Four tensions that organizations face when using agentic AI:

1. Scalability versus adaptability. Constraining agentic systems too much limits their effectiveness, while granting too much freedom can introduce unpredictability.
   
2. Experience versus expediency. Agentic AI forces organizations to rethink how they assess cost, timing, and return on investment.
   
3. Supervision versus autonomy. Excessive supervision of agentic AI systems can negate the benefits of autonomy, while insufficient oversight exposes organizations to risks.
   
4. Retrofit versus reengineer. Organizations must decide whether to quickly retrofit agentic AI into existing workflows or take the time to reimagine those workflows altogether.
   

A growing share of organizations are no longer just experimenting with artificial intelligence — they’re beginning to delegate work to it. According to a new report from MIT Sloan Management Review and Boston Consulting Group, “The Emerging Agentic Enterprise: How Leaders Must Navigate a New Age of AI,” more than a third of surveyed companies are already deploying agentic AI systems that can plan, act, and learn autonomously, with another 44% planning to do so. These systems don’t just assist employees and automate isolated tasks; they pursue goals, coordinate across workflows, and adapt based on outcomes.

Full opinion : How to navigate the age of agentic AI.