AI Employee Training Requirements Under the Colorado AI Act

The Colorado AI Act doesn't just regulate the AI itself — it regulates the people who use it. If your employees interact with high-risk AI systems, you are required to train them. Here is what the law actually requires and how to build a training program that satisfies the statute without grinding your operations to a halt.

Most businesses that deploy AI tools focus on the technology: model selection, vendor due diligence, data governance. Those matter. But the Colorado AI Act also imposes obligations on the humans in the loop — the employees who use AI outputs to make or inform decisions about consumers. If those employees are not properly trained, your business is exposed even if the underlying AI system is perfectly compliant.

Who needs to be trained?

The Act applies to deployersof high-risk AI systems — businesses that use AI to make “consequential decisions” about consumers in areas like employment, lending, insurance, housing, education, and access to essential services. If your business fits that description, every employee who interacts with the AI system or its outputs needs training. That includes people who:

• Directly operate or configure the AI system (data entry, prompt engineering, threshold adjustments)
• Review, approve, or override AI-generated recommendations before they reach consumers
• Communicate AI-driven decisions to consumers (customer service reps, loan officers, claims adjusters)
• Manage or supervise teams that do any of the above

What does the training need to cover?

The statute does not prescribe a specific curriculum, but it does require that employees have sufficient knowledge to:

1. Understand the AI system's intended use — what the system does, what inputs it considers, and what kind of output or recommendation it generates.
2. Recognize the system's limitations — known biases, accuracy rates, categories of errors, edge cases where the system performs poorly.
3. Exercise meaningful human oversight — how to review AI outputs critically, when to override or escalate, and what documentation to create when they do.
4. Follow your organization's AI governance policies — internal escalation paths, logging requirements, and consumer disclosure obligations.

In practice, this means your training program needs to be specific to each AI system, not a generic “AI 101” slide deck. An employee who reviews AI-scored loan applications needs different training than someone who uses an AI chatbot to triage customer support tickets.

How often do you need to retrain?

The Act requires “reasonable” ongoing training — not a one-and-done onboarding session. While the statute does not specify a cadence, regulators and courts will look at whether your training kept pace with changes to the AI system. At minimum, retrain when:

• The AI vendor pushes a significant model update or version change
• Your business changes how it uses the AI system (new decision categories, new consumer populations)
• An audit, complaint, or incident reveals a gap in employee understanding
• Regulatory guidance or enforcement actions clarify new expectations

Building a practical training program

Step 1: Inventory your AI systems

List every AI system your business deploys that touches consumer decisions. For each one, document what it does, what data it uses, and which employees interact with it. This is also the foundation of your AI decision documentation obligations.

Step 2: Create system-specific training materials

For each AI system, draft a training module that covers the four elements above: intended use, limitations, oversight procedures, and internal governance policies. Keep it short and practical. Employees retain more from a 20-minute hands-on walkthrough than a 90-minute compliance lecture.

Step 3: Assign and track completion

Use whatever LMS or tracking system you already have. If you don't have one, a shared spreadsheet works — what matters is that you can prove, for any given employee on any given date, whether they had been trained on the AI system they were using.

Step 4: Schedule refreshers

Set calendar reminders to review your training materials quarterly. Most updates will be minor. But when your AI vendor ships a major model change, you need to update your materials and retrain affected employees before they start using the new version.

What happens if you don't train?

The Colorado AI Act gives the Attorney General enforcement authority. A failure to train employees is evidence that your business did not exercise “reasonable care” in deploying the AI system — which is the core standard the Act uses to determine liability. In practice, inadequate training is often the easiest thing for regulators to prove because it shows up (or doesn't) in your documentation.

Beyond enforcement, untrained employees are a business risk independent of the statute. An employee who doesn't understand an AI system's limitations is more likely to rubber-stamp a bad recommendation, creating liability under existing consumer protection, employment, and lending laws — not just the AI Act.

Get compliant before enforcement begins

The good news: building a training program is one of the most straightforward compliance obligations under the Act. It does not require expensive technology or outside consultants. It requires organizational discipline — mapping your AI systems, writing clear materials, and tracking completion. Our FAIIR compliance framework includes training program templates and documentation checklists designed specifically for Colorado businesses deploying AI.