Stanford HAI Index highlights transformative developments in synthetic intelligence that carry profound implications for societies worldwide—particularly in areas throughout the International South [1]. As we discover these insights, we acknowledge that AI is remodeling industries, creating new alternatives, and driving financial development. There are extraordinary alternatives that AI presents and a shared duty to make sure its advantages are accessible.
A Steep Drop in Prices and Obstacles
Some of the outstanding shifts has been the dramatic discount in the price of AI mannequin utilization. The price of querying an AI mannequin that scores the equal of GPT-3.5 fell from $20 per million tokens in late 2022 to simply $0.07 by late 2024. This greater than 99% lower isn’t merely a technical milestone—it’s a gateway to entry. Innovators and entrepreneurs in low-resource areas can now harness highly effective instruments as soon as restricted to the world’s largest firms, making use of them to native challenges in healthcare, agriculture, training, and public service.
Closing the Efficiency Hole
The hole between open-weight and proprietary closed-weight fashions has additionally narrowed considerably. By 2024, open-weight fashions rival their business counterparts, fueling competitors and innovation throughout the ecosystem. In parallel, the efficiency hole between the highest frontier fashions has additionally compressed. Smaller fashions are reaching outcomes as soon as thought unique to massive-scale programs—Microsoft’s Phi-3-mini, for example, delivers efficiency akin to fashions 142 occasions bigger, bringing highly effective AI inside attain of environments with constrained sources.
Persistent Challenges: Reasoning and Knowledge
But challenges stay. Regardless of advances, AI programs nonetheless battle with higher-order reasoning, akin to arithmetic and strategic planning—capabilities which are important in domains the place reliability is crucial. Continued analysis and accountable utility are important to beat these limitations.
One other rising concern is the speedy discount of publicly obtainable knowledge used to coach AI fashions. As web sites more and more prohibit knowledge scraping, mannequin efficiency and generalizability might undergo—particularly in contexts the place labeled datasets are already restricted. This development might necessitate new studying approaches tailor-made to data-constrained environments.
Actual-World Influence on Productiveness and Workforce
Maybe essentially the most thrilling improvement is AI’s tangible impression on human productiveness. Final yr’s AI Index was among the many first to focus on analysis displaying that AI meaningfully improves productiveness. This yr, follow-up research confirmed and expanded these findings—particularly in real-world office environments.
One such research tracked over 5,000 buyer help brokers utilizing a generative AI assistant [2]. The instrument elevated productiveness by 15%, with essentially the most important enhancements seen amongst much less skilled employees and expert commerce employees, who additionally boosted the standard of their work. Moreover, AI help helped staff be taught on the job, enhancing English fluency amongst worldwide brokers, and even enhanced the work setting—prospects have been extra well mannered and fewer prone to escalate points when AI was concerned.
Complementing these findings, Microsoft’s inside analysis initiative on AI and productiveness compiled outcomes from over a dozen office research, together with the most important recognized randomized managed trial of generative AI integration[3]. Instruments like Microsoft Copilot are already enabling employees to finish duties extra effectively throughout roles and industries. The analysis underscores that the impression of AI is best when instruments are adopted and built-in strategically—and that the potential will solely develop as organizations recalibrate workflows to take full benefit of those new capabilities.
Increasing Entry to Laptop Science Training
As AI turns into extra built-in into day by day life, laptop science training is extra important than ever. Encouragingly, two-thirds of nations now provide or plan to supply Ok–12 CS training, a determine that has doubled since 2019. African and Latin American international locations have made a few of the most important strides in increasing entry. Nevertheless, the advantages of this progress should not but common—many college students throughout Africa nonetheless lack entry to laptop science training attributable to primary infrastructure gaps, together with lack of electrical energy in colleges. Closing this digital divide is crucial to getting ready the following technology to not solely use AI, however to form it.
Our Shared Duty
At Microsoft, we view this second as a major inflection level—one which requires considerate motion as a lot as innovation. The speedy progress in AI brings monumental potential to enhance productiveness, clear up real-world challenges, and drive financial development. However realizing that potential requires continued funding in sturdy infrastructure, high-quality training, and accountable deployment of AI applied sciences.
To take advantage of this second, we have to help employees with studying new expertise and instruments to use AI successfully of their jobs. Nations and companies that put money into AI skilling will foster innovation and open doorways to extra folks to construct significant careers that contribute to a stronger financial system. The objective is obvious: to show technical breakthroughs into sensible impression at scale.
[1] “AI Index | Stanford HAI.” Accessed: Apr. 05, 2025. [Online]. Obtainable: https://hai.stanford.edu/ai-index
[2] E. Brynjolfsson, D. Li, and L. Raymond, “Generative AI at Work*,” The Quarterly Journal of Economics, p. qjae044, Feb. 2025, doi: 10.1093/qje/qjae044.
[3] S. Jaffe et al, “Generative AI in Actual-World Workplaces,” Jul. 2024, Accessed: Apr. 05, 2025. [Online]. Obtainable: https://www.microsoft.com/en-us/analysis/publication/generative-ai-in-real-world-workplaces/
