There’s a striking disconnect — despite the rapid growth of artificial intelligence within the HR function, many HR leaders are not keeping pace with AI policies.
Recent findings from SHRM’s AI in HR report reveal that as of February 2026, 19 of the most populous U.S. states have enacted AI laws or regulations affecting employment-related decision-making and transparency. Still, 57% of HR professionals working in those states say they are unaware of the policies governing their use of AI.
Even among the 43% who are aware, readiness remains low. Only 12% of HR professionals report that they have implemented compliant policies and practices. Another 12% acknowledge they have yet to make necessary adjustments, while 19% say their organizations have not addressed compliance at all.
The Growing Complexity of AI Regulation
The challenge organizations face lies with fragmentation. Unlike other areas of employment law that benefit from clearer federal frameworks, AI regulation is emerging as a state-by-state patchwork.
Bradford Newman, partner and head of complex technology disputes at Eversheds Sutherland, has been closely tracking this trend.
“The patchwork of state and local AI regulations governing the HR function will continue to increase until there is preemptive federal AI legislation,” he said. “These varying laws include different triggers as to who is covered, what is prohibited or required, and what enforcement mechanisms and penalties apply.”
This variability creates additional complexity for organizations operating across multiple jurisdictions. A hiring algorithm that is permissible in one state may trigger disclosure requirements, bias audits, or outright restrictions in another.
At the same time, HR teams are under pressure to adopt AI tools that promise efficiency gains, better decision-making, and cost savings.
“Simultaneously, HR departments are being bombarded with AI tools which promise to increase efficiency and productivity while decreasing risk,” Newman said.
The result is a perfect storm: accelerating adoption combined with uneven governance.
The Risks of Getting It Wrong
Failure to address AI governance proactively exposes organizations to multiple risks:
- Regulatory enforcement: State and local agencies are increasingly empowered to investigate and penalize noncompliance.
- Litigation exposure: Class-action lawsuits related to algorithmic bias and discrimination are on the rise.
- Brand damage: Missteps involving AI can quickly erode employee and candidate trust.
- Operational inefficiencies: Retrofitting compliance after deployment is far more costly than building it in from the start.
“The reality for CHROs is that no AI tool should be procured or rolled out until a privileged risk analysis has been completed, and strategic decisions have been made,” Newman emphasized.
The Need for a Legislative Framework
As federal policymakers develop AI policy that impacts employers and workers, SHRM has recognized the urgent need to provide comprehensive guidance to protect and prepare employers and workers for the future.
In a recently released white paper, The Path Forward: SHRM’s AI Legislative Framework for the Modern Workplace, SHRM outlines guiding principles for federal policymakers.
The framework is built around eight core pillars, including:
A comprehensive national workplace AI framework.
Voluntary, risk-based governance.
Limited mandatory requirements for high-risk use cases.
Safe harbor for responsible AI adoption.
Minimized employer burdens.
Workforce readiness and reskilling.
Stakeholder engagement and expertise.
Support for small and midsize employers.
"SHRM's AI legislative framework provides a clear, practical policy foundation that organizations can rely on to support responsible innovation, protect workers, strengthen workforce readiness, and shape implementable guidance,” said Emily M. Dickens, chief administrative officer of SHRM, in the press release.
“We stand ready to work with the policymakers to advance a national set of policies to help organizations integrate AI responsibly, at scale, and in ways that drive productivity, opportunity, and long-term competitiveness,” she said.
What CHROs Should Do Now
While it may take more time to build a comprehensive national AI workplace framework, CHROs can still act now to help close the AI governance gap. Deliberate, cross-functional approaches can include:
1. Investing in education and capability building. Awareness is the first hurdle. In fact, 67% of organizations are not using AI because employees lack awareness of its capabilities. CHROs should prioritize upskilling HR teams on AI fundamentals, regulatory developments, and ethical considerations.
2. Establishing clear ownership. AI governance cannot be an informal or fragmented effort. CHROs should partner with legal, IT, and compliance leaders to define accountability for AI adoption and oversight.
3. Conducting a comprehensive AI inventory. Many organizations do not fully understand where AI is being used. One research report found that 89% of AI usage is invisible to the organization. Start by identifying all tools, vendors, and use cases — especially those impacting HR such as hiring, promotion, and performance decisions.
4. Implementing structured risk assessments. Before deploying any AI tool, organizations should evaluate:
- Jurisdictions where the tool will be used.
- Applicable laws and regulatory requirements.
- Risk versus reward of deployment.
- Compliance costs and oversight needs.
- Brand and reputational considerations.
5. Aligning policies with evolving regulations. Given the pace of change, static policies are insufficient. Organizations need dynamic governance frameworks that can adapt to new laws and guidance as they emerge.
Was this resource helpful?
Validate your HR expertise
Earning your SHRM-CP credential makes you a recognized expert and leader in the HR field.
Related Content
Transform HR with mobile technology to streamline workflows, enhance communication, and boost employee engagement across distributed teams.
A new study found that talent development practitioners believe performance-based assessments are more effective at measuring employee learning outcomes than knowledge tests.
As AI makes deeper inroads into organizations, employee concerns about the technology continue to grow. Here's how HR leaders can address the fear of AI among their own staff, as well as in the wider organization.