McKinsey: 62% of Organizations Are Already Experimenting with AI Agents and Context Engineering Is the Strategic Shift
McKinsey: Agentic AI Is the Next Frontier
McKinsey, the world's most prestigious strategic consulting firm, has published data confirming that agentic AI has moved from being a future promise to an enterprise reality.
The Current State of Agentic AI
McKinsey's State of AI 2025 report reveals figures that demonstrate the speed of adoption:
- 62% of surveyed organizations are at least experimenting with AI agents
- 23% are already scaling agentic AI systems somewhere in their enterprises
These figures indicate that most organizations are already on the path to agentic adoption, and nearly a quarter have moved beyond the experimental phase.
From Model Training to System Orchestration
McKinsey identifies context engineering as the strategic shift from model training to system orchestration in enterprise AI.
This paradigm shift is fundamental: it is no longer about building better models, but about building better systems that provide existing models with the right context to produce valuable results.
Redesigning Workflows, Not Just Plugging In AI
The report confirms that organizations redesigning workflows around AI (not just plugging it into existing processes) are capturing the most value.
This means that context management is not a technical add-on but an organizational transformation that requires rethinking how information flows between people, systems, and AI agents.
McKinsey's Global Tech Agenda for 2026
In their McKinsey Global Tech Agenda 2026, the firm reinforces that agentic AI will be the primary driver of enterprise transformation, and that organizations need specific infrastructure to manage the context that feeds these agents.
Practical Implications
For organizations in the experimentation (62%) or scaling (23%) phase, context management becomes an immediate priority:
- Agents need structured and governed context to function reliably
- Context must be versioned and auditable to meet compliance requirements
- Context distribution must be automatic and real-time to support agentic speed
Contextaify addresses each of these requirements, providing a platform where context is managed with the same rigor as source code.
Sources:
- The State of AI: Global Survey 2025 (McKinsey, November 2025)
- McKinsey Global Tech Agenda 2026 (McKinsey, February 2026)