Enabling agent-first process redesign

MIT Technology Review / 4/7/2026

💬 OpinionSignals & Early TrendsIdeas & Deep Analysis

共有:

Key Points

The article argues that AI agents enable dynamic, adaptive, and optimization-oriented process execution, contrasting them with static rules-based systems.
It emphasizes that organizations should redesign workflows to be agent-first, rather than adding agents as an afterthought to fragmented legacy processes.
It notes that agent autonomy depends on real-time interaction with data, people, and other agents to carry out complete end-to-end workflows.
It highlights a shift away from traditional optimization approaches toward process architectures that support agent collaboration and continual adaptation.

Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, people, and other agents in real time, AI agents can execute entire workflows autonomously. But unlocking their potential requires redesigning processes around agents rather than bolting them onto fragmented legacy workflows using traditional optimization methods. Companies…