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Managing the Risks of Agentic AI Requires a Lens of Its Own

June 18, 2026 | 8 minutes reading time | By David Weldon

When systems autonomously make and execute decisions, “the challenge is no longer securing models,” JPMorgan says. “It is securing agents operating in dynamic, interconnected environments.” Regulators are on alert for systemic implications.

As artificial intelligence takes the business and financial world by storm, agentic AI is causing a tsunami in its own right. The market for the autonomous technology is already bigger than $9 billion, with analysts expecting well into hundreds of billions by 2034.

In day-to-day terms, the prospects are incredibly exciting or fraught with risks – or both – and disrupting strategies and processes in real time. Some cases in point:

-- JPMorgan Chase & Co., which last year was on its way to being “fundamentally rewired” as a “fully AI-connected enterprise,” said in March that increasingly powerful agentic AI “requires a different emphasis” to “align safeguards to capability and risk . . . The challenge is no longer securing models. It is securing agents operating in dynamic, interconnected environments.”

-- Startup Catena Labs came out of stealth mode in May 2025 on a mission to build “an AI-native financial institution that will give AI agents, and the businesses and consumers they serve, the ability to transact safely and efficiently.” Twelve months later, CEO and co-founder Sean Neville, who was a co-founder of top U.S. stablecoin...

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Topics: Innovation, Cybersecurity, Risks & Risk Factors, Data & AI Model Governance

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