AI Research

AI Economy Institute (AIEI) Program

Published

1 month ago

August 1, 2025

“Education in the AI Economy: Diffusion, disruption, and design for purposeful transformation”

The Microsoft AI Economy Institute (AIEI) invites proposals for its second global research call, inviting submissions that will help shape the future of work, learning, and opportunity in the age of generative AI. As GenAI is demonstrating the potential to become the most widely adopted technology in history, we face a defining moment: will its benefits be broadly shared, or will barriers—technical, institutional, regulatory, economic, educational, and cultural—limit its promise for people and communities around the world?

Microsoft established AIEI to support the diffusion of AI so that it is intentional, inclusive, and informed by rigorous research and scholarly discourse so that societies everywhere may adapt to the economic and social changes AI brings. We seek to accelerate understanding of how GenAI is transforming productivity, labor markets, and workforce development across sectors and geographies. We are especially interested in research that identifies the drivers and barriers to GenAI adoption, and that offers actionable insights for policymakers, educators, employers, and workers.

We invite proposals that address any of the following questions and themes:

1. The Impact of AI on Entry-Level Jobs

What empirical data can be developed to document and analyze the actual impact of AI on entry-level jobs?
In which fields is this impact most pronounced, and why?
How are employers and employees responding? Are employers changing the nature of entry-level work or the employment experience? Are training programs evolving?
How are employees adapting, and what is the impact on AI skills development for both employees and employers?
What lessons can be drawn from apprenticeship programs in Switzerland, Germany, and labor unions?
What does the impact of AI on entry-level jobs mean for the architecture of a career path, including consideration of rapid credentialing and stackable certificates in driving entry-level supply?

2. AI and the Impact on K-12 Teaching

How is AI likely to impact different aspects of teachers’ work, such as administrative tasks, lesson planning, and grading? And how might this affect teacher retention?
What studies best document how teachers currently spend their time, and how might AI help align this with how they would like to spend their time?
What best practices are emerging, and what will be the impact of AI on classroom time?
What insights can inform the development of new products and tools to support teachers?
What are ethical concerns for use of AI in the K-12 classroom and how are AI ethics taught in a K-12 environment?

3. AI and Opportunities for Community, Technical, and Vocational Colleges

How do the questions above apply to community colleges and technical/vocational education?
What unique opportunities and challenges exist for these institutions in preparing students for an AI-enabled workforce?
Thinking about the American investment in land-grant institutions, how could the existing two-year, community, and technical colleges network provide a platform for the rapid diffusion of AI fluency into the workforce?

4. AI and National Diffusion Differences

What conditions best explain why some countries adopt AI faster than others? Do we see links between AI fluency skilling efforts or initiatives and rates of diffusion?
How do national strategies and approaches to data governance and AI regulation shape AI development and use? For example, what strategies are Singapore and the UAE deploying to become early leaders, and are they seeing measurable national dividends?
What policies or practices can be replicated to accelerate responsible AI adoption? How do differences in workforce skills, demographics, and labor needs affect AI adoption across countries?
What policies or programs have helped countries adopt AI responsibly and can they be adapted or scaled elsewhere?

Research Priorities

Proposals should provide a unique approach to advancing the AIEI mission of helping society prepare for the economic transformation driven by the advent of GenAI with consideration of what are barriers to GenAI diffusion across sectors and strategies to address such barriers.

Proposals will be prioritized that:

Are cross, multi, and interdisciplinary
Consider multilayer impacts of the AI Economy
Compare and contrast country and/or regional perspectives
Propose a novel direction of scholarship in alignment with the AIEI mission
Use existing data sets or leverage existing platforms for collecting data
Consider longer-term effects of AI on education, including both challenges and opportunities

Commitment to Program Deliverables

Each awardee will be expected to:

Participate in biweekly virtual convenings that may include interim deliverables, including data analyses, initial findings, and working papers (November 1, 2025 – March 31, 2026)
Workshop with other awardees and Microsoft leadership in person at a Microsoft location, providing an abstract, problem and motivation, brief literature review, methodology, preliminary results, discussion, limitations, and references to further scholarship of AIEI (April 2026))
Contribute a book chapter for a book that will synthesize the findings and observations of the research cohort (May 1, 2026)
Participate in a policy workshop (June 2026)
Conduct research and submit a manuscript to a high-quality, open-access journal within nine-months of notification of award (June 30, 2026)

Researchers will be recognized as senior fellows of the AI Economy Institute and, as appropriate, will be offered opportunities to present their findings at industry events and conferences.

