Companies have become accustomed over the past few years to clearly defined processes. New applications, external services, and access permissions go through approval and control by IT teams. However, with the rise of AI agents, this situation is beginning to change.
Unlike traditional AI tools, AI agents are capable of independently performing tasks, connecting applications, retrieving information, and coordinating entire workflows. Gradually, they are shifting from assistants to active participants in the corporate environment. This raises a new question: who controls their decisions?
Organizations have so far focused on managing users, devices, and applications. AI agents, however, do not fully fit into this framework. They can operate across multiple systems, use external services, and execute tasks with minimal human intervention. Traditional IT rules may therefore no longer be sufficient.
Companies will need to start asking new questions:
- Who is responsible for a specific AI agent?
- What permissions has it been granted?
- Which systems and services does it use?
- Who oversees its activities?
Without clearly defined rules, AI may become another layer of corporate processes over which organizations gradually lose visibility.
AI governance is becoming essential
This is why AI governance is coming to the forefront — a set of rules and processes that help organizations deploy, monitor, and manage AI in a controlled way. The goal is not to restrict innovation. On the contrary, it is to ensure that AI operates transparently, predictably, and in line with internal organizational policies.
Just as companies today manage user accounts and access rights, they will need to adopt a similar approach for autonomous AI systems.
From strategy to practical oversight
As the use of AI agents grows, it is becoming clear that rules alone will not be enough. Organizations will also need tools that give them visibility into how AI behaves in real environments.
This is why Radware is expanding its portfolio with a solution called Agentic AI Protection, focused on monitoring AI agents, identifying risky behavior, and improving control over which systems and services AI interacts with.
Combined with API security and AI Security Posture Management (AI-SPM), companies gain a more comprehensive view of their AI environment and can identify potential risks early, before they become real problems.
The question is no longer whether AI agents will enter organizations. Many already actively use them today. The real challenge is establishing processes that ensure their decisions remain under control. The future of artificial intelligence will depend not only on what AI can do, but primarily on how organizations govern it.
Source: The Invisible Supply Chain: How AI Agents Create New Third- Party Risk Without Human Awareness
