The State of AI in the Enterprise

The untapped edge

Organizations today stand at the untapped edge of AI's potential. Our 2026 AI report reveals that success hinges on the ability to move boldly from ambition to activation.

Key findings from this year's AI report:

1. AI is moving from the pilot and experimentation phase to enterprise scaling as worker access to AI expands.

• Workforce access to AI has expanded by 50% in just one year—growing from fewer than 40% to around 60% of workers now equipped with sanctioned AI tools.
• 11% of leading companies currently provide workers with near-universal (>80%) access to sanctioned AI tools; among those workers with access, fewer than 60% use it in their daily workflow, a pattern that remains largely unchanged from last year.
• 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.

2. AI transformation reveals productivity for most, business reimagination for a few.

• AI’s real-world business impact is rising fast, with 25% of leaders now reporting that AI is having a transformative effect on their companies—more than double from 12% a year ago.
• Trust and investment are also surging, with 84% of organizations increasing their AI investments and 78% of leaders reporting greater confidence in the technology. Yet, most companies are only at the edge of large-scale AI-driven transformation.
• 74% of organizations are hoping to grow revenue through their AI initiatives in the future compared to just 20% that are already doing so.
• One-third of companies (or 34%) are already starting to use AI to deeply transform their businesses— creating new products and services, reinventing core processes, or even fundamentally changing their business models.
• Another third of companies (or 30%) are redesigning key processes around AI but keeping their business models intact.
• And the remaining third of companies (or 37%) are using AI at a more surface level, with little or no change to existing processes.

3. Companies are focused on building AI fluency instead of redesigning work around AI. 

• Within a year, 36% of survey companies expect at least 10% of their jobs to be fully automated. The majority of surveyed companies (or 82%) expect at least 10% of their jobs to be fully automated when looking out three years.
• Despite high expectations for automation, 84% of companies have not redesigned jobs around AI capabilities.
• Entry-level and task-aligned roles could be most affected, as automation may replace common, time-consuming tasks; 53% of organizations have considered pod-based or non-hierarchical models since fewer roles require supervision of large teams, with only 16% having moved to such models to a great or maximum extent.
• While 13% of non-technical workers are highly enthusiastic about AI and are proactively seeking to use it—and 55% are at least open to exploring it— skepticism remains; 21% prefer not to use AI but will do so if required, and 4% actively distrust and avoid it.
• Fewer than half of companies are making significant adjustments to their talent strategies, with most (53%) simply focusing on educating employees to raise AI fluency.

4. Sovereign AI is now a strategic imperative, and solution origin now plays a crucial role in vendor and infrastructure decisions.

• More than 8 in 10 companies (83%) view sovereign AI as at least moderately important to their strategic planning, and nearly half (43%) rate it as very important or extremely important.
• 66% of companies express at least moderate concern about reliance on foreign-owned AI technologies and infrastructure, with 22% very concerned or extremely concerned.
• More than 3 in 4 companies (77%) now factor an AI solution’s country of origin into their vendor selection decisions, and nearly 3 in 5 (58%) now build their AI stacks primarily with local vendors—which signals sovereignty is now as important as innovation.
• Only 11% of companies in the Americas rely on foreign[1]sourced solutions for the majority of their AI stack, compared to 32% of Europe/Middle East/Africa (EMEA) companies.

5. Agentic AI adoption is outpacing the development of governance and oversight.

• 23% of companies are using agentic AI at least moderately. However, within the next two years, agentic AI is expected to become nearly ubiquitous, with nearly 3 in 4 companies (74%) using it at least moderately, 23% using it extensively, and 5% fully integrating it as a core component of their operations.
• Commercial software vendors offer a wide range of AI agents for various use cases; however, 85% of companies expect to customize agents to fit the unique needs of their business.
• One in 5 (21%) companies surveyed report currently having a mature model for governance of autonomous agents.
• The AI risks companies are most worried about all relate to governance—data privacy and security tops the list at 73%, followed by legal, intellectual property, and regulatory compliance (50%), governance capabilities and oversight (46%), and model quality, consistency, and explainability (46%).

6. Physical AI, such as robotics and autonomous devices, is now integral to many operations, with adoption expected to surge dramatically in just two years.

• Physical AI integration is already expanding, with 58% of companies reporting at least limited use of physical AI, and among these, 18% are leveraging it to a moderate or greater extent.
• The percentage of companies using physical AI in any capacity is expected to reach 80% within two years— with 15% using physical AI extensively and 3% fully integrating it as a core element of their operations.
• As physical AI gains broader adoption, certain types are expected to have a bigger long-term impact than others: intelligent security systems and/or smart monitoring (21%); collaborative robotics (20%); and digital twins (19%).

7. Leaders feel more strategically ready for AI than operationally ready in infrastructure and talent. 

• Despite the rapid evolution of AI beyond GenAI to agentic and physical AI, 42% of companies believe their strategy is highly prepared for AI adoption and 30% say the same about risk and governance, both rising since last year’s report (+3 and +6 percentage points, respectively).
• Meanwhile, perceptions of high preparedness have shifted down compared with last year for technical infrastructure (43%), data management (40%), and talent (20%), revealing the persistent challenge of modernizing systems and skills at the speed of innovation.
• Most respondents believe that resolving the key challenges for their organization’s priority AI initiatives will take more than a year—far too long in today’s fast[1]moving, hypercompetitive marketplace.