Potential for Long-Term Collaboration

Collaboration may extend beyond the funding period. Depending on the structure of the AIEI, future opportunities could include:

Additional research projects or commissioned studies and funding focused on AI and the economic impacts thereof;
Consulting engagements, guest lectures, and involvement with industry;
Opportunities to highlight an existing body of work and academic affiliations.

Eligibility and Format

Open to researchers affiliated with accredited universities or research institutions, worldwide
One principal investigator (PI) per proposal; interdisciplinary teams encouraged
Each selected PI will receive a $75,000 grant plus a travel allowance for the in-person convening; for the travel allowance, awardees in the United States, Canada, and Mexico will receive $7,500 and all other awardees will receive $20,000
Researchers will produce:
- A peer-reviewed journal article
- A book chapter for AIEI’s second volume, to be published in 2026

Timeline

Proposal deadline: September 29, 2025, 5PM Pacific time
Award notification: October 27, 2025
Research period: November 1, 2025 – June 30, 2026
Virtual convenings: Biweekly, November 1, 2025 – March 31, 2026
Timeline for book chapter deliverables shared: November 3-7, 2025
In-person workshop: April 2026
Book chapter submission: May 1, 2026
In-person policy convening: June 2026
Manuscript submission: June 30, 2026

Evaluation Criteria

Relevance to the AI economy and alignment with AIEI’s mission (25%)
Originality and potential for scholarly and policy impact (25%)
Methodological rigor, feasibility, and likelihood of meeting deliverable timelines (25%)
Commitment to equity, interdisciplinarity, and real-world application (25%)

Submit your proposal >

Back to AIEI home page >

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AI Research

Lenovo research shows that AI investments in healthcare industry soar by 169%

Published

36 minutes ago

September 11, 2025

Mark Forker

Research from Lenovo reveals that 96% of retail sector AI deployments are meeting or exceeding expectations – outpacing other industries. While finance and healthcare are investing heavily, their results show mixed returns, highlighting sharp differences in how AI is being applied across sectors.

Lenovo research has demonstrated a huge rise in AI investments across the retail, healthcare and financial services sectors.

The CIO Playbook 2025, Lenovo’s study of EMEA IT leaders in partnership with IDC, uncovers sharply different attitudes, investment strategies, and outcomes across the Healthcare, Retail, and, Banking, Financial Services & Insurance (BFSI) industries.

Caution Pays Off for EMEA BFSI and Retail sectors

Of all the sectors analysed, BFSI stands out for its caution. Potentially reflecting the highly regulated nature of the industry, only 7% of organisations have adopted AI, and just 38% of AI budgets allocated to Generative AI (GenAI) in 2025 – the lowest across all sectors surveyed.

While the industry is taking a necessarily measured approach to innovation, the strategy appears to be paying dividends: BFSI companies reported the highest rate of AI projects exceeding expectations (33%), suggesting that when AI is deployed, it’s well-aligned with specific needs and workloads.

A similar pattern is visible in Retail, where 61% of organisations are still in the pilot phase. Despite below-average projected spending growth (97%), the sector reported a remarkable 96% of AI deployments to date either meeting or exceeding expectations, the highest combined satisfaction score among all industries surveyed.

Healthcare: Rapid Investment, Uneven Results

In contrast, the healthcare sector is moving quickly to catch up, planning a 169% increase in AI spending over 2025, the largest increase of any industry. But spend doesn’t directly translate to success. Healthcare currently has the lowest AI adoption rate and the highest proportion of organisations reporting that AI fell short of expectations.

This disconnect suggests that, while the industry is investing heavily, it may lack the internal expertise or strategy needed to implement AI effectively and may require stronger external support and guidance to ensure success.

One Technology, Many Journeys

“These findings confirm that there’s no one-size-fits-all approach to AI,” said Simone Larsson, Head of Enterprise AI, Lenovo. “Whether businesses are looking to take a bold leap with AI, or a more measured step-by-step approach, every industry faces unique challenges and opportunities. Regardless of these factors, identification of business challenges and opportunity areas followed by the development of a robust plan provides a foundation on which to build a successful AI deployment.”

