HR Maturity Gap Report: AI, Governance & Trust in HR

The gap between how fast organisations are adopting AI in HR and how slowly they are governing it. Our survey found that 74% of HR leaders expect AI to improve their working environment — yet 61% lack clearly defined AI guidelines and 51% have no governance role at all. The ambition is real. The infrastructure to match it largely isn’t.

AI maturity is the degree to which an organisation uses AI effectively, consistently, and with appropriate oversight. Most HR functions are stuck at the lowest level, using AI only for isolated tasks rather than integrating it into decisions that shape real outcomes. Maturity matters because without it, organisations accumulate risk without realising the benefits.

Start with three questions: does your AI predict actual job performance? Would the same candidate receive a consistent result over time? Are the insights genuinely job-relevant? Beyond the tool itself, assess whether your organisation has clearly defined AI guidelines, a named person with authority to review AI-driven decisions, and a process for monitoring bias in practice.

The EU AI Act sets out binding obligations for organisations that deploy AI in recruitment, screening, and performance management. Crucially, these obligations cannot be transferred to your vendor. They include trained oversight personnel, impact assessments, worker notification, and decision logging. Worker consultation requirements are already enforceable, with full high-risk obligations targeted for August 2026.

In practice, it means having a named person with the authority and time to review and override AI-driven decisions, guidelines that people actually follow, and tools that are monitored for bias continuously — not just at deployment. Our data shows that organisations with genuine governance infrastructure are more than twice as likely to provide formal AI training and significantly more likely to actively monitor for bias.

Three things: validity (does the tool actually predict job performance?), consistency (would the same candidate receive the same result on a different day?), and differential impact (does the tool perform differently across demographic groups?). Most HR AI tools are not built with this level of rigour. The report explains what to look for and what to ask your provider.

It sets out what Article 26 requires of deployers in plain language, explains the distinction between provider and deployer liability, and gives HR leaders a clear picture of where most organisations currently fall short. It also includes practical recommendations tailored to CHROs, HR business partners, and L&D leads, so you know exactly where to focus.

HR leaders, HR business partners, L&D teams, and people analytics professionals – particularly those using or planning to use AI in recruitment, performance management, or development. The final section includes role-specific guidance, and the report is structured so readers who go straight to the recommendations still get everything they need to act.