We recently wrote that America's schools don't have a technology problem, they have a leadership problem. The organizations that will succeed with AI are the ones with leaders who understand that this is fundamentally about organizational change, systems thinking, and the courage to abandon what's comfortable for what's necessary.
We know what happens when we let technology race ahead of strategy. We lived through it during the pandemic, and students are still paying the price of unforeseen consequences that came with AI’s rapid adoption.
We must not make that mistake twice.
Here's the hard pivot K-12 leadership needs: not another pilot, not another purchase, and not a new shiny title. There are five moves only leaders can make at both state and district levels.
Before you craft an AI vision, develop strategy or purchase anything, engage your community in defining what problems AI should address. And make this engagement continuous, not episodic.
In New York, the Capital Region BOCES is taking this approach at the regional scale. They're bringing together local districts, higher education and workforce partners not to discuss the latest AI tools, but to align around shared challenges and goals and to emerge with a regional framework.
States can lead the way by building real structures for regional dialogue and collaboration. They can create spaces where districts learn from one another, studying what works, what doesn’t and why. And they can demand transparency: where AI is being used, for what purpose, and with what results.
Districts can follow suit. The same approach can work locally, adapted to each community’s needs.
2. Stop piloting without purpose.
K-12 is great at launching "cool" pilots and terrible at institutionalizing what works. We’re prone to the shiny-object syndrome, rushing something into classrooms simply because it’s new. And too often, even our pilots lack research, clear goals, or measures of success.
We need to measure both the human experience and the outcomes: Are students mastering content? Are teachers freed up to do higher-value work? Is the tool making a difference where it matters most?
States can advance this approach by providing clear frameworks for what rigorous piloting looks like and creating mechanisms for districts to share results transparently.
3. Invest in people before platforms.
Think about AI integration first from a leadership lens. Make sure leaders have personal experiences with AI. The superintendent, state chiefs, cabinet members, principals and others in the organization need to use AI personally and understand its benefits and limitations to lead its adoption.
Build leader and teacher capacity first, then have the tools follow. States have a critical role here: integrating AI literacy into teacher preparation programs, updating licensure requirements, and supporting research and professional learning at scale.
4. Teach students to work with AI and to manage change.
AI literacy experts increasingly warn that the way people communicate with AI determines the quality of what they get back. Vague prompting produces vague results. Thoughtful, specific prompting yields powerful outcomes. Yet almost no one, outside of wealthier and well-resourced schools, is teaching students to effectively communicate with AI.
Just like every other achievement gap in education, this one will fall along predictable lines of wealth, race and class. States can lead by incorporating AI literacy into curriculum frameworks and provide transparency around better tools for safe and effective use. Districts can ensure every student has access to quality AI literacy instruction, and analyze AI skill growth across employee roles in their schools and divisions.
Don't let AI literacy be a privilege. Make it a guarantee.
5. Earn trust with radical transparency.
Use AI to accelerate what matters most to your community and be clear about the ethical guardrails. Think about how the tool positively affects operations, and what operational pieces must be in place to embrace it.
Create an "AI report card" that shows impact on learning, teacher workload and student experience. Post plain-language data policies, opt-in choices and rapid response procedures if something goes wrong. Be clear about what must always remain human, and communicate this clearly and often.
States can model continued community engagement and transparency by publishing their own AI use cases, evaluation frameworks and progress metrics, creating a culture of openness that local districts can emulate. Make this dashboard part of your accountability rhythm so families and educators can see progress, understand where AI is moving the needle, and raise concerns early.
Lead With Intention.
If you're a district or state leader, do these five things, publish your plan, and invite your community into ongoing dialogue. Then measure what matters and adjust. That's how you avoid past mistakes, rebuild public trust through sustained transparency and community engagement, and make AI work for the people at the heart of every school: students and educators.
The clock is ticking. And the students, depending on us to get this right, can't afford to wait while we figure it out.
Dr. Julia Rafal-Baer is the co-founder and CEO of ILO Group, a women-owned education and policy strategy firm, and the founder of Women Leading Ed, a national nonprofit network for women in education leadership. She is also a member of the National Assessment Governing Board.
Dr. Scott Muri served as a superintendent for 10 years at two large Texas school districts (Spring Branch ISD and Ector County ISD) and is now the CEO of innovations in leadership and superintendent in residence at the policy firm ILO Group.
