AI is spreading across enterprise risk functions, but confidence in those systems remains uneven, according to AuditBoard. More than half of organizations report implementing AI-specific tools, and many are training teams in machine learning skills. Yet, few feel prepared for the governance requirements that will come with new AI regulations.
AI experimentation increased in May and June 2025, then dropped in July as acceptance rates fell and decision times lengthened. That volatility shows how many teams are eager to test new tools but lack governance structures that build lasting trust in their results.
The middle maturity trap
Across industries, many organizations are caught in what AuditBoard calls the “middle maturity trap.” Teams are active, frameworks are updated, and risks are logged, but progress fades after early success.
When boards include risk oversight as a standing agenda item and align on shared performance goals, activity becomes consistent and forward-looking. When governance and ownership are unclear, adoption slows and collaboration fades.
Control maturity depends on governance
Controls translate policy into daily practice, but adoption speed…