The CIO Playbook 2025 is designed to help IT leaders benchmark their progress and learn from peers across industries and geographies. The report provides actionable insights on AI strategy, infrastructure, and transformation priorities in 2025 and beyond. The full CIO Playbook 2025 report for EMEA can be downloaded here.

Europe and Middle East CIO Playbook 2025, It’s Time for AI-nomics features research from IDC, commissioned by Lenovo, which surveyed 620 IT decision-makers in nine markets, [Denmark, Eastern Europe, France, Germany, Italy, Middle East, Netherlands, Spain and United Kingdom]. Fieldwork was conducted in November 2024.

Explore the full EMEA Lenovo AInomics Report here.

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AI Research

Augment Raises $85 Million for AI Teammate for Logistics

Published

1 hour ago

September 11, 2025

PYMNTS

Augment raised $85 million in a Series A funding round to accelerate the development of its artificial intelligence teammate for logistics, Augie.

The company will use the new capital to hire more than 50 engineers to “push the frontier of agentic AI” and to expand Augie into more logistics workflows for shippers, brokers, carriers and distributors, according to a Sept. 4 press release.

Augie performs tasks in quoting, dispatch, tracking, appointment scheduling, document collection and billing, the release said. It understands the context of every shipment and acts across email, phone, TMS, portals and chat.

“Logistics runs on millions of decisions—under pressure, across fragmented systems and with too many tabs open,” Augment co-founder and CEO Harish Abbott said in the release. “Augie doesn’t just assist. It takes ownership.”

Augment launched out of stealth five months ago, and the Series A funding brings its total capital raised to $110 million, according to the release.

When announcing the company’s launch in a March 18 blog post, Abbott said Augie does all the tedious work so that staff can focus on more important tasks.

“What exactly does Augie do?” Abbott said in the post. “Augie can read/write documents, respond to emails, make calls and receive calls, log into systems, do data entry and document uploads.”

Augie is now used by dozens of third-party logistics providers and shippers and supports more than $35 billion in freight under management, per the Sept. 4 press release.

Customers have reported a 40% reduction in invoice delays, an eight-day acceleration in billing cycles, 5% or greater gross margin recovery per load and, across all customers, millions of dollars in track and trace payroll savings, the release said.

Jacob Effron, managing director at Redpoint Ventures, which led the funding round, said in the release that Augment is “creating the system of work the logistics industry has always needed.”

“Customers consistently highlight Augment’s speed, deeply collaborative approach and transformative impact on productivity,” Effron said.

In another development in the space, Authentica said Tuesday (Sept. 9) that it launched an AI platform designed to deliver real-time supply chain visibility and automate compliance.

In May, AI logistics software startup Pallet raised $27 million in a Series B funding round.

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.

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AI Research

The race to power artificial intelligence

Published

1 hour ago

September 11, 2025

EMMA WITHROW | Fact Check Team

WASHINGTON (TNND) — The United States is experiencing a significant increase in electricity demand due to the rapid growth of artificial intelligence technologies. According to an analysis from Berkeley Lab, data centers currently consume about 4.4% of all U.S. electricity, a figure expected to rise sharply as AI models require more power. By 2028, over half of this consumption could be attributed to AI alone, equivalent to powering 22% of all U.S. households.

Most of this electricity is generated from fossil fuels, with data centers operating on grids that emit 48% more carbon than the national average, said a report from MIT Technology Review. While companies like Meta and Microsoft are investing in nuclear power, natural gas remains the primary energy source.

In response to the growing demand, President Donald Trump signed an executive order in April directing the Department of Energy to expedite emergency approvals for power plants to operate at full capacity during peak demand. The order also mandates the development of a uniform methodology to assess reserve margins and identify critical power plants essential for grid reliability.

Despite these measures, concerns remain about the U.S.’s ability to provide the 24/7 power required by AI, especially as China implements plans to ensure reliable electricity for data centers. According to reporting from Forbes, “the U.S. does not have a coherent and continuing energy plan of any type. China’s central planning allows for development and sustainability, while the U.S. approach to energy changes every four years”.

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