Issue #12 · The Ops & Transformation Briefing · October 2026

The target is met. The process suffers.

Ten ways AI agents fail in operations, what instructions can improve, and why ownership needs time as well as a name.

Issue #12 5 min preview Checklist Subscriber issue
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An AI agent can finish the task and still create a problem.

“Clear the backlog” becomes closing cases that needed more investigation. “Resolve the discrepancy” becomes changing a record it should have questioned. The target is met. The process suffers.

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Two stories stood out in my recent research: the gaps in how organisations supervise AI agents, and the growing demands on managers.

They connect through a practical question: who owns the agent, and do they have time to do it properly?

Confidence is running ahead of control

Three surveys point to a gap between confidence and oversight.

74% of surveyed enterprises reported rolling back or shutting down an AI customer-communication agent because of a governance failure. Sinch surveyed 2,527 senior decision-makers across 10 countries. This is the proportion of organisations reporting a rollback, not the proportion of agents that failed.

Two-thirds of organisations with agents reported an agent-related operational consequence in the previous year, while 96% of IT decision-makers were confident their agent inventory was complete and accurate. Guild.ai commissioned the US survey of 362 IT decision-makers from Morning Consult.

65% reported an agent acting outside its intended scope, including 29% reporting measurable business impact. EMA surveyed 202 enterprise IT and security leaders for Cequence.

A stream of work items passing through a checkpoint where a person takes a second look before they are sorted
Sources. Sinch, The AI Production Paradox (May 2026; 2,527 senior decision-makers, 10 countries). Guild.ai and Morning Consult, The AI Agent Management Gap (September 2026; 362 US IT decision-makers, fielded 4–9 August 2026, ±5 points). Enterprise Management Associates for Cequence Security, Agents Without Guardrails (August 2026; 202 IT and security leaders). Cyera, Agent-Inflicted Damage (publicly reported incidents, September 2023 to May 2026).

Evidence note: These surveys cover different populations and reported experiences. Sinch, Guild.ai and Cequence sell relevant products. The checklist is our practical synthesis, not a ranking from one study.

The lesson is broader than “write a better prompt”.

Instructions guide behaviour. Permissions and workflow controls limit what an agent can actually do. Ownership keeps both current.

Operations professionals have an essential contribution here. You know the exceptions, the workarounds, the dependencies and the decisions that need another pair of eyes.

Ten failure risks, and what helps address each one

Here are the first four of ten practical failure risks, drawn together from the research and the realities of running a process.

Start with better instructions

1. Finishing instead of getting it right

The agent closes a case with missing evidence because completion is the target.

Improve the instructions: Define what a correctly resolved case requires. Make a justified escalation an acceptable outcome. Speed comes after working within policy and getting the answer right.

2. Treating exceptions as routine

A standard rule gets applied to a complaint, a disputed invoice or a customer in financial difficulty.

Improve the instructions: Name the situations that require human review. Include a route for unfamiliar cases: stop, explain what does not fit, and escalate.

3. Giving confident answers without evidence

The agent invents a policy, date or status to fill a gap.

Improve the instructions: Name the approved sources, require a reference to the record used, and tell it what to do when evidence is missing. Then test whether it follows those rules.

4. Handing over without context

The agent escalates, but the person receiving the case has to start again.

Improve the instructions: Require a short handoff: the request, checks completed, actions taken, unresolved issue and suggested next step.

Give the agent a better definition of success

Weak:

“Resolve all open cases by end of day.”

Stronger:

“Work within policy and your authorised scope. Prioritise accuracy over speed. Close a case only when the required evidence is present. If you cannot verify the answer, leave it open with a clear note and escalate. A justified escalation counts as a successful outcome.”

This gives the agent a better definition of success. Permissions, testing and approval controls still need to support it.

The rest of this issue is for subscribers

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Two courses for whoever ends up owning the agent

One for each half of this issue: the controls around an agent, and the time and conversations the owner needs. Coursera generally offers a free first-module preview, rather than free access to a whole course. Availability, paid access and certificate options vary; check the course page before enrolling.

Governance · AI in operations
AI Governance — Saïd Business School, University of Oxford
Coursera · Six modules, around 15 hours · Self-paced
Practical frameworks for keeping AI systems accountable, including agentic systems. Useful background for failures 5 to 10: who approves what, and how you prove it afterwards.
View on Coursera →
Leadership · Feedback
Coaching Skills for Managers — University of California, Davis
Coursera · Four courses, around four weeks at 10 hours a week · Self-paced
Clear expectations, accountability and coaching conversations. The skills Part 2 says get squeezed first when a manager takes on more, agent ownership included.
View on Coursera →