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July 25, 2025

The White House Has a New AI Plan. Your Company Needs One Too.

The White House chose speed over sight. Smart companies will choose both.
Lexi Reese, Lanai CEO & Co-Founder
Thought Leadership

The most telling details in the White House's new AI Action Plan are not its specific ideas, nor what it prioritizes. It's what the document designed to "win the AI race" eliminates.

In a word: guardrails.

‍The Race We're Actually In

The plan explicitly frames AI as a geopolitical competition. "Winning the AI race is non-negotiable," administration officials declared. The goal: beat China by removing every regulatory friction point that might slow American companies down.

This urgency makes more sense given what happened earlier this year. The Chinese company DeepSeek shattered core assumptions about AI leadership in February when it burst on to the scene. While OpenAI spent $100 million creating ChatGPT, DeepSeek built comparable capability for what it said was a fraction of the cost, $5.6 million. And it did so using hardware everyone assumed was inadequate. Nvidia lost $589 billion in market cap in a single day.

DeepSeek freaked out Washington and Silicon Valley alike. It exposed an uncomfortable question. If we're leading in AI, why are we spending 20 times more to build the same thing? The White House's response is to double down on speed and remove every possible barrier.

‍Racing Blind

What the plan misses, though, is that we're already governing blind while AI transforms everything around us.

Government can't even see AI usage in its own processes. Researchers at the National Institute of Health discovered researchers submitting dozens of AI-generated grant applications that reviewers couldn't detect. If government can't see AI usage in its own processes, how can it possibly govern AI in the broader economy?

Meanwhile, the plan creates new political compliance requirements for federal AI purchases—systems must be "free from top-down ideological bias" and can't mention concepts like systemic racism or unconscious bias. This isn't anti-bias governance; it's pro-bias enforcement. We're requiring AI to pretend discrimination doesn't exist while ignoring actual algorithmic bias in hiring, lending, and healthcare that hurts real people.

The bottleneck isn't permission to test AI. It's that we're governing blind while AI transforms everything around us. We're trying to race China while, at the same time, we can’t even see the track we’re running on.

Meanwhile, American companies face the same visibility crisis. Most Fortune 500 companies are regularly discovering employees using 20+ AI tools leadership never approved. Gallup shows 40% of workers use AI while only 22% of companies have strategies.

As Lexi Reese, Lanai's CEO, put it in Politico: “Companies aren’t held back by lack of permission to test AI. They’re already deploying it without oversight.”

‍What We're Really Competing Against

China's advantage isn't just speed—it's systematic efficiency and coordination.

DeepSeek proved they can build frontier AI for a fraction of our costs while we debate regulatory frameworks. Their oversight lets them see and steer development strategically.

Europe's building systematic measurement capabilities through its own AI Act, creating standards that companies master first then export globally as requirements.

America's choosing pure velocity while abandoning the governance capacity that could steer that speed effectively. The plan threatens to cut federal funding from states that regulate AI and emphasizes deregulation over building institutional expertise.

‍The Governance Vacuum

Without guardrails, responsibility falls to companies and citizens. The infrastructure for responsible AI governance exists. You just have to build it yourself. Here’s how you do it:

‍Start with visibility: Most organizations can't govern what they can't see. Before writing AI policies, understand what tools teams actually use, what value they create, what risks they generate.

‍Build accountability: Stop counting AI deployments and start measuring real impacts. Track productivity gains, risk exposure, and outcome patterns.

‍Prepare for whiplash: Today's hands-off approach won't last. When the inevitable AI incident occurs, regulation will return with vengeance. Companies with robust internal governance will weather that transition; those flying blind won't.

‍Winning the Right Race

The White House is betting that moving fast and breaking things scales to civilizational infrastructure. That is the same thinking that gave us the social media mental health crisis and the opioid epidemic. DeepSeek exposed a fundamental flaw in this approach. We might not just be breaking oversight mechanisms: we might be breaking the bank to build inferior systems.

Companies don't have to make Washington's bet. They can compete on building AI that people actually trust and want to use. They can turn responsible governance from compliance cost into competitive advantage.

Real AI leadership means governing with eyes wide open: seeing what tools create value, what risks cross red lines, and what capabilities actually serve human needs rather than just corporate growth.

We can win the AI race. But first we need to make sure we can see where we're going—and that we're not just running in expensive circles.

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