Reza Vatankhah Barenji and Sina Khoshgoftar from Nottingham Trent think AI should fix problems automatically, not just detect them:

As Agentic AI continues to evolve, it holds the promise of redefining how complex systems are monitored, understood, and controlled—shifting the role of human operators from reactive problem-solvers to strategic supervisors in an ecosystem of intelligent, autonomous agents.

We've been managing complex systems reactively. Build dashboards, set up alerts, wait for humans to fix things when they break. AI helps with diagnosis, but humans still make the final call on intervention.

The authors argue this doesn't scale. Systems are getting too complex for human operators to manage every problem manually.

This paper describes a move away from simply detecting anomalies to building agentic systems that can independently reason about, plan, and execute a response. It’s a move from passive observation to active participation.

This changes the design challenge completely. Instead of building dashboards for humans, you're designing the autonomous agent itself. Its goals, boundaries, decision-making processes.

How do you build a system you can trust to act independently in high-stakes environments? Humans become "strategic supervisors" rather than reactive problem-solvers.

We're shifting from designing interfaces for people to designing the constitution of our autonomous digital colleagues. No pressure.