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View all search resultsSafeguarding autonomy in AI systems
The rise of agentic AI, or automous artificial intelligence systems that can make decisions and act with little to no human prompts or supervision, signals a need to revisit and rethink the practical, legal and ethical aspects of cybersecurity frameworks.
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A hooded man with a laptop computer is silhouetted against a projection of binary code, in this illustration created on May 13, 2017. (Reuters/Kacper Pempel)
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rtificial intelligence has entered a new phase. It is shifting from passive tools to autonomous agents that can plan and act across digital and physical systems, often for extended periods and in concert with other agents. Their interacting and collaborating capabilities are scaling quickly, allowing them to perform increasingly complex tasks with minimal human input across sectors such as banking, e-commerce and logistics.
These systems are improving efficiency but they also raise the stakes for cybersecurity, as many of them were not built with security in mind.
Agentic AI systems can be attacked. As they interact with enterprise systems, other agents and humans, the cybersecurity attack surface expands, exposing them to new threats such as impersonation attacks, prompt injections and data exfiltration.
The boundaries between appropriate autonomous use and deliberate misuse are blurring as enterprises permit AI agents to use apps on users' behalf more frequently. Malicious agents can also take advantage of the same interfaces that authentic agents employ.
Safeguarding agentic AI in enterprise systems is therefore emerging as one of the defining cybersecurity challenges of the near future.
Recent state-linked campaigns, such as the attack by cyber espionage group UNC3886 reported in Singapore, revealed how adversaries try to exploit trusted enterprise platforms to gain persistent access, and similar risks will arise as agentic systems become more deeply integrated into operations.
Traditional cybersecurity frameworks were designed for systems with predictable behaviors; agentic AI breaks that predictability.
