For Many Schools, Implementing AI Has Become a Minefield. How Congress Can Help
By Ji Soon Song, Michael Ham, Sabia Prescott
Weeks into the new school year, artificial intelligence is already in the hands of students and teachers — whether school systems are ready for it or not. The rapid surge in classroom adoption has vastly outpaced district readiness, leaving school leaders scrambling to build guardrails in real time. While Congress and the Trump administration remain focused on macro-level AI governance, federal leaders have left states and local school systems without the guidance or funding needed to navigate this transition. In the resulting policy vacuum, students and educators are caught in the middle as state legislatures weigh hundreds of proposed AI policies and state education agencies race to issue updated guidance.
The scale of youth adoption is vastly outpacing district capacity. A June 2026 report found more than 4 in 5 teens have used AI tools, with over two-thirds reporting regular use. Yet, as policy experts emphasized at a recent Capitol Hill briefing hosted by the American Innovation Policy Forum, school districts still bear the sole burden of vetting and deploying these tools — with virtually no evidence linking them to improved educational outcomes or to the development of essential skills like critical thinking, media literacy and problem-solving.
For already under-resourced schools, basic implementation has become a minefield. Supporting teachers, reassuring parents and vetting vendors now require evaluating complex AI safety, privacy and security risks. These technical demands go far beyond standard software procurement, leaving districts to navigate the risk alone.
Ongoing congressional debates regarding AI governance, particularly with the 2026 midterm and 2028 general elections approaching, highlight a unique window of opportunity for policymakers to champion meaningful, local-first policy. Rather than top-down mandates, lawmakers must invest in community-level readiness. A forthcoming “Big Bets” white paper from the A-I Policy Forum provides a roadmap, offering five concrete recommendations that outline how targeted federal resources can help schools manage implementation risks and harness AI to drive deeper learning, critical thinking and workforce readiness.
First, establish national technical assistance hubs. Districts need a clear map of an increasingly complex technical environment. A national network of dedicated technical assistance centers could provide practical guidance on procurement, implementation and student privacy, ensuring that schools are not left to navigate commercial market pressures in isolation.
Second, create regional pilot programs. Communities need designated spaces to explore new tools without turning classrooms into unvetted testing grounds. Regional piloting centers with strong safety and ethical safeguards would allow schools and researchers to evaluate AI tools, measure real learning outcomes and establish best practices before software is adopted at scale.
Third, help integrate foundational AI literacy across core curricula. A basic understanding of AI cannot remain an optional elective restricted to advanced computer science tracks. Federal support should help states embed digital literacy and algorithmic critical thinking across standard subjects, equipping all students to evaluate emerging tools responsibly and recognize their limitations.
Fourth, modernize federal funding streams. To sustain these efforts over time, Congress must update federal programs designed to support district-wide technology adoption. Reauthorizing and modernizing the Enhancing Education Through Technology program would provide predictable funding for state and local agencies to manage ongoing professional development, privacy safeguards and evidence generation.
Finally, launch targeted innovation grants to reimagine classroom instruction. Ambitious competitive grants can enable pioneering districts to reimagine instruction entirely. By funding schools eager to explore novel, AI-enabled learning models, federal leadership can spur true innovation in classrooms rather than simply layering new technology onto outdated routines.
The economic case for acting now is as urgent as the educational imperative. By 2030, up to 65% of workforce skills are predicted to shift, moving the job market from basic digital literacy toward advanced human-AI collaboration, critical analysis and data-driven decision-making. While competitors like China and the European Union are already pursuing deliberate approaches to preparing the next generation, the United States cannot afford to treat K-12 AI readiness as a collection of disconnected, under-resourced experiments.
The coming school years do not have to be marked by uncertainty and confusion. By providing targeted federal funding and technical infrastructure, Congress can empower states, districts, educators and parents to shape AI instruction on their own terms and ensure American K-12 education serves as the cornerstone of America’s long-term technological leadership.
About the Authors: Ji Soo Song, Michael Ham, Sabia Prescott, and are educators, policy leaders, and Big Bets in AI Policy Fellows at the A-I Policy Forum, A non-partisan effort established to help define a new American model for AI governance that ensures safety, unlocks broad-based prosperity, and gives people the power and agency to shape how technology impacts their daily lives.
Michael Ham is a policy implementation leader and former middle school math teacher who helps K-12 systems turn emerging technology into sustainable practice.
Sabia Prescott is a K-12 state policy expert focused on educational equity and helping leaders navigate the risks and opportunities of AI.
Ji Soo Song is an educational technology policy leader and former advisor at the U.S. Department of Education who focuses on digital access, safe AI integration, and student-centered learning.
