Latest data on AI adoption reinforces need for internal auditors’ “superpowers”

The value of timely risk data

One of the first major projects I championed after taking over as president and CEO of The Institute of Internal Auditors back in 2009 was the inaugural North American Pulse of Internal Audit survey and report. I knew that the benchmarking data it could provide on staffing, budgets, and emerging risk trends would be invaluable to chief audit executives.

The Pulse has served as a vital, consistent, and forward-looking resource, offering a comprehensive snapshot of the profession's current state and a roadmap for future development and increased value to organizations.

I raise this now to emphasize the value of up-to-date data on issues that impact risk and risk management. In today’s dynamic business environment, that must include staying current on artificial intelligence (AI), its rapid adoption rates, and its impacts on work productivity, processes, and profits.

New insights on rapid AI adoption

Two recent additions to the plethora of data on AI are the Generative AI Adoption Tracker developed by the Federal Reserve Bank of St. Louis, and McKinsey’s State of AI in 2025: Agents, Innovation and Transformation report. These two resources provide updated data that support findings in AuditBoard’s Focus on the Future 2026 report, which I wrote about earlier this month.

Generative AI adoption and productivity gains

The tracker, which relies on data from the fed’s quarterly Real-Time Population Survey, affirms what we already know to be true — Generative AI is being adopted at rates never seen before. It took an estimated 16 years for personal computers to reach a similar adoption level to GenAI, which was introduced publicly in November 2022 with ChatGPT. Further, data suggests AI is saving worker time: the tracker’s yearlong monitoring reflects an overall increase in productivity:

• In August, survey respondents reported an overall increase of 1.7% in time savings.
• Higher gains were noted for management (3%) and business and financial operations (2.4%).
• Fed analysts calculate that generative AI may have increased labor productivity by up to 1.3% since the introduction of ChatGPT.

While these estimates come with caveats, such as whether time saved is applied to higher-value tasks, the data strongly suggests AI is making workers more efficient.

Related: Top takeaways from The 2026 Focus on the Future Report.

Business integration and scaling

The key findings from McKinsey’s State of AI in 2025 report provide important insights into how businesses are incorporating AI into operations, as well. Nearly two-thirds of organizations say they have not yet begun scaling AI across the enterprise, and are still finding their way. What’s more, 62% report that their organizations are experimenting with AI agents — autonomous programs that can understand goals, make independent decisions, plan multi-step processes, and take action across various systems to achieve specific objectives with minimal human supervision.

As with adoption of any transformative technology, some organizations will move more quickly than others. Larger companies move more quickly from experimenting to piloting to scaling AI. Of particular interest to me is that while 80% of respondents in the McKinsey survey say their organizations set efficiency as an objective for AI initiatives, companies seeing the most value from AI tend to set growth or innovation as additional objectives and see redesigning workflows as a key success factor.

Cultivating internal audit superpowers to thrive in the AI age

The new data from the Fed tracker and McKinsey continue to point to one inevitable truth: AI will transform how business operates, and the greatest benefits won’t simply come from efficiency gains, but from innovation.

My review of AuditBoard’s Focus on the Future report raised serious concerns about whether the profession is positioned to thrive in an AI environment. Functions seen as compliance-focused or low-value will be highly vulnerable to being displaced by AI-driven processes.McKinsey’s findings on high interest in AI agents only reinforce those concerns. Adoption and scaling data from the Fed tracker and McKinsey should raise additional red flags when combined with data from the AuditBoard report on lagging governance efforts and internal audit’s low confidence in its ability to audit AI.

I don’t want to come across as a doom-and-gloom messenger. Indeed, I’ve already identified the key to ensuring internal audit’s growth as a valuable part of effective risk management in an AI environment.

The latest data from the Fed and McKinsey only strengthen my belief that by cultivating their “superpowers” — professional skepticism and inquisitiveness, relationship-building and communication, ethical judgment, critical thinking, and intellectual curiosity — internal auditors can help lead the way.

About the authors

Richard Chambers, CIA, CRMA, CFE, CGAP, is the CEO of Richard F. Chambers & Associates, a global advisory firm for internal audit professionals, and also serves as Senior Advisor, Risk and Audit at AuditBoard. Previously, he served for over a decade as the president and CEO of The Institute of Internal Auditors (IIA). Connect with Richard on LinkedIn.