ENTERPRISE AI,
INDEXED.

How companies and people actually deploy AI — organizational adoption rates, generative-AI use, enterprise spend, top use cases, and the shift toward AI-native, outcome-based workflows. Every figure primary-sourced and dated.

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The state of play: enterprise AI in 2026

Enterprise AI has crossed from novelty to default. McKinsey’s State of AI 2025 finds that 88% of organizations now use AI in at least one business function, up from 78% a year earlier — reach that is effectively universal across departments and industries.

Yet adoption is not impact. In the same survey, only about 39% of organizations report material EBIT contribution from AI, and roughly a third have moved past piloting to scale it across the enterprise. The sharpest reading comes from MIT’s NANDA initiative, whose “GenAI Divide” report estimates that 95% of generative-AI pilots deliver no measurable P&L return — despite $30–40 billion in enterprise spend.

The frontier is now agents. Google Cloud’s ROI of AI 2025 study reports that 52% of executives say their organization has deployed AI agents in production. The pattern holds: broad deployment, uneven payoff. The dividing line is execution, not access.

• Adoption is near-universal. 88% of organizations use AI in at least one function (McKinsey, 2025) — advantage now comes from depth, not presence.
• Value trails reach. Only ~39% see EBIT impact and 95% of gen-AI pilots show no P&L return (McKinsey; MIT NANDA, 2025).
• Agents are scaling fast. 52% of enterprises have deployed AI agents (Google Cloud, 2025), making disciplined execution the real differentiator.