Stanford's AI Index Exposes A School Crisis

When Stanford's Institute for Human-Centered AI released its 2026 AI Index Report on April 13, the headlines mostly went to the model benchmark battles, the $581.7 billion in global corporate AI investment, and the data center power numbers. Buried in chapter seven, however, is the finding that should be on the desk of every school leader.

Four in five U.S. high school and college students now use AI for schoolwork. Data is similar in the UK. Only 6% of teachers say their school's AI policies are clear.

That is not a guidance gap. That is an institutional readiness failure and it is happening right now, while the systems built to support teachers continue to lag behind the technology students are already using every day.

A few weeks ago I working with a school on the upper east side of Manhattan and their survey of their middle and hig school students found that 100% were using AI.

The Numbers That Should Reframe Our Efforts

The Stanford report, produced in collaboration with the Kapor Foundation, the Computer Science Teachers Association, and the Expanding Computing Education Pathways Alliance, is now in its ninth edition and remains one of the few comprehensive AI datasets not produced by an organization with a financial stake in the outcome.

Its findings on schools are stark. Estimates of student AI use for schoolwork range from 50% to 84%, drawing on data from the College Board, RAND, and the Center for Democracy and Technology. High school students most often use generative AI for conducting research, editing essays, and brainstorming - three activities that sit at the heart of how schools have traditionally measured learning.

Yet only about half of middle and high schools have any AI policy at all. Of those that do, just 28% permit AI use in some circumstances, while 22% prohibit it. Forty-seven percent of students said they have wanted to use AI for schoolwork but were unsure whether it was allowed.

A separate, independent survey from RAND released in September 2025 reached the same destination by a different route. Researchers found that 54% of students and 53% of English language arts, math, and science teachers were using AI for school-related work by spring 2025. That was a jump of more than 15 percentage points in roughly a year. Yet over 80% of students reported that their teachers had not explicitly taught them how to use AI for schoolwork. Only 34% of teachers said their school had policies on AI use related to academic integrity.

When two of the most rigorous independent studies in the field arrive at the same finding, school leaders no longer have the option of waiting for clarity to emerge.

What Most Coverage Got Wrong

Most reporting on the AI Index has framed this as a story about students racing ahead while schools fall behind. That framing is incomplete, and it lets the wrong people off the hook.

The deeper finding in chapter seven is that the responsibility for AI policy is being pushed almost entirely down to local education agencies. As of January 2026, in the US, 30 states have issued some form of AI guidance, but according to research from the Expanding Computing Education Pathways Alliance cited in the report, state-level guidance is largely nonbinding and decentralised. Most states are relying on existing federal frameworks like the Children's Online Privacy Protection Act and FERPA rather than issuing AI-specific mandates. Only five states have allocated specific professional development funding for AI education.

The April 2025 federal Executive Order 14277, "Advancing Artificial Intelligence Education for American Youth," created a White House AI Education Task Force and a Presidential AI Challenge. But the order's actual implementation depends on discretionary grants, public-private partnerships, and existing teacher preparation pathways. As the Stanford report notes, AP Computer Science, which is one of the most common pathways to advanced computing in U.S. high schools, does not include AI-specific content.

What that means in practice is a teachers in very different contexts are being asked to figure this out on roughly the same timeline, with vastly different resources. The RAND data shows the consequences. Teachers in higher-poverty schools are less likely to use AI, and principals in the highest-poverty schools are less likely to receive AI guidance. This is a divide that, as RAND researchers warned in coverage of their findings, risks turning AI rollout into another driver of educational inequality.

Three Things Educators Can Do Now

Sitting with the data does not change classrooms. Acting on it does. Three concrete moves are within reach of most school leaders before the summer break.

1. Write a one-page AI policy that students can actually understand.

The Stanford data shows the issue is not just the absence of policy but the absence of clarity. Only 36% of students described their school's policies as extremely clear. A workable policy answers four questions in plain language: when students may use AI, when they may not, how they should disclose AI use when permitted, and what happens if they get it wrong. Schools that have moved fastest on this have one thing in common, according to the report: they treat AI as something to be taught about, not just something to be governed.

2. Train teachers on prompting before training them on tools.

RAND's 2025 panel data found that the fastest-growing AI literacy skill among American workers, measured by LinkedIn profile data, is AI prompting. Yet most school AI training continues to focus on specific products, this might be a particular chatbot, a particular grading tool, a particular lesson planner. Tools change every quarter. Prompting is the underlying competence. Schools that invest in the durable skill rather than the latest product will see the return on professional development hold up across budget cycles.

3. Replace the cheating conversation with a thinking conversation.

The Stanford report notes that students themselves worry about diminished critical thinking and weakened academic skills as much as their teachers do. A separate RAND study published in March 2026 found that nearly seven in ten middle and high schoolers are concerned AI use is eroding their critical thinking. The researchers proposed a useful distinction: AI use that involves cognitive offloading versus AI use that produces cognitive augmentation. Translating that distinction into specific assignment design is more useful to a teacher than another policy memo.

The Counter-Argument Worth Taking Seriously

Not everyone agrees that schools should be moving faster. Some experienced educators argue that the absence of clear AI policy is, paradoxically, protecting students. South Korea's experience, also documented in the Stanford report, is instructive here. The country launched AI textbooks in primary schools in March 2025 and reversed course within months after parent and teacher pushback.

The case for caution is not without merit. The honest reading of the data, however, is that students are not waiting for a verdict. The decision schools face is not whether AI enters their classrooms but whether teachers shape how it enters or whether students do it on their own.

Where This Goes Next

The 2026 AI Index makes clear that the gap between what AI can do and how prepared we are to use it well in classrooms is widening, not closing. The good news is that it is closeable, but only at the level of individual schools and districts willing to do the work.

The 6% of teachers who say their school's AI policies are clear didn't get there by waiting.