Excessive agency directly proportional to over-permissioning: Organizations are worried about the level of autonomy AI introduces into their operational framework. Nearly three-quarters of organizations say agents often receive more access than necessary. It’s this excessive agency that needs to be reined in.In practice, unchecked autonomy within a particular workflow means the agent can access systems it doesn’t need, execute actions outside its predetermined role and interact with external systems beyond predefined parameters. This means organizations are not just looking at a ‘wrong answer’ as the biggest risk, but ‘unauthorized action.’ This action may involve unintended data exposure, unauthorized commands or integrity-impacting changes that are difficult to unwind.Over-permissioning is a sneaky beast. I’ve seen it slowly creep into agentic AI workflows, usually driven by three common factors:
The people in charge, in their ‘wisdom,’ enable a broad range of tools/APIs to make the agent even more useful.There might be some integration problems, and elevated access is given to make integration work smoothly, which means extra permissions that exceed the safe-use threshold.Agents can decide with fewer human checkpoints, especially for actions that have a tangible impact. This can stem from a blind trust in AI and a focus on being an execution-first business.
3 systemic risks in agentic AI workflows: Less than half of businesses have adopted formal risk management frameworks for AI, and I believe that’s where the real challenge with agentic AI begins. It’s not about what it can do, but that its actions become harder to observe and govern once it operates across connected systems.First, many models are effectively black boxes. Opaque internal workings make it harder to verify outputs, explain decisions or confidently audit what happened after the fact.Second, capability invites overreliance. In conversations I’ve had with CISOs, a consistent theme emerges. As agents appear to “handle it,” humans step back and critical reviews thin out. The result is mistakes and biases persisting longer because fewer people are watching closely, especially dangerous in high-stakes environments.Thirdly, attackers don’t need to compromise the model itself if they can compromise what the agent reads or the services feeding it. Connected workflows create supply-chain-style attack modes, where upstream manipulation becomes the lever.
The road toward re-permissioning: Controlling agency: Re-permissioning is not about limiting the autonomy of AI agents, but more about controlling them appropriately. AI agents execute, and we need them to execute well, but we must implement a continuous permission audit to identify agents slowly climbing the ‘agency’ ladder.Organizations must have complete visibility so they can evaluate agentic AI interactions, flag irregular behaviors, verify if permissions conform to policy and use tabletop real-world exercises like prompt-injection tests to guard against vulnerabilities. Also, subscribe to a human-in-the-loop workflow in which human oversight is mandatory when sensitive data, financial decisions, access changes or major operational updates are involved.It’s also necessary to avoid giving agents tools ‘just in case they need them.’ Instead, implement least-privilege context sharing, limiting the agent’s view and tool access to only what the task truly requires.Finally, let me emphasize that you shouldn’t forget the agent AI supply chain that includes integration, libraries, APIs and third parties. These need to be vetted, patched and secured with tight network controls to build a trusted ecosystem and reduce the risk of upstream manipulation.If AI agents are treated like harmless helpers, they’ll be permissioned like harmless helpers, and excessive agency becomes normalized.We must pump the brakes on the inevitability of unchecked autonomy. Take control of broader functionality and permissions; focus on instilling oversight where it matters. Agents can enhance operations, but only if they’re governed as actors within guardrails and not trusted by default.This article is published as part of the Foundry Expert Contributor Network.Want to join?
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