Top Highlights
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Nearly 74% of companies plan to deploy agentic AI in two years, but only 21% have mature governance models for autonomous agents.
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Key concerns for executives include data privacy (73%), legal compliance (50%), and oversight (46%), highlighting significant risk areas.
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A robust control plane is essential for governing, observing, and securing AI agents, enabling scalable, safe, and repeatable automation.
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Effective governance ensures transparency and safety, preventing unpredictable failures and facilitating the transition from pilots to enterprise-wide AI deployment.
Many Companies Plan to Use Agentic AI Soon
A recent report shows that nearly 74% of companies want to deploy autonomous AI within the next two years. However, only 21% of these companies have a mature system to manage these AI agents. This gap raises concerns about how well businesses are prepared for the rise of agentic AI.
Data Privacy and Security Are Top Priorities
Executives worry most about data privacy and security, with 73% citing it as their main concern. Legal issues and regulatory compliance follow at 50%, while 46% focus on governance and oversight. These worries highlight the need for better control over AI systems.
Understanding How AI Agents Operate Is Critical
Many businesses do not realize they treat AI agents as “first-class citizens.” This approach can create blind spots and security risks. Without proper oversight, AI tools may act in unpredictable ways, exposing data and processes.
The Importance of a Control Plane
To manage AI agents effectively, companies need a control plane. This is a centralized system that governs who can run what agents, with what permissions, and under which policies. Without it, managing many AI agents becomes difficult and risky.
Why Governance Matters
Good governance makes it clear what each AI agent is doing. It answers questions like: What data is used? Under which rules? Who is responsible? This clarity helps companies move from small tests to large-scale AI applications safely. Without strong governance, AI systems may fail unpredictably and cause problems across organizations.
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