Artificial intelligence is no longer a technology on the horizon. It is here, operating inside organizations across every sector, reshaping how decisions are made, how services are delivered, and how risk is managed. Yet many leadership teams — including those at the highest levels of government and enterprise — are still approaching AI as a future problem rather than a present responsibility.
That gap between AI’s operational reality and leadership’s readiness to govern it is one of the most consequential challenges facing organizations today. Closing it requires something more than a technology strategy. It requires a leadership strategy.
What Leaders Are Getting Wrong
The most common mistake I observe is treating AI governance as a technical problem to be delegated downward. CIOs and CTOs are handed AI responsibility while boards and executive teams remain largely uninvolved in the strategic decisions that will define how AI shapes the organization. This is a structural error with real consequences.
AI decisions are not purely technical. They are decisions about risk tolerance, about organizational values, about the relationship between automation and human judgment. Those decisions belong at the leadership level — and they require leaders who are conversant enough with AI to engage meaningfully, even if they are not engineers themselves.
“AI decisions are not purely technical. They are decisions about risk tolerance, about organizational values, about the relationship between automation and human judgment.”
The Government Context
In the federal government, the challenge carries additional weight. Public sector AI deployments affect citizens, critical infrastructure, and national security in ways that demand a higher standard of accountability. During my tenure as CIO at the Department of Energy and the EPA, I watched agencies struggle to keep pace with the rate of AI development — not for lack of talent, but for lack of governance frameworks capable of operating at that speed.
The policy environment is evolving rapidly. Executive orders, congressional activity, and agency-level AI guidance are all shifting simultaneously. Organizations that engage proactively with this environment — rather than waiting for regulatory clarity — will be better positioned to deploy AI responsibly and at scale.
What Boards and Leadership Teams Should Be Asking
The questions I encourage boards and executive teams to prioritize are not about specific tools or vendors. They are about organizational readiness. What AI capabilities are already deployed in our organization, and are we governing them adequately? What decisions are we comfortable automating, and which require human review? How are we managing the data quality and security implications of AI at scale?
These are not questions that require technical expertise to ask. They require strategic clarity about what the organization values and what risks it is willing to accept. Leadership teams that engage with those questions early will be far better prepared for the AI decisions that are inevitable in the years ahead.
The organizations that will lead in this environment are not necessarily those with the most advanced AI capabilities. They are the ones where leadership has taken the time to understand what AI can and cannot do — and has built the governance structures to deploy it with confidence.