AI Regulation Is Coming—Will It Accelerate Innovation or Cement Monopolies?

TL;DR: Good AI regulation unlocks innovation. Bad regulation locks it down. The community cannot just watch it happen, and I am asking everyone to talk about it more.

Quick disclaimer: I’m not a policy expert. At GMI Cloud, we focus on building the best tech stack for scalable, fast, and safe AI.

But I know this: just focusing on the infrastructure isn’t enough. The rules around AI will shape who builds, what gets built, and how safely it scales. The future of our industry and community won’t be defined by model quality but by who controls the rules. Good regulation creates a thriving ecosystem. Bad regulation locks us into monopolies.

So why isn’t this conversation front and center? Regulation is inevitable. The real question isn’t if but how. Will new rules empower open innovation and fair competition? Or will they entrench incumbents and lock others out?

Here’s what I want the AI community to think about:

• What regulation outside of tech—aviation checklists, financial disclosures, biotech protocols—might be useful to apply to our industry?
• And if you had to write a rulebook that guaranteed a monopoly, what would it include?

These aren’t academic hypotheticals. We need to answer them now before someone else — someone who may not understand this space — does it for us. That second question should feel uncomfortable as it inevitably expects you to inspect how we measure up. In some ways, I worry we’re already sliding in that direction.

If you know, you know.

AI is already changing how we build, govern, and decide. And history is clear: without thoughtful frameworks, markets drift toward concentration. If builders stay silent, others will set the rules. The idea of regulation is not a threat, but those who want to play the regulation game so that anything they build wins, are.

That’s why engineers, founders, and product teams must engage. Good regulation gives us room to run and compete fairly. It defines the lanes. It builds trust. It sustains momentum. Capitalism is all about competition, and no competition is interesting if it's not fair.

At GMI Cloud, we believe good regulation should be:

• Outcome-oriented – focused on transparency and safety
• Tech-agnostic – not limited to specific models or approaches
• Flexible and evolving – able to adapt to a fast-moving field

Regulation should protect the public without stifling experimentation. It should reward openness, not abuse. And it should support the open-source and small teams driving much of AI’s real progress.

That’s why we’re building toward open-spec inference runtimes, modular APIs, and transparent pricing as foundations for a healthy, inclusive ecosystem.

Insider insight: At GMI Cloud, we’ve seen small teams move from prototype to production 4x faster when standards are open and infra isn’t locked behind proprietary APIs. That’s the environment we want regulation to protect.

Best- vs. Worst-Case Futures for Our Community of AI Builders

In the best-case scenario: AI regulation fosters a vibrant, open, and competitive ecosystem. Builders have the freedom to choose the best tools without fear of lock-in. Infrastructure is modular. APIs are accessible. Compliance is clear and achievable—even for small teams. Startups can compete on merit, and auditing tools are available to all.

In the worst-case scenario: Regulation entrenches control in the hands of a few. Monopolies own everything—from the foundation model to the deployment pipeline. APIs are closed off. Switching providers is prohibitively expensive. Compliance becomes a barrier instead of a baseline. Open-source dries up. Innovation slows because new players can’t break in.

This contrast isn’t hypothetical. The decisions we make today are already steering us in one direction or the other. As an example, I made a firm decision not to charge ingress or egress fees despite people telling me I'm leaving money on the table and will risk higher churn. Some have abused this freedom; that's fine, they can go. I want my partners to stay because they love what GMI Cloud has to offer, not because of sunk-cost fallacy and disgusting lock-in practices.

Ask yourself: Are we moving toward openness, modularity, and access—or toward closed systems, regulatory gatekeeping, and dominance by a few?

Red Flags to Watch For:

• Rules that only benefit the largest players
• Drop-off in open-source momentum (we love open-source)
• Growing friction around interoperability
• More money entering lobbying than engineering and building

How to Measure the Direction We’re Heading

Again, I'm not an expert. I'm just thinking about this a lot more lately because I like to play the actual game of "hey let's build AI to change the world" instead of playing the "let's change the rules so only select people win" game.

So, are we advancing or regressing, and how do we measure it? These signals can help:

Track the Ecosystem:

• Open-source health: Measure GitHub repo activity (commits, issues, contributors), community engagement, and project longevity.
• Market control: Track model serving share across providers (e.g. Hugging Face Spaces, cloud usage stats, hosted model dashboards).
• Who’s at the table: Review public regulatory consultation documents, advisory board rosters, and participation in standard-setting organizations.

Assess Developer Experience:

• Are tools composable? Look for support across frameworks (ONNX, MLIR), shared formats (tokenizers, adapters), and vendor-neutral pipelines.
• Is API access improving or narrowing? Track changes in pricing, rate limits, TOS updates, and developer access programs. This is a large reason why GMI Cloud commits to offering the most affordable pricing on the market. Reward good ideas, not deep pockets.
• Are audits affordable and open? Check whether interpretability, safety, and alignment toolkits are publicly available and usable without enterprise support.

Watch Community Trends:

• Where are top contributors going? Monitor LinkedIn/job boards to see whether top OSS contributors are shifting to corporate policy or legal teams.
• Are policies evolving with technical feedback? Look for public RFCs, comment summaries, and visible versioning in policy drafts based on builder input.

Signals We’re Moving in the Right Direction:

• Interoperability is improving
• Startup scenes are thriving
• The stack is modular, not monolithic
• Audit tools are open and usable
• Regulation invites collaboration

Signals We’re Sliding Backward:

• APIs are closing off
• Compliance becomes pay-to-play
• Open-source dries up
• "Safety" becomes a gatekeeping tactic
• Auditing becomes enterprise-only

What we don’t want is regulation driven by panic: vague bans, fragmented standards, or backroom deals. That doesn’t protect innovation. It smothers it, and this is the reason why "regulation" is such a dirty word among innovators. I think most of the community will agree when I say: we don't want to play the regulation game. But we do want good regulation for a fair game of "let's build AI!"

I think most of the community is like me: we just want to build cool AI products that change the world. But we need to really think about what it means if the world wants to change AI too. Given the relative newness of our industry, we’re not too late to ask for these types of regulations. But we won’t get a second chance. Get involved. The future of AI won’t just be written in code. It will be shaped by the standards we create, the access we defend, and the voices we include.

So I'm starting the conversation: Which is worse: overregulation that slows progress—or underregulation that hands control to monopolies?