Cary Montrose

The way people talk about the EU AI Act sometimes makes it sound like every startup founder needs to become a lawyer overnight.

From what I've seen, that's probably not the most useful way to think about it.

For early-stage teams, the bigger takeaway is understanding the direction AI regulation is moving. There is increasing attention on risk, accountability, oversight, and the ability to explain how important decisions were made. As AI systems become more involved in customer interactions, business operations, and decision-making processes, regulators seem to be asking for clearer records and more visibility into what happened and why.

What's interesting is that many of these ideas are valuable even outside a regulatory context. If an AI system influences a customer outcome, most teams would probably want to know which model was involved, what information it used, whether anyone reviewed the result, and how the final decision was made. Those questions can come from customers, internal stakeholders, auditors, or simply from the team trying to understand its own systems.

If your business sends emails, transactional or marketing, you'll want to pay attention because this directly impacts your bottom line.

What I've observed in the last 4 years isn't good and the frustration is real.