Seizing the agentic AI advantage
đGenAI paradox: exploring AI use cases | McKinsey
The âGen AI paradoxâ: nearly 80âŻ% of firms use generative AI, yet most report little impact . McKinsey argues for shifting from reactive gen AI to proactive, agentic AIâequipped with autonomy, planning, memory, and integration. They introduce the âagentic AI meshâ architecture and stress that success requires addressing both technical and human challenges: trust, adoption, and governance. Organizational transformation must be driven by the CEO, with a move from siloed pilots to strategic programs, workforce upskilling, infrastructure adaptation, data productization, and agent-specific regulation.
The âGen AI paradoxâ: the widespread adoption of generative AI has yielded minimal financial impact. This is because organizations deploy horizontal solutionsâchatbots, copilotsâwithout reimagining core processes . AI remains reactive; to unlock value, it must evolve to proactive, goal-driven systems.
âAgentic AI mesh" implies systems that plan, act autonomously, remember, and integrate across workflows . It distinguishes single-agent from multiagent orchestration. Real-world examples include call centers, HR, finance, and legacy system modernization.
McKinsey emphasizes that only the CEO can lead this strategic shift . Businesses must move from isolated pilots to strategic programs, from siloed AI efforts to cross-functional units. This entails redesigning operating models, infrastructure, governance (costs, ethics, accountability), roles, metrics, and corporate culture.
Generative AI was a prelude; true competitive advantage lies in agentic AI's ability to automate complex processes and unlock new revenue opportunities. Realizing this potential requires holistic transformationâprocess redesign, infrastructure, talent, governanceâled by the CEO.