.png)
What SB 243 Actually Does (and Why It Matters)
On October 13, 2025, Governor Gavin Newsom signed SB 243 into law, making California the first state to set guardrails for AI chatbots. SB 243 isn’t about how AI thinks – it’s about how it acts. The law targets use-case safety and disclosure, not model weights or training data. Key elements include:
- Clear disclosure that a user is interacting with a chatbot (not a human)
- Measures to prevent harmful content in youth interactions
- A framework that places responsibility on chatbot operators
SB 243 plants a flag: regulate what AI does, not how it’s built. That approach is easier to enforce because it maps to observable product behavior.
California’s done this before with privacy, emissions, and security. When it sets the bar, everyone else eventually follows. Expect SB 243 style duties around disclosure, youth protections, and harm-prevention protocols to appear in other states’ bills this year.
Use-Case Regulation vs. Model Regulation
The SB 243 model shows where lawmakers are converging:
- Regulating applications where harms are concrete and where consumer-protection concepts apply.
- Avoiding blanket rules on models, which are harder to define and risk chilling innovation.
In other words: regulators can evaluate what products do to people in context, not the architecture under the hood.
Congress Didn’t Preempt the States—So the Patchwork Stays
Over the summer, Congress stripped out a proposed ten-year ban on state and local AI regulations from its “One Big Beautiful Bill.” That means there’s no federal umbrella shielding startups from a wave of state-by-state rules.
Advocacy groups argued that a ban on AI laws would tie states’ hands in addressing real harms like algorithmic bias and consumer deception. For now, they’ve won. The federal debate isn’t over, but founders shouldn’t build compliance roadmaps in the hope that Congress will unify the rules anytime soon.
What This Means for AI Startups Right Now
Think of 2025 AI compliance as 2018 privacy: fragmented, fast-moving, and achievable if you design for it. Here are a few ways to get (and stay) ahead:
1) Rank your use cases by human impact
Map where your product touches minors, sensitive populations, or high-stakes domains (health, employment, credit, education). These will be first targets for state rules and scrutiny from state Attorneys General (AGs).
2) Ship disclosure like it’s part of UX
Implement conspicuous “You’re chatting with AI” notices at session start. Treat the disclosure as a usability component, not a legal afterthought.
3) Operationalize content-safety controls
Combine policy filters, guardrails, and post-generation classifiers. Keep an auditable trail of safety interventions. This aligns with SB 243’s “reasonable measures” standard and future state laws.
4) Expect state AGs to start asking for attestations
Even where full audits aren’t mandated, expect questionnaires, certifications, or AG inquiries. Maintain a living AI Risk & Controls Register mapped to each jurisdiction (CA, CO, NY, etc.),t focused on model use and harms.
Takeaways for Founders and Product Leaders
If you’re building or selling AI products, your playbook is clear: design for the strictest state — right now, that’s California — and relax only where you can. It’s cheaper than scrambling later, and it keeps enterprise buyers from stalling in security review.
Treat go-to-market risk like any other product feature. Buyers will ask about chatbot safety controls; show up with an SB 243-ready statement and a clean safety architecture diagram. And don’t count on Congress to bail you out — federal preemption isn’t coming soon.
Ship with the patchwork in mind. That’s how you stay compliant and commercially credible as the map fills in.
