From Generative AI to Autonomous Intelligence: Why Security Is Already Behind
Originally published in The AI Journal, 23 March 2026. Summary below; the full article is linked at the end.
The shift from generative AI to autonomous intelligence is not a change in what AI can say. It is a change in what AI can do. When systems move from drafting to deciding, from suggesting to executing, every weakness in the estate underneath them is executed too, at machine speed and machine scale.
My argument in this piece is that AI does not create entirely new security problems. It magnifies the consequences of the ones we already have: identity sprawl, weak data governance and poorly secured APIs. A flaw that once touched dozens of transactions can now touch millions before a human notices.
What I argue in the piece
Automation amplifies existing weaknesses. The foundations of identity, data and API security must be fixed before autonomy is layered on top, not after.
The governance gap is real: fewer than 30% of enterprises have a formal AI governance framework, while attackers are already using AI to scale their own operations.
A new discipline is needed. AI Safety Engineers, blending cybersecurity, data science and governance, will be the people who keep intelligent decision systems inside policy boundaries.
This is the thinking behind Pinpoint's Safe AI Adoption work: secure the foundations, govern the decisions and prove, continuously, that the controls hold.
Read the full article in The AI Journal: From Generative AI to Autonomous Intelligence.
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