Organizations hit an inflection point in 2025: AI access expanded, early productivity wins emerged, and confidence in AI’s potential grew. This year, for many businesses, the harder work begins – closing the gap between experimentation and true enterprise transformation.

Business leaders today face an unprecedented challenge: moving beyond pilots to truly integrate AI into the heart of their organizations. Deloitte's 2026 “State of AI in the Enterprise” report found this requires a deliberate shift, redesigning how work gets done. Humans establish a vision and guardrails, while AI provides the insights, speed, and scale to deliver against that ambition. Done correctly, that means reimagining core processes and operating models with AI, ensuring that human strengths, such as judgment, creativity, empathy, and relationship-building, are elevated and not automated.

Where does AI adoption stand?

Access to approved AI tools for employees rose 50% in a year, growing from under 40% to around 60%. Among those with access, 11% of leading companies currently provide workers with near-universal (more than 80%) access to AI-sanctioned tools.

However, enterprise AI remains underutilized, with fewer than 60% of those workers with access using it in their daily workflow. While 25% of respondents said their organization has moved 40% or more of their AI experiments into production to date, 54% expect to reach that level in the next three to six months, demonstrating that a clear pathway to value is achievable.

What’s driving business transformation?

AI’s real-world impact is rising fast. Today, 34% of companies are using AI to deeply transform their businesses, creating new products and services, reinventing core processes, or fundamentally changing business models.

While 25% of leaders now report that AI is having a transformative effect on their companies – more than double from 12% a year ago – most organizations are at the edge of large-scale change. AI is already improving efficiency and productivity, but other outcomes are lagging. Revenue growth remains largely aspirational: 74% of organizations hope to grow revenue through AI in the future, compared to the 20% who say they are doing so today.

What about the workforce?

Within a year, more than one-third of surveyed companies (36%) expect at least 10% of their jobs to be fully automated. In three years, 82% expect the same.

Despite high expectations for automation, 84% of companies have not redesigned jobs or the nature of work itself around AI capabilities. Leaders cite insufficient worker skills as the biggest barrier to integrating AI into existing workflows. Most (53%) are focused on educating employees to raise AI fluency, but far fewer are rearchitecting roles, workflows, and career paths.

As one director of AI and innovation at a major logistics organization explained: “We are reskilling our people on the business side and investing a lot to ensure they adopt the new AI tools so they can deliver bigger, better, and smarter. For example, in the future we would like to see AI enable today’s pricing analysts to become pricing strategists.”

What about sovereign AI?

With sovereign AI taking hold, it matters where technology is built as much as what it can accomplish. More than three in four companies (77%) weigh country of origin in vendor selection, and nearly three in five (58%) now build their AI stacks primarily with local vendors. This signals that geographic sovereignty is now as important as innovation.

That priority is now showing up in planning: 83% of companies view sovereign AI as at least moderately important to their strategic planning, and nearly half rate it as very important or extremely important. As one telecommunications executive noted: “There is skepticism when you’re using something from outside the country. With state-run companies in particular, we’re taking the approach to build distilled small language models for them that meet import/export control rules because we build in their country.”

What’s happening with autonomous agents?

AI agents are scaling faster than guardrails. Nearly three in four companies (74%) plan to deploy agentic AI within two years, yet only 21% report having a mature model for governance.

A financial services company is building agentic workflows to automatically capture meeting actions from video conferences and draft communications. An air carrier is using AI agents to help customers complete common transactions like rebooking flights, freeing up time for human agents to address more complex matters. A manufacturer is leveraging AI to support new product development, finding an optimal balance between competing objectives such as cost and time-to-market.

One telecommunications leader cautioned: “We thought we were going to automate jobs. The truth is, you’re not. You’re going to give existing workers force multipliers where they can be more effective.”

What does the future hold?

Physical AI is quickly becoming operational infrastructure. Fifty-eight percent of companies report already using it to some extent, with adoption projected to hit 80% within two years. Manufacturing, logistics, and defense lead the way globally, and Asia-Pacific markets are driving widespread integration of robotics, autonomous vehicles and drones.

As the untapped edge of AI’s potential becomes clearer, the challenge is activation: bridging the gap from access to meaningful adoption, moving beyond experimentation to operationalizing AI at scale, embedding AI into core business processes, and transforming technology potential into enterprise value.