Speaking of Risk and Audit

The episode covers several substantive topics - AI governance evolution, post-quantum cryptography, agentic AI use cases, and skill development for auditors - but spends considerable time on general introductions and conversational pleasantries. While there are actionable insights (e.g., the momentum game in building AI agents, starting with planning and reporting phases), much of the discussion restates common knowledge without dense, non-obvious claims that would surprise a seasoned audit operator.

“building your first agent is tricky. You've got to figure out how to navigate your organization's governance... But once you get to your second or third or fourth agent, you start to get some muscle memory”

“Usually where I see teams start is in the planning phase of the audit, when you're trying to synthesize a lot of documentation”

The guest makes one genuinely original contribution - post-quantum cryptography and harvest-now-decrypt-later threats - which is underappreciated in audit planning. However, the bulk of the discussion (AI governance maturation, skill development, treating AI as a tool requiring human judgment) tracks well-worn industry talking points. The framing of curiosity as the 'killer app' is memorable but not novel.

“We're one major breakthrough away from a quantum computer that can break all of our encryption”

“One of the trends that you're seeing now is a lot of organizations are taking a harvest now, decrypt later approach”

Charles King is a KPMG partner with genuine operational credibility: he spent years as an internal auditor, earned an NYU master's in data analytics, led revenue optimization in industry, and now leads innovation and AI integration at a Big Four firm. He is not a pure theorist but someone with hands-on experience building AI solutions and managing internal audit transformation. This is a relevant practitioner at scale.

“I started my career at KPMG as an internal auditor”

“Got a master's from NYU in data analytics and went off into industry to start a data analytics practice. Did that for about five years”

The episode lacks concrete data, named examples, or quantified metrics to anchor claims. Richard cites Optro research showing 25% of CAEs actively using AI, 50% piloting, and 25% not engaged, but Charles provides no specific client cases, ROI figures, timeline data, or named organizations to illustrate points. The discussion remains abstract about 'teams,' 'agents,' and 'organizations' without grounding in real-world examples.

“What came back from the population that we surveyed, chief audit executives, about 25% of them said they were actively using AI. About 50% said they're piloting or experimenting with it. And then about 25% said, you know what, we're not really going to do anything for at least a year”

“As we get more and more advanced along your journey, you can start to become more sophisticated”

Richard Chambers asks structured, logical follow-up questions that advance the conversation (challenges keeping CAEs awake, underestimated trends, evolution of AI conversation, immediate use cases, skill development). However, he rarely probes deeper when Charles makes bold claims - e.g., post-quantum cryptography is mentioned as critical but not interrogated further, and the metaphor of AI as 'precocious intern' is left unchallenged. The tone is collegial rather than press-like; missed opportunities to pressure-test claims.

“Let me ask you, what do you think are the most significant pressures and challenges that internal audits are currently facing”

“What would you say to a listener who's sort of on the fence? They know they want to try something”