initiative on the Digital Economy and affiliated with NBER. Tambe\u2019s research explores the economics of technology and labor, including widely cited work on AI in human resource management. <\/p>\n\n\n\n\n\n

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Interested in becoming an advisor, share research question ideas or have general questions – contact us (opens in new tab)<\/span><\/a>!<\/p>\n\n\n\n

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AI Economy Institute Cohort 3 Open Call<\/h2>\n\n\n\n
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About AI Economy Institute<\/h3>\n\n\n\n

Launched in 2025, Microsoft\u2019s AI Economy Institute (AIEI) supports independent, policy-relevant research on how artificial intelligence is reshaping productivity, labor markets, education systems, and economic opportunity, worldwide. AIEI advances rigorous scholarship that informs policymakers, educators, employers, and workers as societies adapt to the rapid diffusion of generative AI.  The institute emphasizes scholarship that is immediately translatable top policy, decision-making, and investment.<\/p>\n\n\n\n

All research supported by AIEI is conducted independently. Findings, interpretations, and conclusions are those of the authors and do not represent the views of Microsoft.<\/em><\/p>\n\n\n\n

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AIEI research to date<\/h3>\n\n\n\n

Since its launch, the AI Economy Institute has convened two research cohorts through open and targeted Calls for Proposals, supporting independent scholarship across a range of topics related to AI\u2019s economic and societal impacts.<\/p>\n\n\n\n

Previous cohorts have focused on studying:<\/p>\n\n\n\n