Are New AI Regulations About to Help—or Wreck—Your Business?

Imagine you’re leading an AI project that detects anomalies in medical scans, poised to transform patient outcomes. Then, legislation like California’s AB 412 comes along, demanding rigorous documentation for copyrighted training data—and imposing daily fines if you don’t respond to inquiries fast enough. While these laws are meant to protect creators’ rights, they also risk creating a patchwork of state-level rules that especially burdens smaller innovators.

In an ideal world, AI regulations would strike a balance between protecting intellectual property and fostering progress. Instead, the current environment can feel like a maze of local laws. Businesses that lack resources to navigate these obstacles may find themselves forced to scale back or abandon promising AI initiatives.

These compliance hurdles at the state level are just one facet of a larger regulatory trend emerging across the country.

AB 412: A Snapshot of the Regulatory Puzzle

California’s AB 412 is designed to protect owners of copyrighted works from unauthorized use in training AI models. Consider a freelance illustrator whose designs are ‘scraped’ by a major tech platform. The bill offers them a straightforward path to discover and claim compensation for their work.

However, AB 412 also includes:

Documentation Overload Every copyrighted item in a training set must be logged meticulously—an enormous task for startups processing thousands or millions of data points.
Strict Response Timelines You have seven days to verify whether you used someone’s copyrighted material—or risk $1,000-per-day fines.
Extended Record-Keeping The bill mandates keeping proof of compliance not only for the AI model’s commercial lifespan but also for an additional decade.

That’s a tall order if your AI team is small and working on limited budgets.

The Broader Patchwork: More Than Just California

California isn’t alone in forging AI regulations. States like Illinois have proposed biometric privacy laws that affect certain AI applications, while New York has weighed local bills on automated decision-making in hiring practices. Each new rule aims to safeguard specific public interests—privacy, fairness, copyright protection—but taken together, they create a tangled web for businesses operating across state lines.

Consider many AI startups in the U.S. have 50 employees or fewer like Cursor who went from 0 – $100M ARR with 20 people, or Mercor who went from 0 to $50M ARR with 30 people or ElevenLabs that reportedly went from 0 to $100M ARR in with about 50 people.

These smaller companies face disproportionate compliance costs. Regulatory uncertainty creates an environment that often favors established players.

“These extensive regulations would also have an anticompetitive effect, as they impose fixed costs that disproportionately affect smaller businesses with less time and capital to comply with them.” — Cato Institute

Too much regulation can also create a barrier to entry for new and disruptive players: high compliance costs can make it almost impossible for startups and smaller companies to develop their ideas.

Why Federal Principles Matter

Some argue that states should tailor AI regulations to their unique concerns. While local responsiveness can be valuable, the resulting fragmentation means businesses struggle to scale effectively. A unified federal framework would help:

Offer Clarity: Clear national definitions of copyright use and data ownership reduce guesswork.
Create Fair Competition: Uniform standards level the playing field so that small ventures can compete.
Encourage Innovation: Developers can focus on ethical AI rather than juggling conflicting compliance rules.

A useful parallel is the U.S. financial sector’s adoption of federal guidelines after the 2008 financial crisis. Although each state still has some rules, overarching federal standards (such as those from the Federal Reserve or the FDIC) ensure that banks and fintech startups understand the core requirements, no matter where they operate. The same principle could help AI innovators navigate data ownership and privacy protocols without wading through 50 different sets of rules.

Recognizing Another Perspective: Supporters of State-Level Control

Not everyone believes in a single federal solution. States often see themselves as “labs of democracy,” capable of responding to local concerns swiftly. Advocates of state-specific regulation say that community needs vary and one-size-fits-all policies can be too rigid. But the trade-off is that every new state law adds another layer to the compliance burden, increasing the legal risk for those trying to innovate nationwide.

Practical Steps: Interim Measures While Federal Guidance Evolves

Until a cohesive federal framework emerges, here’s how you can protect your AI initiatives:

Audit Your Training Data Catalog data sources, relevant licenses, and any potential copyright issues.
Set Up Governance Playbooks Document internal policies for data handling and quick responses to inquiries—these serve as your compliance blueprint.
Stay Current on Legislative Changes Assign someone on your team—or a trusted partner—to track pending AI bills from coast to coast. Regulators change course frequently.
Implement a Rapid Response System Even if you disagree with certain regulations, failure to respond within tight windows can be expensive.
Engage with Policy Debates Join industry consortiums or legal advocacy groups. Local and federal policymakers often value input from real-world AI developers.

Toward a Unified Vision

While protecting creators’ rights remains a priority, a fragmented approach to AI legislation could stifle the very innovation that has the potential to benefit everyone. Small-scale developers, who often spark some of the most transformative breakthroughs, face uncertainty that can slow progress—or stop it altogether.

A balanced federal framework that respects both content creators and innovators would help ensure that the United States remains globally competitive in AI. Until that framework arrives, businesses must manage compliance carefully, share their experiences with policymakers, and advocate for rules that shield stakeholders while fueling progress.

As you consider the path forward, how do you plan to balance the protection of creative works with bringing AI-driven breakthroughs to life?