At the same time, organizations are deploying systems vulnerable to prompt injection, model manipulation, data leakage, and other attacks aimed directly at AI. Grimes compares prompt injection to SQL injection: a form of attack made possible by a particular underlying technology. The difference is that AI will be embedded across desktops, devices, and interconnected services, and an attack against one model may reach an organization through an AI supply chain security teams have not fully mapped.
“There are attacks from AI against you, whether or not you’re using AI,” Grimes says. “And then there are attacks to the AI that you use, because we’re all using AI in some way, and that’s only going to grow over time.”
Traditional security fundamentals will mitigate many of the pathways attackers use to reach AI systems, but organizations will also need new controls for models, agents, prompts, and AI data flows. This, Grimes says, is an expansion of the security program, not an excuse to abandon what came before.
AI can help do the hard, tedious work
None of the experts argues that CISOs should turn away from AI. Used carefully, it can help security teams analyze telemetry, investigate alerts, discover assets, examine code, and identify vulnerabilities — scaling work organizations have historically performed poorly because it is tedious and labor-intensive.
AWS’s Brandwine says security organizations need ways to experiment with AI without subjecting every idea to a lengthy production review. A new AI-powered detection, for example, can run in parallel with an established system so defenders can compare results without immediately depending on it. That agility becomes essential as developers produce software faster and employees adopt new models and agents, requiring security teams to keep pace without turning governance into an obstacle employees evade.
AI may finally make some aspects of security hygiene easier to sustain — assisting with asset classification, correlating disconnected inventories, prioritizing remediation work, and reducing the manual burden of reviewing logs. But its results will be only as dependable as the systems, data, and human decisions surrounding it.
The winning formula is therefore neither “forget AI and return to the basics” nor “let AI solve cybersecurity.” It is to use AI to increase the speed and scale at which organizations perform the fundamentals while preserving the human knowledge, governance, and accountability necessary to determine whether the technology is getting the work right.
As Google Cloud’s Betz puts it, the journey is “a firm foundation and a move-faster piece with AI on top.”
