Why do agentic AI projects fail?

Gartner names three reasons: escalating costs, unclear business value and inadequate risk controls. It also notes many projects are early experiments driven by hype and often misapplied.

How can a business avoid a canceled AI project?

Agree the result the agent must deliver, one owner, what counts as done and how you will measure it, before building. Gartner recommends pursuing agentic AI only where it delivers clear value or ROI.

Why agentic AI projects get canceled, and how to avoid it

Put to the Check takes a widely quoted idea about business and AI and runs it through the six questions of the ERMODA Check.

The claim

In June 2025, Gartner said: “Over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls.” (Gartner)

What they got right

A lot. Gartner’s analyst Anushree Verma describes most current projects as “early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied.” Gartner also estimates that only about 130 of the thousands of vendors selling agentic AI offer the real thing. Its advice is sensible and simple: pursue agentic AI only where it delivers clear value or ROI.

It’s not an anti-AI forecast either. The same release predicts that at least 15% of day-to-day work decisions will be made autonomously by agentic AI by 2028, up from 0% in 2024.

Put to the Check

We looked at the three reasons Gartner gives through the ERMODA Check.

E · Expectation: Gap found. “Unclear business value” is an expectation problem. If nobody wrote down what the agent must deliver, and for whom, there’s nothing to measure it against.

R · Right people: Evidence needed. Were the people who own the work involved in choosing the use case, or was it chosen by the team that wanted to try the technology?

M · Map: Gap found. Gartner warns that fitting agents into older systems “can be technically complex, often disrupting workflows.” Mapping the workflow before choosing the tool is where that cost shows up early instead of late.

O · Owner: Evidence needed. Someone owns the budget. Does someone own the result?

D · Done: Gap found. This is the heart of it. A project without an agreed finish line can’t show value, so when costs rise it is the easiest thing to cancel.

A · Assured: Evidence needed. Do the people who were meant to benefit say it’s working?

The missing step

Agree the finish line before the build. One page is enough: the result the agent must deliver, the owner, the measure and the date you’ll check it. Projects with that page can defend their budget. Projects without it are guessing.

Your move

If you run your own business

Before paying for any “AI agent”, write one sentence: what should be different, and by how much, in 90 days?
Ask the vendor to show that result for a customer like you, not a demo.
Put a date in your calendar to check it. If it hasn’t delivered, stop paying.

If you lead a larger firm

Require a one-page finish line for every agentic AI project: result, owner, measure, review date.
Review each project against its page at 30 and 90 days, and be willing to stop the ones that can’t show progress.
Use Gartner’s own sorting rule: agents where decisions are needed, automation for routine workflows, assistants for simple retrieval.

AI agents will do real work. The projects that survive will be the ones that agreed, up front, what that work was.