The New Economics of Risk: Securing AI in the Era of Immediate Consequence
Artificial intelligence is no longer an experiment at the edges of the enterprise. It is rapidly becoming core business infrastructure, shaping how software is built, how decisions are made, and how entire systems operate at a global scale.
That shift is unlocking enormous economic opportunity. It is also fundamentally changing the nature and cost of risk.
AI systems now move at machine speed, operate with increasing autonomy, and scale faster than the controls designed to govern them. The distance between action and consequence has collapsed. In this new environment, organizations can no longer afford to discover security failures after systems are already live.
The World Economic Forum has warned that AI-driven systems are increasing digital complexity while compressing the time between action and consequence. In practical terms, that means failures can propagate instantly across interconnected systems, supply chains, and markets. Security has shifted from a technical afterthought to an economic imperative.
"AI has moved from experimentation into production across the enterprise," said Peter McKay, CEO of Snyk. "That shift changes the economics of risk. You can't afford to discover security issues after the fact."
The Rise of Autonomous Risk
One of the most underappreciated changes underway is autonomy. AI systems are no longer just assisting humans; they are increasingly making and executing decisions on their own.
Snyk's latest research shows that half of security leaders say AI is already operating as a quasi-autonomous agent inside their environments today. Nearly 70% expect attackers to use AI to automate cyberattacks in the next 12 to 24 months, with many anticipating that those campaigns will be largely machine-driven.
This is not a future scenario. It is an active operating condition.
Software development offers a clear preview of what's coming. AI can now generate, modify, and deploy code continuously—expanding attack surfaces and introducing dependencies at a pace traditional security models were never designed to manage. What is happening in software today will soon extend across automated decision-making, operational workflows, and interconnected supply chains.
The Readiness Gap
Despite near-universal AI adoption, readiness is lagging. While organizations recognize AI's strategic value, most have not embedded security deeply into the systems where AI is introduced and scaled.
Only 29% of organizations have fully integrated AI-aware security checks across design, development, testing, and deployment. More than a quarter allow vendors to enable AI features in SaaS products with minimal review, effectively rubber-stamping third-party AI risk. As a result, more than half of security leaders believe their organization is likely to experience a material AI-driven incident within the next two years.
Trust by Design and the Case for Minimum Standards
As AI becomes foundational infrastructure, security must move upstream, embedded at the point where systems are designed, trained, and deployed. This is not about slowing innovation. It is about making innovation sustainable.
That reality is driving a notable shift in industry sentiment toward regulation. Snyk's research shows near-unanimous support for mandated minimum AI security standards, with a majority calling for urgent action. Clear baselines for transparency, accountability, and autonomous system oversight help align incentives, reduce systemic risk, and build trust across markets.
Well-designed regulation does not stifle innovation. It enables it.
The Leadership Imperative
Over the next decade, the organizations and economies that succeed with AI will be those that treat security and trust as design requirements, not downstream fixes. Security architectures built for human-paced software are structurally misaligned with autonomous systems operating at machine speed.
The defining leadership question is no longer, "Are we using AI securely?"
It is, "Can our security systems operate as autonomously and as fast as the AI we deploy?"
In the AI era, trust is not a byproduct of innovation. It is the condition that makes innovation possible.
This advertiser content was paid for and created by Acumen. Neither CBS News nor CBS News Brand Studio, the brand marketing arm of CBS News, were involved in the creation of this content.