After a year of experimentation with generative AI, most companies have little to show for it on their balance sheets. But a new report from McKinsey & Co. says the solution isn’t more copilots or chatbots — it’s autonomous AI agents capable of reengineering core business processes.
In its latest research brief, “Seizing the Agentic AI Advantage,” McKinsey’s QuantumBlack unit argues that AI agents — not just generative AI tools — will be the real driver of enterprise transformation in the years ahead. These agents, the firm says, can:
- Act independently
- Plan across multiple steps
- Adapt to real-time feedback
- Deliver measurable gains across functions like finance, operations, and customer service
“Gen AI is everywhere — except in the company P&L,” the report states.
While 78% of companies have implemented some form of generative AI, McKinsey found that most of these deployments have failed to materially impact earnings. The firm attributes this disconnect — what it calls the “Gen AI paradox” — to an overreliance on horizontal tools like chatbots, copilots, and internal Q&A assistants that increase individual productivity but rarely scale across the enterprise.
How McKinsey sees companies benefiting most from AI agents
What’s needed now, McKinsey argues, is a shift from task-based productivity tools to outcome-driven systems. Enter AI agents — systems that can proactively act, make decisions, and automate complex workflows with minimal human oversight.
“These agents don’t just respond to prompts — they plan, adapt, and execute,” the report says. “They represent a fundamentally different paradigm, with the potential to reshape how work gets done.”
Some early adopters are already seeing returns. One global bank cut its IT modernization timelines by over 50% by deploying agents to assist engineering teams. Another firm used multiagent systems to clean up and interpret complex market data, unlocking $3 million in projected annual savings. In a third example, a financial institution restructured its credit memo process, resulting in a 60% productivity gain for analysts.
But the shift won’t be easy. McKinsey warns that most AI deployments remain stuck in pilot purgatory, with fewer than 10% of vertical use cases reaching production. Technical debt, organizational silos, and lack of leadership alignment remain major barriers.
How to overcome AI challenges
To overcome those hurdles, the firm recommends building an “agentic AI mesh” — a modular, governed system for managing distributed AI agents across teams, tools, and data. Crucially, McKinsey says business leaders must lead this transition, not just IT departments.
“Capturing the full value of agentic AI requires rethinking how companies operate — not just accelerating what they already do,” said Michael Chui, partner at McKinsey and co-author of the report.
The firm outlines a four-step playbook for scaling AI agents:
- Prioritize vertical use cases tied to core business metrics
- Shut down low-impact pilots
- Reengineer workflows to accommodate AI integration
- Embed clear governance to manage risk and accountability
“AI agents mark the start of a new chapter in enterprise transformation,” McKinsey concludes. “The technology is ready. Now it’s time for leadership to catch up.”
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