Enterprises are entering a new phase of AI maturity. Since our April survey, companies have moved from identifying use cases to deploying them at scale. They’re also beginning to rethink how the human workforce fits alongside increasingly autonomous AI systems.

As in previous quarters, for our State of Enterprise Tech Spending report we surveyed 100 CXOs who collectively represent over $35 billion in annual technology spending. Our goal was, as always, to gauge the budget planning and overall sentiment of large, enterprise technology buyers. The survey was conducted during the last week of October and first week of November 2025.

A recurring theme in leadership conversations adds color commentary to the survey findings. As AI evolves, human work shifts from “in the loop” to “on the loop,” and eventually toward orchestrating networks of agents. Some leaders describe the emerging model as an “octopus” structure—intelligence distributed at the edges, coordinated by a central brain. Humans control the operation, while AI orchestrates the mission, making AI intelligence a two-way street. This effectively allows agents to surface new intelligence for humans to evaluate and possibly act upon, while humans continue using AI to research their own hunches. The next evolution will be how humans work, both with each other as well as with other agents.

To catch up on previous reports, check out what we published in March 2023, September 2023, April 2024, September 2024 and April 2025.

Einige Highlights aus der Umfrage:

• AI use cases scale rapidly, with deployments now the norm.

Enterprises have identified an average of 88 Gen AI use cases and increased production deployments nearly 4x year over year, with 74 percent already implementing Gen AI and all respondents planning to do so within two years.

• Budgets stay steady, but AI absorbs a larger share of spend.

Sixty-five percent of organizations expect budget increases, and Gen AI, LLMs and agentic AI now rank as the top spending priorities as companies reallocate capital toward automation, observability and AI-native operations.

• Agentic AI adoption accelerates into early-majority territory.

Thirty-three percent of enterprises already run agentic AI in production, and another 48 percent plan to deploy it within 12 months. Customer support, IT operations and software development are emerging as the leading domains for adoption.

• Human roles evolve as enterprises embrace autonomous workflows.

Most enterprises view AI as augmenting, not replacing people: 45% are focused on augmentation, only 1% on primarily replacing, and 48% pursuing a mix of both.

That said, 69% of companies are piloting agentic AI workflows, 42 percent are scaling them across functions, and nearly 60 percent expect fully autonomous workflows within two years, driving demand for oversight, orchestration and governance roles.

• AI is shifting the balance of power in the C-suite.

Twenty-three percent of enterprises now have a Chief AI Officer—rising to 40 percent among organizations with more than $1 billion in annual tech spend and 34% among those deploying agentic AI. These findings underscore the cross-functional complexity of these next-gen systems and reflect a shift from experimentation to strategic AI governance and accountability.

• Software development is now AI-native by default.

AI coding assistants are now delivering 10–20 percent efficiency gains, with tools like GitHub Copilot and Cursor embedded in daily workflows and multi-model AI strategies becoming standard across enterprise engineering teams.

We see strong opportunities for early-stage technology startups in these survey findings. Check out the full report here to learn more:

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