Fractional HR helps companies comply with Colorado’s AI hiring rules

Colorado has put employers on notice: when artificial intelligence materially influences hiring or other employment opportunities, it can trigger new legal obligations aimed at preventing “algorithmic discrimination.” Senate Bill 24-205 (Consumer Protections for Artificial Intelligence) treats employment and employment opportunities as a “high-risk” use case and frames the law as consumer protection for consequential decisions, explicitly including employment.

For many companies, the operational reality is that HR teams already juggle fast-moving recruiting demands, vendor tools, and evolving compliance rules. Fractional HR, experienced HR leaders embedded part-time, can be a practical way to build and run the recurring compliance program SB 24-205 expects, even though Colorado’s official materials do not endorse any particular service model and focus instead on developer and deployer duties.

Colorado’s SB 24-205: Why AI in hiring is “high-risk”

SB 24-205 regulates “high-risk artificial intelligence systems” used in “consequential decisions,” and employment decisions fall squarely within that scope. Colorado’s Attorney General describes the law as protecting consumers from algorithmic discrimination in consequential decisions, explicitly including employment-related outcomes.

In practice, “AI in hiring” can include screening tools, resume ranking, candidate scoring, interview analysis, assessment platforms, and workflow automations that materially affect who advances. The legal risk increases when an automated system becomes a “substantial factor” in whether a person gets an interview, an offer, or a promotion opportunity.

This matters because employers may be considered “deployers” when they use these systems in the real world, even if they did not build them. The law’s compliance burden is therefore not limited to tech vendors; it attaches to organizations that use the tools to make or influence employment decisions.

The most important “recent” update: the effective date moved to June 30, 2026

Colorado’s timeline changed. SB 24-205 obligations were extended to June 30, 2026 (not February 1, 2026) through SB25B-004, as reflected in the Colorado General Assembly’s bill summary for the 2025 legislation.

The amended effective date is also reflected in the Colorado Revised Statutes for deployer duties, which begin “On and after June 30, 2026.” For employers building a compliance plan, this statutory language is critical because it anchors when core deployer obligations become enforceable.

The delay does not mean companies should wait. It means they have a defined runway to inventory AI tools, update hiring workflows, establish governance, and pressure-test vendor claims, before obligations and potential enforcement concerns arrive.

What compliance looks like for employers (deployer duties)

For hiring teams, the deployer obligations under SB 24-205 function like an ongoing program rather than a one-time policy update. The bill summary highlights requirements such as using “reasonable care,” implementing a risk management policy or program, completing impact assessments, and annually reviewing deployments to help prevent algorithmic discrimination.

“Reasonable care” is not abstract. As summarized in HR compliance commentary, the law expressly expects deployers to protect individuals from “known or reasonably foreseeable risks” of algorithmic discrimination. That phrasing pushes employers toward structured documentation and repeatable processes, not informal checks.

Because hiring processes change frequently (new roles, new screening steps, new vendors), compliance is likely to be iterative. Each meaningful change to how a tool is used can affect risk, and annual review requirements reinforce the need for a living system of oversight.

Notice, transparency, and appeals: what applicants may need from you

SB 24-205’s summary includes transparency duties that will feel familiar to privacy and consumer-protection regimes but are newly relevant for recruiting operations. When a high-risk AI system will be a substantial factor in a consequential decision, the individual must be notified.

The same summary describes additional rights and workflow expectations: individuals may be offered a way to correct personal data, and they may have an appeal pathway for adverse decisions, “via human review if technically feasible.” In employment contexts, that means HR teams should think a about how a rejected candidate or internal applicant can request a reconsideration.

These requirements can collide with high-volume hiring realities. Without a designed process, templates, SLAs, trained reviewers, and documentation, companies can end up with inconsistent notices, ad hoc “appeals,” and uneven human review that is hard to defend later.

Recordkeeping and impact assessments: the unglamorous work that drives readiness

Impact assessments are central to deployer compliance, and record retention is part of the operational burden. An ABA analysis notes deployers must keep the most recent impact assessment and prior assessments/records for at least three years after final deployment.

For employers, that can translate into building a small “AI hiring compliance file” for each system: purpose, data inputs, evaluation criteria, monitoring results, vendor statements, changes over time, and outcomes of annual reviews. The goal is to be able to show the reasoning and steps taken to avoid discriminatory impact.

Done well, documentation also improves decision-making. It forces clarity on what the tool does, what it should not do, which job families it supports, and how the company will respond if metrics suggest bias or inconsistent outcomes.

Rulemaking uncertainty: why operational flexibility matters

Colorado’s Attorney General has described an AI rulemaking process and notes that formal notice-and-comment rulemaking will begin after a notice of rulemaking is filed. As reflected on the AG’s AI page, the state has collected pre-rulemaking input and laid out future steps, but formal rulemaking had not begun at the time described there.

This creates a predictable problem for employers: you must prepare for compliance, but some interpretive details may evolve. That uncertainty increases the value of a governance approach that can be updated, policies, training, vendor questionnaires, and audit routines that can be revised without re-architecting the whole recruiting function.

Business and legal observers also expect changes. Greenberg Traurig reports the delay to June 30, 2026 was intended to allow more time and that lawmakers may pursue substantive amendments during the 2026 regular session. Preparing now should therefore emphasize durable principles (risk management, transparency, documentation) that will remain useful even if details shift.

Why companies are preparing now: scrutiny, lobbying, and reputational risk

Even with the effective date extended, the topic is not quiet. Axios Denver reported that more than 100 companies and organizations hired roughly 150 lobbyists around the 2025 special session changes, an indicator of how seriously the business community views the law’s potential impact and the stakes involved.

For employers, “waiting” can increase future costs. Vendor contracts, ATS integrations, assessment platforms, and recruiting workflows take time to redesign. By the time June 2026 arrives, the organizations that started early will be refining; the rest will be scrambling.

There is also a reputational dimension. Hiring discrimination allegations, especially those involving AI, can escalate quickly. A proactive compliance posture signals that the company is treating fairness and transparency as core operating requirements, not after-the-fact fixes.

How fractional HR supports SB 24-205 readiness (without claiming it’s “endorsed”)

Colorado’s official sources focus on deployer/developer duties and do not present “fractional HR” as a compliance pathway. Still, fractional HR can be a practical staffing model for executing the specific, ongoing tasks the bill summary anticipates, especially for small and mid-sized companies without a large in-house compliance function.

Fractional HR leaders can stand up and maintain the core operational program: drafting and updating written risk management policies, coordinating AI impact assessments, running annual reviews, building applicant/employee notice templates, and designing appeal and human-review workflows. These are the exact types of cross-functional tasks (HR + legal + IT + recruiting + vendors) that often stall when no single owner has time and authority to drive them.

Fractional HR can also manage vendor documentation and governance. That includes maintaining tool inventories, ensuring contracts and intake questionnaires capture what the system does, which data it uses, and what monitoring is available, then tying those vendor artifacts back to the employer’s impact assessment and recordkeeping obligations.

Colorado’s SB 24-205 makes AI-assisted hiring a compliance priority, not a future “nice to have.” Employment decisions are treated as high-risk, and deployers are expected to use reasonable care, implement risk management, complete and retain impact assessments, provide notices, and support appeals with human review where feasible.

With obligations now effective on June 30, 2026, employers have time, but not unlimited time, to build repeatable processes that can adapt to rulemaking and potential legislative amendments. Fractional HR won’t replace legal advice or eliminate deployer duties, but it can provide the operational horsepower to implement the policies, reviews, documentation, and workflows that make Colorado AI hiring compliance achievable.