Seizing the agentic AI advantage

🔗Seizing the agentic AI advantage | McKinsey

1. The Gen AI Paradox: Widespread Deployment, Minimal Impact

McKinsey coins the term "gen AI paradox" to describe a striking disconnect: nearly 80% of organizations have adopted generative AI—but about the same percentage report no significant impact on their bottom line:

• Horizontal use cases—such as enterprise-wide copilots and chatbots—spread rapidly because they’re easy to implement, often through plug-and-play integrations like enabling Microsoft Copilot.

  However, these deliver diffuse, hard-to-measure gains, failing to translate to notable business outcomes.

• Vertical use cases (function-specific applications embedded deeply in processes) hold far greater value potential but remain largely stuck in pilot phases—fewer than 10% scale beyond initial testing. These are impeded by fragmentation, lack of packaged solutions, siloed initiatives, and weak executive sponsorship.

The paradox lies not in the technology’s capability, but in how—and where—it’s applied.

2. From Paradox to Payoff: How Agents Can Scale AI

McKinsey proposes AI agents—autonomous, goal-driven systems—as the breakthrough needed to escape the gen AI paradox:

• Agents are more than reactive tools; they can plan, act, remember, integrate, and coordinate across systems to drive proactive, complex workflows—transforming gen AI from a “tool” to an operating collaborator.

• This shift boosts operational agility and unlocks new revenue-generating opportunities beyond mere productivity gains.

• To truly harness this, organizations must reengineer workflows from the ground up, embedding agents at the core—not just plugging them in superficially.

• The report introduces the architectural concept of an “agentic AI mesh”—a dynamic, composable framework combining both custom and off-the-shelf agents while addressing technical debt and emergent risks.

• Yet, the greatest barrier is human, not technical: building trust, fostering adoption, and governing agent autonomy to prevent uncontrolled deployment.

3. AI Transformation at a Tipping Point: The CEO Mandate in the Agentic Era

The report emphasizes a shift: CEOs must now lead the transition from scattered experimentation to strategic, scalable AI transformation. Key elements of this paradigm shift include:

• From experimentation to industrialized delivery—moving beyond ad‑hoc pilots toward structured, high-impact programs,

• From isolated use cases to core business process integration—with agents orchestrating work instead of waiting on demand.

• From siloed AI teams to cross-functional squads—bringing together business leaders, technologists, and change managers to embed agents effectively and sustainably

• Foundation-building for the agentic era involves:

  • Upskilling the workforce,

  • Adapting AI infrastructure for autonomy,

  • Accelerating data productization,

  • Deploying agent-specific governance mechanisms.

• Ultimately, only the CEO can—and should—make this pivot, bringing focus and accountability to enterprise-wide agentic AI adoption.

4. Conclusion

McKinsey’s report wraps up with a rallying call: it’s time to end the gen AI experimentation chapter and enter the age of strategic, scalable AI driven by agents:

• Organizations must pair clear strategy with tight feedback loops and disciplined governance, ensuring agents are used to reshape decision-making and workflow execution.

• The move to an agentic AI mesh architecture represents not just technological evolution, but transforming the very foundation of operations.

• Only those companies that reimagine their structures and processes—with CEO-led ownership and robust organizational alignment—will unlock the full-scale, sustainable value of agentic AI.