Agents Are Scaling Faster Than the Guardrails: Deloitte’s State of AI in the Enterprise 2026
Key takeaways
74% of companies plan to deploy agentic AI within two years, but only 21% report a mature governance model for autonomous agents.
77% factor an AI solution's country of origin into vendor selection; 83% call data residency and in-region compute at least moderately important.
Only 20% already grow revenue through AI, while 74% expect to; for now, efficiency gains come first.
84% have not redesigned jobs around AI; 53% have considered pod-based team structures, but only 16% have moved to them substantially.
Deloitte's annual State of AI in the Enterprise report is based on a survey of 3,235 director- to C-level respondents across six industries and 24 countries, conducted in August and September 2025 and published in January 2026. Its subtitle — the untapped edge — reflects the main finding: AI is spreading quickly inside companies, but most of its value is still ahead of them.
From pilots to scale — slowly
Worker access to sanctioned AI tools grew by about 50% in one year, from under 40% to around 60% of employees. Among workers who have access, fewer than 60% use it daily, a share that has barely changed.
Only 25% of organisations have moved 40% or more of their AI experiments into production, although 54% expect to reach that level within three to six months. Deloitte calls the gap the proof-of-concept trap: pilots run with small teams, clean data and isolated environments, while production requires integration, security reviews, compliance checks, monitoring and maintenance. Use cases planned for three months can stretch to eighteen once those requirements appear.
Productivity now, revenue later
25% of leaders say AI is already transforming their company, up from 12% a year earlier. 84% are increasing AI investment. But the benefits are concentrated in efficiency:
66% report improved efficiency and productivity today.
Only 20% report revenue growth from AI today, while 74% hope to achieve it.
Organisations divide roughly into thirds: 34% are starting to transform products, processes or business models with AI; 30% are redesigning key processes while keeping the business model; 37% use AI at a surface level with little change to existing processes.
Agents are coming before governance
The headline for engineering and risk leaders: 74% of companies plan to deploy agentic AI within two years, but only 21% report having a mature governance model for autonomous agents.
That gap matters because agents act rather than suggest. An agent that can send messages, change records or trigger payments needs defined permissions, logging, escalation rules and a person accountable for its behaviour. Without these, the first visible error tends to halt the whole programme.
Where AI is built now matters
Deloitte treats sovereign AI as a boardroom issue:
83% say data residency and in-country or in-region compute are at least moderately important to strategic planning; 43% call them very or extremely important.
66% are at least moderately concerned about reliance on foreign-owned AI technology and infrastructure.
77% factor an AI solution's country of origin into vendor selection, and 58% build their AI stacks primarily with local vendors.
For companies operating across the EU, the UK, the Middle East and Asia-Pacific, this means architectures that can run models in specific regions — or self-hosted — and vendors who can document where data goes.
Work redesign lags
Expectations of automation are high: 36% of companies expect at least 10% of jobs to be fully automated within a year, and 82% within three years. Yet 84% have not redesigned jobs around AI capabilities. Leaders name insufficient worker skills as the biggest barrier to integration, but fewer than half are making significant changes to their talent strategy; most focus on general AI training.
Team structures are starting to move. As fewer roles require supervising large teams, 53% of companies have considered pod-based or non-hierarchical models — but only 16% have adopted them to a great extent.
Physical AI is already in operations
58% of companies already use physical AI — robotics, autonomous vehicles, drones — to some extent, and adoption is projected to reach 80% within two years, with Asia-Pacific markets leading.
Preparedness
42% believe their strategy is highly prepared for AI, and 30% say the same of risk and governance — both up from last year. Confidence in technical infrastructure, data management and talent fell slightly, which suggests that the operational work is harder than the strategic work.
What follows for 2027–2028
The survey describes a sequence many organisations are now in. Access and pilots are mostly solved. The next constraints are integration with real systems, governance for agents that act, regional requirements for data and models, and teams organised around outcomes rather than tasks. Each of these is primarily an engineering and operating-model problem rather than a model-selection problem.