The accelerated adoption of autonomous AI agents is transforming the way organizations automate critical processes, but it is also creating a new risk surface that many companies still don’t know how to manage, according to cybersecurity experts.
Unlike traditional AI systems, autonomous agents are not limited to answering queries or generating content, but can execute actions, interact with multiple corporate systems, and make decisions independently within complex workflows. This evolution is driving important benefits in terms of efficiency and scalability, but also poses new challenges in security, governance and control.
Among the main risks identified are the possibility of improper escalation of privileges, unauthorized access to sensitive information, execution of unforeseen actions and the propagation of chain errors when these systems operate without adequate human supervision.
In this context, Alberto Román, Sales Director for Central and Southern Europe at Synack, warns that the main challenge is not only technological, but also one of trust and control. “The question is no longer whether organizations are going to adopt autonomous agents, but how they are going to guarantee that their actions can be monitored, audited and validated in critical environments, say cybersecurity specialists.”
Evolution towards hybrid models with automation
The growth of these systems is leading many organizations to rethink their traditional security models, evolving towards hybrid approaches that combine AI automation with human validation at the most sensitive points of the processes.
This approach, known as human-in-the-loop, is emerging as one of the keys to balancing innovation, operational efficiency and risk management in the new generation of AI-based systems with autonomous agents.
“The speed of adoption of these technologies is exceeding, in many cases, the capacity of organizations to establish solid governance and control frameworks. This is generating a growing gap between the operational potential of autonomous agents and the maturity of the mechanisms necessary to supervise them safely,” continues Alberto Román.
As these systems become integrated into critical business processes, from infrastructure management to security task automation, the need to establish clear accountability, traceability and validation models becomes increasingly urgent.
The approach, known as human-in-the-loop, is key to balancing innovation, operational efficiency and risk management
In this scenario, cybersecurity evolves from an approach focused exclusively on threat detection towards a model based on trust, where the ability to verify and validate AI decisions becomes a central element of the protection strategy with autonomous AI agents.
Advanced automation powered by AI
The emergence of autonomous AI agents is part of a broader trend of advanced automation driven by generative artificial intelligence, which is transforming sectors such as cybersecurity, IT operations and business management.
Regulations such as the European Artificial Intelligence Regulation (AI Act) are beginning to establish frameworks for the use of these systems, especially in high-risk use cases.
