Gartner predicts 40% of enterprise applications to run task-specific AI agents by the end of 2026. That’s up from less than 5% in 2025, one of the fastest adoption jumps the research firm has tracked in enterprise software.
The shift marks a change in what AI does inside a company. Until now, most AI tools have acted as assistants: they help with a task but still need a person to guide them. Agents work differently. They’re built to complete a job on their own, from start to finish, with far less human input.
Gartner’s Anushree Verma says this is just the early stage. Assistants come first, task-specific agents follow, and full multi-agent systems that work across departments are expected by 2029. By 2035, Gartner predicts agentic AI could drive close to 30% of all enterprise application revenue, a market worth more than $450 billion. In 2025, that figure was just 2%.
The wider AI agent market backs up the trend. Analysts estimate it will be worth $10.9 billion to $12 billion in 2026 alone, growing more than 44% a year through 2030.
The catch
Gartner predicts that growth won’t be smooth. It expects more than 40% of agentic AI projects to be cancelled by 2027. The reasons are familiar: costs spiral, the payoff isn’t clear, and companies underestimate what it takes to run these systems safely.
That warning lines up with what other research is finding. An IBM study of company leaders in 2025 found only 25% of AI projects delivered the returns they expected. Separately, IDC and Microsoft found that companies do see a return on generative AI spending, about $3.70 back for every dollar spent, but that return isn’t evenly spread. Some teams are winning big. Many others are burning cash with little to show for it.
Agent or assistant?
Gartner also flags a problem with how the term “agent” is being used. A lot of products marketed as AI agents today are really just assistants with a new label, a trend the firm calls agentwashing. A genuine agent, in Gartner’s view, should be able to act independently. One example it gives is a cybersecurity agent that monitors network traffic and user behavior in real time, then responds to threats on its own, without waiting for a person to approve each step.
What this means going forward
The takeaway is simple: demand for AI agents is real and growing fast, but so is the risk of building the wrong thing. Gartner’s roadmap has nearly every enterprise app carrying AI task-specific agents becoming common in 2026, agents starting to work together by 2027, and fully autonomous, multi-app agent systems by 2028 and beyond.
For now, the companies most likely to succeed are the ones treating cost and governance as part of the build, not an afterthought.
Sources: Gartner Inc. (August 2025); IBM 2025 CEO study; IDC and Microsoft research on generative AI returns; industry estimates on the global AI agent market.
