The 2026 survey figures cited here put reported AI-agent deployment at ninety-seven percent and production use at eleven percent. These figures come from multiple surveys. Without comparable definitions and respondent populations, they cannot establish how many enterprises deployed an agent and then failed to reach production.
For an individual team, the useful check is concrete: identify the live work an agent handles and inspect the record of its recent runs.
Check what deployed agents actually do
A deployment report should say whether the agent runs on test data or live data, how often it runs, and who relies on the result. An agent configured for a successful demo may still need permissions, monitoring, and a review process before a team can use it in daily work.
PwC’s 29th Global CEO Survey found that 56% of CEOs see no revenue or cost impact from AI. That result warrants checking both the cost of pilots and the contribution of systems already in use.
Treat ROI as a claim to examine
A reported average 171% ROI also appears in the adoption figures. The source population, cost basis, and measurement period need reconciliation before that number can guide a business case. It does not establish the return a new deployment will earn, or what will happen to other enterprises over the next six months.
A pilot review can begin with its own costs and results. Record the work completed, the review time, and the failures requiring intervention before expanding to another workflow.
Include adoption in the production plan
IBM’s 2026 CEO Study surveyed thousands of executives and found that eighty-three percent believe AI success depends more on people’s adoption than on the technology itself. The study also found that eighty-five percent of employees have access to AI tools at work, but only twenty-five percent use them regularly.
The production plan needs to cover change management, workflow redesign, ownership clarity, monitoring, escalation paths, and the organizational willingness to let an agent do real work. Writer’s 2026 enterprise survey found that 54% of C-suite executives say AI adoption is tearing their company apart. That is a reason to examine how the rollout affects the people expected to use it.
Assign an owner for the production outcome and define the agent’s responsibilities within the workflow. Give the team a way to check results and escalate mistakes before expanding its access.
Give the pilot an exit decision
For a team whose agents remain in a sandbox, set a review date and specify the evidence needed for live use. That may include successful runs on representative tasks, approved access, and a person available to handle exceptions. The review can lead to production, a narrower trial, or stopping the project. Each is a decision the owner can explain.