What Do AI Regulations Actually Require From SMBs?

What do the new AI regulations actually require from small businesses?

Right now, most small businesses do not face hard federal AI compliance deadlines. But two developments changed the calculus in 2024 and 2025: Colorado substantially rewrote SB 205 before it ever took effect, and Congress introduced a 269-page federal AI bill that signals where things are heading. If you use AI in any consequential decision about people, you need to understand what these laws are actually targeting.

Who do these laws target, and does that include you?

Both the Colorado law and the federal framework are built around the concept of 'high-risk AI systems.' This is not a vague term. It refers specifically to AI used in decisions about employment, credit, housing, education, healthcare, and insurance. If your business uses an AI tool to screen job applicants, score leads for loan eligibility, or triage patient intake, you are likely in scope.

Colorado's SB 205 originally applied to any company deploying an AI system that makes or substantially influences a 'consequential decision' affecting a Colorado resident. The rewrite narrowed some definitions and extended the effective date, but the core framework held: deployers and developers both carry obligations, and 'deployer' means you if you are using the tool in production.

Small businesses often assume these rules only apply to the vendors who build the AI. That assumption is wrong and getting more wrong with each legislative cycle.

What does the Colorado law actually require you to do?

Under Colorado's revised framework, businesses that deploy high-risk AI systems must:

• Conduct and document impact assessments before deployment and on a regular review cycle
• Disclose to consumers when AI is making or influencing a consequential decision about them
• Provide a meaningful appeals process so consumers can contest AI-driven decisions
• Maintain a risk management policy that maps to a recognized framework (NIST AI RMF is the most commonly referenced)

The law does include a small-business consideration. Companies with fewer than 50 employees that use a third-party AI system, without modifying it, may qualify for a lighter-touch compliance path. But 'lighter touch' does not mean 'no documentation.' You still need to show you performed reasonable due diligence on the vendor's system.

'We just use the vendor's tool' is not a legal defense. It may reduce your exposure, but it does not eliminate it.

What is the federal bill proposing, and should you care yet?

The federal bill, sometimes called the SAFE Innovation Framework, is still in committee as of mid-2025. At 269 pages, it is not light reading. The core obligations it proposes for covered entities include:

| Requirement | What it means in practice | |---|---| | Transparency disclosures | Tell users when AI is being used in a decision | | Algorithmic impact assessments | Document risk before deployment, not after | | Human oversight requirements | High-risk decisions need a human in the loop | | Incident reporting | Report significant AI failures to a federal body | | Data provenance records | Track what data trained or informed your AI system |

The bill has not passed. But it represents the direction of travel, and several state laws are already mirroring its structure. Waiting for federal law to finalize before building any compliance muscle is a losing strategy. By the time the law is final, the businesses that prepared will have a six-to-twelve month head start on documentation and vendor vetting.

What counts as 'high-risk' AI in an SMB context?

This is where most operators get confused. They picture high-risk AI as facial recognition or autonomous weapons. In regulatory terms, it is much more mundane.

Common SMB use cases that likely qualify as high-risk under current and proposed frameworks:

• Using an AI tool to rank or filter job applicants (even if a human makes the final call)
• Using a credit-scoring or lending AI to approve or decline customer financing
• Any AI-assisted medical or mental health intake or triage
• Insurance underwriting tools that use AI to set premiums or deny coverage
• AI-driven tenant screening for property managers

Use cases that are generally not high-risk under current frameworks:

• AI writing assistants for marketing or internal docs
• Chatbots for customer service that do not make binding decisions
• AI for scheduling, inventory, or operations optimization
• Summarization and research tools used internally

If your AI stack sits entirely in the second column, you have more time. If anything touches the first column, the clock is already running.

How should a small business actually approach compliance right now?

The businesses getting this right are not hiring compliance attorneys on day one. They are building a lightweight internal record that proves they thought about this seriously. That means three things:

First, inventory your AI tools. List every AI system your business uses, who the vendor is, what decisions it informs, and whether any of those decisions affect customers, employees, or applicants. One spreadsheet. Update it quarterly.

Second, read your vendor contracts. Most AI vendors now include AI-specific terms. Some are passing compliance obligations downstream to you. You need to know what you agreed to before a regulator asks.

Third, map any high-risk use to NIST's AI Risk Management Framework (NIST AI RMF). You do not need to implement the whole framework. But being able to say 'we followed NIST guidance' is meaningful protection and it is free.

None of this requires a six-figure compliance budget. It requires about four to eight hours of focused work to set up, and a quarterly review habit after that.

What we'd actually do

• Run the inventory this week. Pull every AI tool your business touches, categorize it as high-risk or low-risk using the criteria above, and document it. This single step puts you ahead of the majority of SMBs.
• Pull your top vendor's AI terms of service and read section by section for indemnification and compliance language. If it is unclear, email the vendor and ask directly who is responsible for regulatory compliance. Their answer tells you a lot.
• Join the conversation before the rules are final. The AI for Business community at skool.com/aiforbusiness is where operators are working through exactly this, including governance templates, vendor vetting frameworks, and real-time updates as state laws move. Governance is not a solo sport.