AI Optimisation Agents for Continuous Performance Tuning

Enterprises are exploring AI agents that continuously optimise digital systems rather than relying on periodic tuning cycles. This content explains how optimisation agents monitor performance signals, test variations, and autonomously adjust parameters across applications and workflows. It highlights a shift toward closed-loop optimisation where experimentation, evaluation, and deployment are embedded into runtime operations. Technology leaders should assess implications for control, observability, and how much decision authority is delegated to autonomous systems.