If you’re building or deploying AI, the rules have changed. Regulators now care about AI as a category—not just the downstream harms your technology might cause. And while there’s no single federal AI law yet, enforcement is already happening, customer expectations are rising, and investors are asking harder questions.
This isn’t theoretical. It’s affecting deal cycles, diligence timelines, and go-to-market strategy right now.
The Landscape in 60 Seconds
The EU AI Act went live in 2024 with phased implementation through 2025 and beyond. It’s the first comprehensive, horizontal AI regulation from a major jurisdiction. In the U.S., there’s no federal equivalent yet—but state attorneys general, the FTC, and sector regulators are actively enforcing existing consumer protection, privacy, and anti-discrimination laws against AI products. California’s privacy regulator has expanded its authority to cover automated decision-making, essentially making it an AI regulator by another name.
The pattern is familiar: the EU gives us a framework, U.S. federal action stays fragmented, and states plus sector regulators fill the void.
Three Reasons You Can’t Ignore This
1. Your customers will ask.
Enterprise buyers—especially in financial services, healthcare, and HR—are embedding AI compliance questions into vendor questionnaires. If you can’t answer “What AI do you use?”, “How do you know it works?”, and “What happens to our data?”, your deal slows down or dies. We’re seeing this at every stage, including Seed and Series A companies selling into Fortune 500s.
2. Your investors will ask.
AI governance is becoming a standard diligence topic. Investors want to know you’ve thought about risk classification, vendor dependencies, and regulatory exposure. It’s not a deal-breaker if you’re early, but you need a coherent answer. “We haven’t thought about it” doesn’t work anymore.
3. Enforcement is already happening.
The FTC has brought actions against companies for unsubstantiated AI claims—what regulators call “AI washing.” State AGs are investigating discriminatory outcomes in hiring and lending. The EU is gearing up to enforce the AI Act. This isn’t a 2027 problem. It’s happening now.
The Shift: From Harm to System
Historically, tech regulation focused on harm after the fact: data breaches, discriminatory outcomes, deceptive practices. You built the product, launched it, and if something went wrong, you dealt with it.
AI regulation is different. Regulators are asking questions before harm occurs: What risk category is your system in? How did you test it? What oversight exists? This is a fundamental shift, and it changes how you need to think about compliance from Day 1.
What “Good Enough” Looks Like at Each Stage
You don’t need the same compliance posture at Seed that you need at Series B. Here’s a rough guide:
Pre-Seed / Seed:
- Know what AI you’re using (third-party models, custom models, vendors)
- Be able to explain your data flows in a customer meeting
- Don’t make unsubstantiated claims in marketing (e.g., “99% accurate,” “bias-free”)
Series A / early B:
- Maintain a use case inventory and vendor dossier (we’ll cover these in Part 4)
- Have a documented process for evaluating and monitoring AI systems
- Be ready for enterprise procurement questionnaires
- Understand whether your product touches high-risk categories (hiring, credit, biometrics)
Growth stage (Series B+):
- Formal AI governance process with ownership and review cadence
- Testing and monitoring infrastructure for accuracy, bias, drift
- Contracts that anticipate regulatory change
- Documented incident response for AI-related issues
The goal isn’t perfection. It’s being proportional, evidence-based, and able to show your work.
Your Compliance Posture Needs to Answer Three Questions
In any customer meeting, investor diligence call, or regulatory inquiry, you should be able to answer:
- What AI do you use? (Third-party models? Custom models? Where and how?)
- How do you know it works? (Testing? Monitoring? Accuracy benchmarks?)
- What data are you processing? (Inputs? Retention? Training?)
If you can answer these three questions clearly, with documentation to back it up, you’re in the top quartile of early-stage companies.
What This Series Covers
Over the next four parts, we’ll walk through:
- Part 2: The EU AI Act and the five questions every startup must answer
- Part 3: U.S. enforcement reality and what actually gets startups in trouble
- Part 4: The three documents that answer 80% of customer and investor questions
- Part 5: Building a lightweight compliance process that scales
Each part is designed to be actionable. You can read them in order or jump to what’s most urgent for you right now.
Action Item
Block 30 minutes this week to list every place AI touches your product or operations. Include customer-facing features and internal tools. Ask yourself: Do I know what model we’re using? Do I know what data it’s processing? Can I explain this to a customer?
That’s your starting point.