At a recent American Enterprise Institute event, a panel of experts dissected the sweeping AI Action Plan released by the Trump administration just a few days earlier. Together, they unpacked the plan’s ambitious goals, its underlying approach, and potential roadblocks that could hinder implementation.
Understanding the plan requires understanding the moment. White House AI advisor David Sacks likened it to President John F. Kennedy’s declaration of the space race. Now, as then, the stakes are global. President Trump declared that America is in an AI race—one that will shape the future of civilization. “Whether we like it or not,” he said, “we are suddenly engaged in a fast-paced competition to build and refine this groundbreaking technology.” He pledged that the US would do “whatever it takes” to lead, stating unequivocally: “America is the country that started the AI race, and as President, I’m here today to declare that America is going to win it.”
Just days later, China released its own sweeping national AI strategy centered on massive infrastructure investment, global AI partnerships, and aggressive talent development. It highlighted just how fiercely the competition is escalating on the world stage.
We assembled a panel of bipartisan experts from industry and policy to help unpack the plan and make sense of the rapidly evolving AI landscape:
- Miles Brundage served as the former Head of Policy Research at OpenAI and founder of the AI Verification and Evaluation Research Institute (AVERi), which works to ensure frontier AI systems are continuously, independently, and credibly evaluated against shared safety and security standards.
- Molly Kinder is a Brookings Senior Fellow bringing years of experience at the intersection of tech and equity, leading a major research initiative on how generative AI is reshaping work.
- Will Rinehart is a Senior Fellow at AEI explores the political economy of emerging technologies, analyzing how laws and regulations—from the CHIPS Act to agency rulemaking—shape innovation, AI deployment, and economic growth.
Here are some of the key takeaways from the discussion.
Overall Reactions: The panel praised the plan’s ambition—calling it “bullish” and “directionally right”—but flagged major concerns around implementation. Key risks: limited federal tech talent, fragmented agency capacity, and inadequate funding to meet the plan’s urgency.
Infrastructure as National Security: AI success depends on physical infrastructure. Will Rinehart emphasized that datacenters, chip fabs, and energy grids are no longer just technical assets—they’re strategic levers in geopolitical competition. The plan rightly prioritizes permitting reform to accelerate buildout.
Auditing Frontier AI, A Middle Way Forward: Miles Brundage underscored the push for independent third-party AI evaluations as a critical innovation. Rather than defaulting to industry self-regulation or heavy-handed government control, the plan champions a financial audit-style model for safety and security assurance. The goal is rigorous, frequent, and independent evaluation.
Workforce Impact. Molly warned of a coming labor shock: Cognitive automation will inevitably bring winners and losers, disrupt some occupations (especially those held by women), and outstrip the current capacity of educational and workforce development systems. Panelists urged a reimagining of the safety net, emphasizing the need for innovative job transition models and genuinely worker-centered strategies that go beyond traditional skills training to address displacement and evolving hiring challenges.
Open Weighted as a Strategic Priority: The AI Action Plan decisively supports open-source and open-weight AI models. This represents a significant shift away from the Biden-era caution and positions US open-weight models as a counterweight to China’s strategy.
Kids Left Behind in the AI Safety Debate: Despite rising concerns and debate around AI’s impact on children, especially through chatbots and AI companions, the plan is nearly silent on any aspect of child safety. There is consensus on the need for better, more timely research and stronger engagement with civil society and academia to understand and manage these risks as AI technologies permeate everyday life and society.
The Vision Is Bold, Now Comes the Hard Part: The panel repeatedly noted that, although the Action Plan is ambitious, real challenges remain in implementation, given the potential lack of technical talent in agencies, resource limitations, and the speed of execution. Much will depend on how agencies implement the plan, the engagement with a broader range of stakeholders, and the ability to adapt as new AI risks and opportunities emerge in practice.
The AI Action Plan represents an important step toward strengthening American leadership in AI innovation. Achieving the plan’s promise will demand more than federal leadership. Governors must lead, aligning state investments and priorities with national goals; frontier AI labs hold the technical expertise to make safety and transparency real; civil society must push to ensure the benefits of AI are broadly shared and grounded in public trust. Only through this kind of deep, cross-sector partnership can the US turn vision into sustained advantage.
We’ve created a public NotebookLM featuring the full AI Action Plan and related Executive Orders from the Trump Administration. Use it to explore the administration’s emerging AI policies—ask questions about specific directives, get summaries of key sections, or clarify core concepts. Please note that NotebookLM is still experimental, so it’s a good idea to double-check any responses it provides.
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