🔗GenAI paradox: exploring AI use cases | McKinsey
The “Gen AI paradox”: nearly 80 % of firms use generative AI, yet most report little impact . McKinsey argues for shifting from reactive gen AI to proactive, agentic AI—equipped with autonomy, planning, memory, and integration. They introduce the “agentic AI mesh” 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 “Gen AI paradox”: the widespread adoption of generative AI has yielded minimal financial impact. This is because organizations deploy horizontal solutions—chatbots, copilots—without reimagining core processes . AI remains reactive; to unlock value, it must evolve to proactive, goal-driven systems.
“Agentic 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 transformation—process redesign, infrastructure, talent, governance—led by the CEO.