Two hundred real tickets in a free chat tool
A Scrum Team supports a customer service platform. Support tickets contain names, addresses and account numbers. The team wants to send tickets to a public LLM API to auto-classify and draft replies, targeting a 40% reduction in handling time. The Product Owner wants to test AI-drafted replies on live customers next Sprint because 'the samples looked fine'. During refinement a developer pasted 200 real tickets, including account numbers, into a free chat tool to check feasibility. Nobody has documented which vendor holds what, and there is no retention policy. One team member has raised that auto-classification may systematically misroute non-English tickets, which come mostly from one region. The Sprint Goal is about reducing the ticket backlog.
1. Rank the risks and separate what must stop now from what needs a plan.
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Rank by severity, likelihood and reversibility - reversibility is the one people forget.
- Real customer data sent to an uncontrolled third-party tool. Already happened. High severity, hard to reverse: the data may be retained, logged or used to improve the vendor's model, and you cannot un-send it. This is an incident, not a hypothetical. Stop the flow today, establish exactly what was sent and when, notify whoever owns privacy and security in your organisation, use whatever deletion mechanism the vendor offers, and move any further exploration to an approved environment with a data-processing agreement and training disabled.
- Customer-facing A/B testing of AI-drafted replies without a quality gate or disclosure. Reversible in principle, but the reputational and regulatory cost lands on customers who did not consent. 'The samples looked fine' is not evidence: samples selected by the team are the easiest cases, and no sample of twenty tells you the error rate on edge cases.
- Systematic misrouting of non-English tickets. This is the quiet one. If the evaluation sample was drawn from the bulk of tickets, it almost certainly under-represents the region affected, so the team's own evidence cannot detect the harm. That makes it a fairness and quality risk that persists after launch, and it is invisible in aggregate accuracy numbers.
- No named risk owner. Every risk above is being carried by nobody, which is why they all surfaced at once in refinement.
Stop now: sending any real ticket data to unapproved tools; any live-customer test. Needs a plan: everything else, in the order above. Stopping is not obstruction - it is the only way the remaining work is worth doing.
2. How do you make this actionable inside Scrum artifacts rather than as a separate governance exercise?
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The artifacts are the mechanism; that is what makes it stick.
- Product Backlog: add explicit items - data-handling approval, a de-identification or pseudonymisation pipeline, a stratified evaluation set with defined size and coverage by language and region, a human-in-the-loop review step, and a rollback plan. These are real work with real cost; ordering them against the backlog reduction items is the Product Owner's call, made visibly.
- Definition of Done: no real customer data in unapproved tools; any AI-drafted output reviewed by a human before it reaches a customer; provenance logged for AI-drafted content so it can be audited; evaluation results recorded against the stratified set, not against a friendly sample.
- Sprint Goal: 'reduce the ticket backlog' must not be satisfiable by an unsafe mechanism. A Sprint Goal can be met or missed; it cannot be met by breaking the DoD. That distinction is the Scrum Master's to hold, and it is what protects the team when the Goal creates pressure.
- Every risk gets a name. A risk with no owner is a wish. Put the owner next to the backlog item, not in a separate register nobody reads.
- Sequence it honestly. A two-week spike to build the stratified evaluation set before any customer-facing test is not a delay to the Goal; it is the difference between learning whether this works and discovering it in production.
3. The Product Owner says: 'Legal will catch up eventually - we cannot wait, the backlog is a problem now.' How do you respond?
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Do not moralise, and do not simply refuse. Reframe as delivery risk and offer a parallel path.
Reframe the argument. The PO is right that the backlog is a problem now. The question is not speed versus caution; it is which route reaches a working solution without a rollback. A customer-data incident discovered after launch means stopping the feature, notifying customers, and rebuilding trust - a cost far larger than a two-week gate now. Put it in the PO's own currency: what does a recall cost the product compared with the wait?
Offer a path that keeps the team learning this Sprint:
- Use synthetic or properly de-identified tickets so the classification work proceeds.
- Run AI-drafted replies internally, with a human sending everything, so quality is measured without customer exposure.
- Set up the approved vendor environment in parallel with Legal rather than after Legal.
- Build the stratified evaluation set now - it is the long pole for any responsible launch anyway.
Make the risk owned, not buried. If the PO still wants to proceed, ask them to record the decision, its owner and the accepted risk. This is not a threat; it is what transparency means. Executives and Product Owners are entitled to accept risk - they are not entitled to leave it invisible.
Know the line. If the decision would require the team to breach the DoD or a legal constraint, escalate through the appropriate channel with facts, once, and say clearly who is accepting what. Your accountability is to make the risk visible and owned, and to keep the team from carrying a risk that was never theirs to carry.