America’s AI Action Plan: Fast, Fierce—and Missing the Middle

On July 23, the White House released America’s AI Action Plan, a sweeping document that outlines a vision for U.S. AI leadership—heavy on speed, light on guardrails. It calls for unleashing innovation through deregulation, accelerating infrastructure for data centers and chips, and launching global AI alliances. Tech titans applauded. But as someone who has spent decades helping smaller companies navigate complex systems and disruptive change, I couldn’t help but pause.

This is not a blueprint for AI readiness—it’s a launchpad for AI supremacy. And while bold ambition has its place, I believe it's fair—and necessary—to ask: at what cost, and to whom?

The Velocity Trap

There’s no question the global AI race is heating up. Countries are vying not just for technological dominance, but also for economic and geopolitical leverage. The U.S. plan is unmistakably aimed at staying ahead of China, with provisions to fast-track domestic chip production, cut through permitting barriers, and create AI export packages for allied nations.

But in its quest for velocity, the Action Plan makes a dangerous assumption: that speed is synonymous with progress.

We’ve seen this movie before. Prioritizing scale and speed over thoughtful governance can leave smaller businesses, workers, and communities scrambling to catch up—while a few powerful players widen the gap.

Regulatory “Relief”—For Whom?

One of the plan’s most controversial components is its proposal to tie federal AI funding to a state’s willingness to loosen its own regulations. In other words, if your state prioritizes civil rights, labor protections, or consumer safeguards around AI, it could be penalized.

That’s a worrying precedent. It centralizes power, shifts the balance away from democratic deliberation, and creates an uneven playing field for communities trying to protect their most vulnerable.

It’s also telling that the plan contains no mention of antitrust measures or transparency mandates for large AI providers—despite bipartisan concerns about the consolidation of power in the tech sector. Startups and SMBs may be promised “streamlined procurement,” but when infrastructure and investment dollars flow disproportionately toward mega-corporations, the imbalance speaks louder than the policy language.

Ideological “Neutrality”—Or Soft Control?

Another buried headline: Federal AI systems and contractors will be required to ensure “ideological neutrality” in their outputs. It sounds reasonable in theory—AI models should not impose biased worldviews. But in practice, this opens the door to subtle but dangerous forms of control.

Who decides what constitutes “neutral”? What happens when neutrality becomes a proxy for suppressing discussions of race, gender, labor, or environmental justice in algorithmic systems?

This is not a hypothetical risk. We've already seen heated debates over whether AI models should be allowed to weigh in on climate change, reproductive rights, or historical injustice. Mandating neutrality—without transparent oversight—could be the quietest form of censorship.

What’s Missing: People

To its credit, the plan does acknowledge AI’s impact on jobs. It proposes workforce hubs, pilot reskilling programs, and tax incentives for companies that invest in training. But there’s no consistent, enforceable commitment to worker protections, minimum standards for displacement response, or meaningful inclusion of communities most at risk.

For SMBs, there’s similarly little clarity. The procurement language is vague. The R&D support is broad. And while infrastructure investment sounds great, smaller firms won’t benefit from new chip fabs in Arizona if they can’t afford compute resources or navigate complex compliance mazes.

What’s needed isn’t just innovation infrastructure—it’s adoption infrastructure. Guidance, access, and support to help underfunded players make sense of the technology without falling behind.

Strategic Takeaways

As a strategist, I’m not opposed to ambition. But ambition without inclusion becomes extraction. If we truly want AI to serve the public good, here’s what we need to press for next:

• Distributed Governance: Let’s not punish states that want to lead responsibly. Instead, invite them to co-create smarter standards.
• Ethical Transparency: Bias audits and clear criteria for what “neutrality” means should be non-negotiable.
• Inclusion Beyond Industry Giants: Procurement reform must favor diverse vendors, not just repeat contractors.
• Civil Society Input: Where is the voice of educators, healthcare workers, or frontline communities? We can’t govern AI with only tech CEOs at the table.

Closing Thought

The Action Plan is not all bad. It signals that AI is now viewed as infrastructure-level policy, not just tech policy—a shift I’ve long advocated for. But we can’t let the urgency of competition override the dignity of care.

If you work in a startup, lead a nonprofit, or support underserved communities, you deserve a voice in this conversation. This is your invitation. Let’s make sure the future of AI isn’t just powerful—but also just.

~Wendy

"America's AI Action Plan" from the White House: https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf

Wendy Jameson is the founder/CEO of Potentiate and author of 3G4AI. She advises organizations on AI strategy, governance, and responsible innovation.

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