New findings from the Stanford AI Index reveal a more uneven picture of public sentiment and labor market outcomes than previously thought, as AI investment surpasses $1 trillion.
“Follow the money” is a phrase that has endured for good reason — money reveals priorities far more than rhetoric can. And in the case of artificial intelligence, the money underscores an economic ambition of extraordinary scale.
Thus far in 2026, global corporate investment in AI has surpassed $1 trillion, already exceeding the entire 2025 total by 46%. This is a significant amount of capital being committed to a technology whose consequences we are still learning how to measure. AI’s economic and societal effects are unfolding in real time, from shifts in talent migration to emerging evidence in labor markets and the expanding physical infrastructure that communities are being asked to accommodate.
As we prepare the 2027 AI Index report from the Stanford Institute for Human-Centered Artificial Intelligence, we periodically refresh our annual and year-to-date datasets. Several previously unreleased findings offer a glimpse into what we may need to examine more closely — last year, we documented a widening gap between capability, deployment, and readiness as the institutions and frameworks responsible for evaluating and responding to AI struggled to keep pace.
But another, perhaps more urgent, question is emerging: Is the future that is being financed the same future people expect, experience, or want for themselves? Public sentiment is turning out to be just as jagged as AI’s technical frontier. In every country surveyed, more people expect AI to eliminate jobs than create them. In the United States, 60% of adults say they would feel uncomfortable with a new data center in their area, including majorities in both political parties. However, globally, a majority of survey respondents still believe AI’s benefits outweigh its drawbacks.
Concerns about AI’s implications for employment are important to consider against the emerging labor market evidence. Data from the Stanford HAI Digital Economy Lab’s AI Economic Indicators show that employment declines among younger workers in AI-exposed occupations have continued into 2026, particularly in customer service. A new finding broadens the concern: Declines have deepened even in occupations characterized by AI use that supports rather than replaces human work, including roles such as marketing and IT managers. While these patterns do not establish causality, they raise important questions about how AI’s economic effects may differ across the workforce.
So if we follow the money, we see a scale of investment that signals considerable confidence in future economic value. But if we follow public sentiment and labor markets, the confidence is less settled and the acceptance far more mixed. This may be a technological frontier, but the experience of its diffusion is distinctly human and far from uniform.
Sha Sajadieh is the AI Index editor. The Index provides unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. The next AI Index will be released in April 2027.
