Introduction

AI is changing how companies work. The next big step is the agentic organization - where humans and AI agents run businesses together.

What’s the problem it solves?

Most companies still work like it’s the digital era with people and tools in silos, slow decisions, and limited automation. The agentic model fixes this by combining human judgment with AI agents that can act, decide, and learn in real time.

Quick Summary

The “agentic organization” is McKinsey’s term for the next major change in how companies operate. It means humans and AI agents - both digital and physical - work together at scale. Instead of just using AI tools to speed up work, companies redesign how they work from the ground up so AI becomes part of every process.

Early examples show how this looks in practice. A bank, for example, might use AI agents for home loans, compliance, contracts, and customer support - all managed by a small human team. Companies that adopt this model can lower costs, make decisions faster, and create deeply personalized products or services.

This shift rests on five pillars:

1. Business model: AI agents help companies offer hyperpersonalized services and run at near-zero marginal cost by using proprietary data as their edge.
2. Operating model: Work becomes AI-first, organized around small, outcome-focused agentic teams instead of big, slow hierarchies.
3. Governance: Oversight moves from periodic reviews to real-time, data-driven systems, with humans keeping final control.
4. Workforce and culture: Humans move from “doing tasks” to “steering outcomes.” New roles emerge for AI supervisors, specialists, and augmented workers.
5. Technology and data: A network of AI agents (agentic mesh) links systems and teams together. Data creation and software building become democratized across the organization.

To start this journey, leaders must act boldly. McKinsey advises shifting from linear to exponential thinking, technology-forward to future-back planning, and fear of AI to excitement about its opportunity. The key is to pick one process, rebuild it around AI, and scale from there.

Key Takeaways

• Agentic organizations blend humans and AI agents into a shared system for decision-making and execution.
• Competitive edge will come from proprietary data, AI-first workflows, and hyperpersonalized customer experiences.
• Governance, culture, and talent systems must evolve to manage real-time, autonomous AI operations.
• Flat, outcome-based agentic teams replace traditional hierarchies.
• Leaders must reimagine their business around AI instead of simply adding AI tools to old systems.

What to do

• Redesign one key process (like onboarding or customer service) with AI agents managing end-to-end.
• Build or buy an agentic mesh to connect systems and data across your company.
• Invest in reskilling programs for AI supervisors, specialists, and frontline staff.
• Protect and grow your proprietary data - it will be your main competitive moat.
• Create real-time governance frameworks that keep AI systems compliant and explainable.
• Lead cultural change by framing AI as an opportunity for growth, not a threat to jobs.

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