Kayne McGladrey, an IEEE Senior Member and cybersecurity adviser, has tracked the agent identity gap across enterprises for the past year. In previous VentureBeat reporting, McGladrey described organizations as defaulting to human-style user profiles for AI agents, a practice that can lead to permission sprawl from the start. SOC 2, ISO 27001 and PCI DSS have not fully operationalized agent identities. A decision model that returns probabilities instead of prose does not map neatly onto those existing audit categories.

Kayne McGladrey, senior IEEE member, independent vCISO, and author of "Cyber Risk is a Myth," told VentureBeat that the privilege problem predates agents by decades. “We’ve had this pattern for 40-plus years,” McGladrey said. “Take this user account and clone it to that user account. We’re now doing that with agentic systems, except it’s an agent, not a human, and as we’ve seen with agentic AI, it does whatever it needs to do to get its job done, and sometimes that uses far more permissions than it should.”

Push notifications can give “a preview into people’s lives that they don’t really think about and that they don’t know they’re inadvertently disclosing,” McGladrey says. That’s because these notifications typically show the exact text of whatever message or email you’ve received. There’s no censor.

McGladrey offered a blunter test for CISOs weighing the decision. Most victims of AI-driven attacks, he said, "were losing to basic cybersecurity hygiene failures long before the swarms of agents arrived." His advice was to identify key business systems and the technical risks to those systems, and to close those gaps before buying the next generation of AI tooling.

Twenty-five years after 9/11, the systems built to make sense of instability are running lighter just as instability stacks up. The lead this week is the...

“The vendor owes their customers one page, in writing, before a single priority task lands in anyone’s queue,” McGladrey wrote in an email to VentureBeat. “That page should cover where the model sits in the pipeline, whether deterministic code parses the CVEs or the LLM does the counting, who reviewed the output, and what fraction of a 400-row list got verified against the source rather than skimmed.”

In Episode 84, fractional CISO, risk governance expert, and author Kayne McGladrey returns to the show to discuss the complex and rapidly evolving legal and financial realities of AI liability.

McGladrey said access can also be a problem, noting that the Verizon report flagged third-party involvement as contributing to 61% of manufacturing breaches. "Think about always-on VPN credentials issued to equipment vendors years ago that nobody has thought about since the equipment went on the shop floor," McGladrey said.

That 3% has a reason, Kayne McGladrey, author of the forthcoming "Cyber Risk is a Myth" and a senior IEEE member, told VentureBeat during a July interview. "It's only those well-resourced companies that are above the poverty line that have met all the prerequisites," he said.

If a multi-billion-dollar frontier lab can't keep its own models contained during controlled testing, why would you trust your dev team's implementation of an open-weight model? - Kayne McGladrey, fractional CISO

McGladrey walks through how that fails in practice. An agent told to "retrieve the market data report," he explains, could use an unauthenticated connector to skip the payment handshake, hand a fraudulent report to a paying client, and, under a deferred-settlement model that x402 supports, keep the discrepancy hidden until batch reconciliation shows a valid signature that delivered the wrong resource.

Almost nobody has built it. Kayne McGladrey, a senior member of the IEEE, has argued for years that an AI deployment needs a hard governance threshold, a named human holding a kill switch and a way to roll back. Asked whether any Fortune 500 company runs that, he was blunt. “I haven’t seen it done, and no, they haven’t come out and publicly said it,” McGladrey told VentureBeat.

"Kayne McGladrey, an IEEE senior member who advises enterprises on risk, put the funding logic bluntly in an interview with VentureBeat. “Anything that seems to have a cybersecurity flavor is generally put into the cybersecurity risk category, which is a complete fiction,” McGladrey said. “They should be focused on business risks, because if it doesn’t affect the business, like a financial loss, then nobody’s going to pay attention to it, and they will not budget it appropriately.” A rank number from a 29-person vote is a weaker budget argument than the business system the agent touches."

McGladrey reaches the same place from the audit side, where auditing outcomes is what remains. “We can audit code for compliance. We can audit code for security. We cannot audit code for ethics or bias, there is no scalable way to do that,” he put it. “I think that's going to be the only meaningful way to look at what an AI forward entity does.”

Kayne McGladrey, a senior member of the IEEE, has noted the structural distinction that explains why this matters for agent models specifically: "synthetic data lacks the unpredictability of human responses to the unexpected, such as when a window moves or is resized," and behavioral training data is what teaches a model "how tools flow together."

“If you look at the successful investigations over the past five years, there’s been about $350 million in ghost student schemes that have been thwarted,” says Kayne McGladrey, a cybersecurity risk adviser and senior member of IEEE, a nonprofit professional organization that champions technical innovation.

Improving access controls on AI models is the most obvious security gap to close, according to Kayne McGladrey, a senior member of IEEE, CISSP-certified cybersecurity advisor, and independent virtual CISO. “Treat your models and their APIs like crown jewels,” says McGladrey. “If you wouldn’t expose your database to the public internet without identity and access controls, why would you do that for your AI model?”

The pressure to fix this will not come only from threat reports. It is about to come through contracts. Kayne McGladrey, a senior member of the IEEE, told VentureBeat in an exclusive interview that enterprises are starting to push software security obligations onto the vendors and maintainers in their supply chains. "We're going to start seeing companies trying to contractually shift liability to other parties in their supply chain," he told VentureBeat. "We're using your technology, but we want you to do the security for it."

As an independent virtual CISO with a background in risk management, cybersecurity, and regulatory compliance, I prefer facts over marketing claims. For TechRound’s HealthTech44 2026, I ranked the submissions on five evidence-based dimensions: stated security maturity, AI claim substantiation, clinical validity, patient impact, and the team’s credibility. Companies that scored higher had provided named certifications, published benchmarks, regulatory clearance, quantified outcomes, and experienced clinical leaders named in their submission. By comparison, entries with visible AI instructions, placeholder content, or contradictory claims were disqualified, and submissions that were primarily unsubstantiated product marketing ranked poorly with me.

That figure makes the argument fundable. Kayne McGladrey, an IEEE Senior Member who has spent his career in identity security, told VentureBeat that security teams lose these fights by filing the exposure under the wrong heading. Companies "should be focused on business risks rather than some, you know, cybersecurity risk, because if it doesn't affect the business, like a loss or financial loss, in this case, predominantly, then nobody's going to pay any action to it, and they will not budget it appropriately, nor will they adequately put in controls to prevent it," he said. A destroyed model carries a known replacement cost, which is the version of this story a CFO acts on.