Editorial Team A new poll just dropped showing 72% of registered voters want AI regulated, but what’s really telling is that only 15% have any confidence the government is handling it. That’s a huge disconnect between what the public wants and what they think they’re getting. It’s this exact gap where the ‘Trump effect’ on AI regulation will make its mark, for better or worse.
Key Takeaways
- Look for 2026 executive orders on AI to dump broad ethics talk and laser-focus on domestic competitiveness and national security.
- Federal funding for AI in critical infrastructure is set to explode, likely hitting $10 billion by Q4 2026.
- Get ready for more lawsuits over AI policy, especially on data privacy and bias. I’m betting the Supreme Court takes up a big one by early 2027.
- Global cooperation on AI rules is going to fracture. Expect more one-on-one deals between countries instead of big multilateral treaties.
- Small and medium businesses (SMEs) are about to get hit with new AI compliance costs, and they’ll need real guidance from agencies like the Small Business Administration to survive it.
The Shifting Sands of Federal AI Investment: A 25% Increase in Defense Spending
You can always tell what the government’s real priorities are by following the money. For AI, the writing is on the wall. A 2026 GAO report confirmed that defense-related AI R&D funding shot up by 25% in 2025 over the previous year. This is a clear strategic pivot. All the talk from past administrations about ethical AI across society is being replaced by a hard focus on keeping a technological edge in defense and intelligence.
My read on this is simple: we’re shifting from trying to build broad ethical guardrails ahead of time to just funding reactive, mission-specific tools. That means less money for things like AI accountability frameworks in healthcare or consumer finance and a firehose of cash for autonomous systems and cybersecurity. This is the ‘Trump effect’ in action, a pragmatic, even hawkish, AI policy that puts national security first and lets the philosophical debates sort themselves out later. The conversation has changed from “AI for good” to “AI for strength,” which will completely alter how this tech gets built and used in the US.
Executive Orders as Policy Drivers: A 40% Rise in AI-Specific Directives
We’re seeing a 40% spike in AI-specific executive orders and presidential memoranda since early 2025 compared to the two years prior, a number that comes from a Brookings Institution analysis. This tells you the White House prefers to set AI policy with the stroke of a pen rather than going through Congress. These orders are hitting specific agencies, forcing them to quickly come up with rules for how they buy, assess risk, and manage data for their own AI systems.
Relying on executive orders is a clear strategy to sidestep the gridlock in Congress. It’s fast, sure, but it also creates policy on shaky ground that the next administration can wipe away overnight. It also keeps the power (and the conversation) inside the executive branch, cutting out a lot of public and expert input. If you’re a business or a researcher, what does this mean for you? It means you’re working through a policy field that can change without warning, forcing you to stay on high alert. Without real laws passed by Congress, we’re stuck in this cycle of uncertainty with companies scrambling to follow temporary rules. I just don’t see how this piecemeal approach to AI governance will eventually prove unsustainable. We need actual legislation, as messy as it is to pass, to get the stability that’s required for real innovation and public confidence.
“Alfozan had been employed as an engineer by OpenAI since July 2025. The complaint said he was educated in the US and has been a legal permanent resident since 2020.”
Public-Private Partnerships: A Stagnant 5% Growth in Non-Defense Collaborations
For all the talk about innovation, the numbers show something different: public-private partnerships for non-defense AI grew by a measly 5% year-over-year in 2025. According to a report from the National Artificial Intelligence Initiative Office (NAIIO), that figure is nothing compared to the boom in defense-related partnerships. The administration might be talking up American tech leadership, but the data shows they’re building it inside the government and with defense contractors, not by working with the wider private sector on civilian projects.
You’d think a push for national competitiveness would spark collaborations all over the place, but the data says no. The ‘Trump effect’ here looks more like an insulated strategy, where the government prefers to keep control and directly invest in its chosen areas. Maybe it’s about protecting IP and data security, or maybe it’s just a preference for a top-down command structure instead of messy partnerships. Regardless of the reason, the result is a bottleneck preventing government-funded AI breakthroughs from spreading into the broader economy. The dynamic collaboration everyone was hoping for just isn’t happening.
International AI Policy Alignment: A 15% Decrease in Multilateral Treaty Engagement
If you look at the State Department’s records, you’ll see the US backed away from new multilateral AI treaties in 2025, with engagement dropping 15%. At the same time, one-on-one talks with allies and rivals have picked up. The message is clear: the commitment to building a single set of global AI rules is fading.
This data shows we’re moving away from a single global playbook for AI regulation. The administration is choosing to cut custom deals that serve specific national or geopolitical goals instead of helping build a unified standard. We’re headed toward a fractured world for AI, where every region has its own set of rules, which will be a nightmare for international companies trying to navigate a patchwork of regulations, driving up compliance costs and slowing down cross-border projects. I think this is a huge mistake. AI is a global technology that needs global answers, and pulling back from the main table just makes things more complicated and unpredictable for everyone involved.
The Regulatory Burden on SMEs: An Expected 30% Increase in Compliance Costs
We don’t have hard numbers yet, but industry analysts are already predicting a 30% jump in AI-related compliance costs for SMEs by the end of 2026. A recent NFIB report connects this projection to a perfect storm of new data privacy rules, demands for algorithmic transparency, and tougher liability for AI systems. Even when executive orders aren’t aimed at SMEs, they create a ripple effect that forces smaller companies to spend a ton on lawyers, tech audits, and new internal workflows.
This is where things get real for most of the economy. Big companies have the cash and lawyers to handle this, but these new costs could crush a smaller business. It’s ironic, an administration that pushes for deregulation elsewhere is now creating a complex web of new AI rules. Without straightforward guidance and maybe some financial help, a lot of smaller businesses will either avoid AI or get it wrong, making the gap between the tech giants and everyone else even bigger. It’s a perfect case of unintended consequences, where the push for national strength accidentally smothers innovation from the bottom up.
So, the ‘Trump effect’ on AI regulation is a mixed bag defined by a heavy focus on national security, fast-tracking policy through executive orders, and a go-it-alone approach internationally. For businesses and policymakers, the takeaway is clear: get ready for a fast-changing and fractured set of rules. You’ll need to be adaptable and pay very close attention to where the political winds are blowing.
What’s the main focus of current AI regulation?
It’s all about national security and economic competition. The policy is being pushed through executive orders targeting defense and critical infrastructure, not through broad laws.
How are executive orders changing AI policy?
They’re the main tool being used. They give direct orders to federal agencies about how to buy and manage AI, which makes policy change fast but also means it’s unstable and could be reversed easily.
What’s happening with public-private AI partnerships?
They’ve stalled out for anything not related to defense. The current approach favors government control and direct investment in key areas, not broad collaboration with private companies.
How’s the US handling global AI rules?
It’s backing away from big, multi-country treaties and instead making one-on-one deals. This is likely to create a patchwork of different rules around the world instead of a single standard.
What AI compliance problems will small businesses face?
They’re looking at a big jump in costs. New rules on data privacy, algorithmic transparency, and liability mean they’ll have to spend more to stay compliant, which is a huge burden without clear support.
