"Excitement about AI agents may seem over the top, but remember: It takes work and planning on the ground to make these tools productive. Top-level actions include giving agents freedom, but not too much freedom, while also rethinking traditional return-on-investment measures. Also: 3 ways AI agents will make your job unrecognizable in the next few years Effective AI development and management require making informed choices in control, investment, governance, and design, according to Kristin Burnham, writing in MIT Sloan Management Review."
"Reviewing recent research conducted by Sloan and Boston Consulting Group, she cites the "tensions" that AI agent developers and proponents need to be aware of: Constraining agentic systems too much limits their effectiveness, while granting too much freedom can introduce unpredictability. Agentic AI forces organizations to rethink how they assess cost, timing, and return on investment. Organizations must decide whether to quickly retrofit agentic AI into existing workflows or take the time to reimagine those workflows altogether."
Agent deployments require different planning and operational approaches than traditional software launches. Governance must be central because agents can act confidently but incorrectly, creating risk. Teams must balance autonomy and control to preserve effectiveness without introducing unpredictability. Organizations need to rethink cost, timing, and return-on-investment measures for agentic systems. Decisions must be made about retrofitting agents into existing workflows versus reimagining workflows for agentic capabilities. New operational roles and practices, often called AgentOps, emerge to manage deployment, monitoring, and governance at scale to make agents productive and trustworthy.
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