The State of AI in the Enterprise 2026 by Deloitte

The State of AI in the Enterprise report by Deloitte captures a pivotal moment of acceleration and transformation as organizations move from experimentation to enterprise-wide scaling. Based on a survey of more than 3,200 business and IT leaders across 24 countries, the report explores how wider worker access to artificial intelligence, early productivity gains and strategic trends like Sovereign AI, Agentic AI and Physical AI are reshaping the enterprise landscape. While momentum is building, the findings highlight a persistent gap between ambition and activation, emphasizing that true success requires going beyond basic efficiencies to fundamentally redesign work, build robust governance and modernize technology infrastructures.

Key Insights 

• Survey Scope: The report surveyed 3,235 director-level to C-suite-level respondents across 6 industries and 24 countries.
• Worker Access Expansion: Surveyed companies broadened worker access to AI by 50% in just one year, growing from fewer than 40% to around 60% of workers equipped with sanctioned AI tools.
• Universal Access: 11% of leading companies currently provide workers with near-universal access (more than 80%) to sanctioned AI tools.
• Production Deployment Rates: Only 25% of respondents reported moving 40% or more of their AI experiments into production to date, but 54% expect to reach that level within the next three to six months.
• Transformative Business Impact: 25% of leaders reported that AI is having a transformative effect on their companies, more than double the 12% reported a year prior.
• Investment and Confidence Surges: 84% of organizations are increasing their AI investments, and 78% of leaders report greater confidence in the technology.
• Realized vs. Intended Revenue Growth: While 74% of organizations hope to grow revenue through AI initiatives in the future, only 20% are achieving revenue growth today.
• Current Benefits Achieved: Today, 66% improve efficiency and productivity, 60% enhance decision-making and data-driven insights, 53% reduce costs, 40% enhance client/customer relationships, 38% improve products/services and foster innovation, and 20% increase revenue.
• Transformation Approaches: 34% of companies are using AI to deeply transform products, processes, and business models while 30% are redesigning key processes around AI and 37% are using AI at a surface level with little or no change to existing processes.
• Job Automation Expectations: More than a third (36%) of surveyed companies expect at least 10% of their jobs to be fully automated within a year, and 82% expect at least 10% of their jobs to be fully automated when looking out three years.
• Organizational Structure Shifts: 53% of companies have considered pod-based or non-hierarchical models since fewer roles require supervision of large teams, though only 16% have moved to such models to a great or maximum extent.
• Job Redesign Lag: 84% of companies have not redesigned jobs around AI capabilities.
• Talent Strategy Adjustments: 53% are educating the broader workforce to raise AI fluency, 48% are assessing changes to skill supply and demand, 36% provide performance-based incentives for leveraging AI, 33% are combining or reimagining organizations, 30% are measuring worker trust, 30% are changing the balance between full-time/contract/gig workers, 30% are redesigning career paths, 30% are assessing target talent acquisition and hiring specialized talent, and 19% are designing upskilling and reskilling strategies.
• Worker Sentiment: 13% of non-technical workers are highly enthusiastic and proactively seeking to use AI, 55% are open to exploring it, 21% prefer not to use AI but will do so if required, and 4% actively distrust and avoid it.
• Sovereign AI Importance: More than 8 in 10 companies (83%) view sovereign AI as at least moderately important to strategic planning, with 43% rating it as very or extremely important.
• Concern Over Foreign Reliance: 66% of companies express at least moderate concern about reliance on foreign-owned AI technologies and infrastructure, including 22% who are very or extremely concerned.
• Vendor Selection & Local Stacks: 77% of surveyed companies factor an AI solution’s country of origin into vendor selection decisions, and nearly 3 in 5 (58%) build their AI stacks primarily with local vendors.
• Geographic Variances in Foreign Reliance: Only 11% of companies in the Americas rely on foreign-sourced solutions for the majority of their AI stack, compared to 32% of companies in Europe, the Middle East, and Africa (EMEA).
• Agentic AI Deployment Timeline: While 23% of companies use agentic AI at least moderately today, nearly 3 in 4 (74%) plan to deploy agentic AI within two years, with 23% expecting to use it extensively and 5% fully integrating it.
• Customization of Agents: 85% of companies expect to customize agents to fit the unique needs of their business.
• Agentic Governance Maturity: Only 1 in 5 (21%) companies report currently having a mature model for governance of autonomous agents.
• Top AI Risks: Companies are most concerned about data privacy and/or security (73%), legal, IP, or regulatory compliance (50%), governance capabilities and oversight (46%), model quality, consistency, and explainability (46%), and workforce impact (30%).
• Physical AI Integration: 58% of companies report at least limited use of physical AI today (with 18% leveraging it to a moderate or greater extent), and adoption is projected to hit 80% within two years (with 15% using it extensively and 3% fully integrated).
• Regional Physical AI Adoption: In Asia Pacific (AP), 71% report at least minimal physical AI use (and 90% expect it in two years), compared to 56% today and 77% in two years for the Americas, and 56% today and 81% in two years for EMEA.
• Physical AI Impact Areas: The types of physical AI expected to have the greatest industry impact include intelligent security systems/smart monitoring (21%), collaborative robotics (20%), digital twins (19%), IoT-driven retail (16%), autonomous logistics (13%), and smart materials (7%).
• Preparedness Ratings: 42% of companies believe their strategy is highly prepared for AI adoption (up 3 percentage points), 30% feel prepared in risk and governance (up 6 points), 43% in technical infrastructure (down 2 points), 40% in data management (down 3 points), and 20% in talent (down 4 points).
• Generative AI Dominance: Nearly 80% to 90% of new use cases are generative AI.

Conclusion

The findings from Deloitte’s 2026 report demonstrate that while organizations have made immense strides in broadening AI access and testing initial pilot use cases, the true challenge moving forward lies in execution and activation. Enterprises must look past superficial productivity metrics and short-term experimentation to fundamentally redesign workflows, establish rigorous cross-functional governance, and modernize data and technical infrastructures. By thoughtfully addressing emerging frontiers like sovereign, agentic, and physical AI, business leaders can successfully bridge the gap between technological potential and lasting enterprise value.

You can download the full report here.