Free stakeholder question guide

Healthcare AI Vendor Evaluation Questions

48 questions across eight stakeholder perspectives. Use them to organise evidence routes, not to imply that every answer belongs publicly.

Download the PDF guide Download the editable guide
01 / How to use it
Choose a stakeholder

Start with the decision question, then identify the evidence route that could answer it.

Each question explains why it matters, what useful evidence may look like and whether the information is likely to be visible publicly, shared after qualification, confidential or specific to the proposed use case.

Clinical leadership

1. What clinical problem is the product intended to address?

Why it mattersA precise problem definition prevents a promising capability from being evaluated outside the need it was designed to solve.
Useful evidenceA bounded intended-use statement, target condition, current workflow problem and non-goals.
Likely accessVisible publicly
ReferenceOpen source
Clinical leadership

2. Who is the intended user, patient population and care setting?

Why it mattersPerformance and safety cannot be interpreted without knowing who uses the product, for whom and under which conditions.
Useful evidenceNamed users, target population, care setting, inclusion and exclusion boundaries.
Likely accessVisible publicly
ReferenceOpen source
Clinical leadership

3. What role does the AI play in the clinical workflow?

Why it mattersA stakeholder must understand whether the system informs, prioritises, recommends, automates or replaces part of a decision.
Useful evidenceWorkflow diagram, intended inputs and outputs, human review point and action supported.
Likely accessVisible publicly
ReferenceOpen source
Clinical leadership

4. What evidence supports performance, clinical utility and safe use?

Why it mattersA metric alone does not show whether the product improves a relevant decision or outcome in practice.
Useful evidenceStudy summaries, evaluation setting, comparators, endpoints, sample characteristics and limitations.
Likely accessVisible publicly
ReferenceOpen source
Clinical leadership

5. What limitations, failure modes and excluded populations are known?

Why it mattersExplicit limits help teams decide where the product should not be relied upon and what safeguards are required.
Useful evidenceKnown biases, failure conditions, confidence ranges, data gaps, contraindications and out-of-scope uses.
Likely accessVisible publicly
ReferenceOpen source
Clinical leadership

6. What happens when the AI output is uncertain, incorrect or unavailable?

Why it mattersA safe workflow needs a fallback route before implementation, not after an incident.
Useful evidenceHuman escalation, exception handling, override, downtime process and clinical responsibility.
Likely accessShared after a serious enquiry
ReferenceOpen source
Governance and compliance

7. Who is accountable for approval, oversight and stopping use?

Why it mattersA decision cannot be governed when authority and accountability remain implicit.
Useful evidenceNamed decision owner, oversight body, review cadence, escalation authority and stop criteria.
Likely accessShared after a serious enquiry
ReferenceOpen source
Governance and compliance

8. Which decisions remain with humans?

Why it mattersHuman oversight must be described at the point where the system influences care, not only as a general principle.
Useful evidenceDecision-rights map, review obligations, override conditions and prohibited automation.
Likely accessVisible publicly
ReferenceOpen source
Governance and compliance

9. How are bias, fairness and population fit assessed?

Why it mattersA health system needs to know whether performance and risk may vary across populations or settings.
Useful evidenceSubgroup analysis, data representativeness, known gaps, mitigation and local-validation plan.
Likely accessShared after a serious enquiry
ReferenceOpen source
Governance and compliance

10. How are model updates, version changes and new claims governed?

Why it mattersA decision made on one version can become invalid if the product changes without a controlled review.
Useful evidenceVersion history, change-control process, notification rules, revalidation triggers and claim approval.
Likely accessShared after a serious enquiry
ReferenceOpen source
Governance and compliance

11. How are incidents, complaints and performance concerns escalated?

Why it mattersTeams need to know how issues become visible, investigated, corrected and communicated.
Useful evidenceIncident taxonomy, reporting route, response times, corrective action and stakeholder notification.
Likely accessShared after a serious enquiry
ReferenceOpen source
Governance and compliance

12. Which regulatory and claim boundaries apply?

Why it mattersPublic language should not imply uses, outcomes or assurances beyond the product’s current evidence and status.
Useful evidenceRegulatory status, intended-use boundary, approved claims, jurisdiction and legal review route.
Likely accessVisible publicly
ReferenceOpen source
Security and privacy

13. What data enters, leaves and remains in the system?

Why it mattersA security review starts with an understandable data flow, not a list of certifications.
Useful evidenceData-flow diagram, data types, storage locations, transfers, outputs and retention.
Likely accessShared after a serious enquiry
ReferenceOpen source
Security and privacy

14. Which core security controls protect the service?

Why it mattersStakeholders need evidence of how access, identity, encryption, logging and resilience are managed.
Useful evidenceSecurity overview, control mapping, independent assurance and current certification scope.
Likely accessShared after a serious enquiry
ReferenceOpen source
Security and privacy

15. Is customer data used to train or improve models?

Why it mattersThe answer affects consent, privacy, contractual rights, data governance and risk.
Useful evidenceClear data-use statement, opt-in or opt-out conditions, de-identification and training boundaries.
Likely accessVisible publicly
ReferenceOpen source
Security and privacy

16. How are access, logging, retention and subprocessors managed?

Why it mattersOperational control depends on who can access data, how activity is recorded and where third parties are involved.
Useful evidenceRole-based access, audit logs, retention schedule, deletion process and subprocessor list.
Likely accessShared after a serious enquiry
ReferenceOpen source
Security and privacy

17. How are vulnerabilities disclosed and patched?

Why it mattersA buyer needs to understand how security defects are found, prioritised, communicated and corrected.
Useful evidenceVulnerability disclosure policy, patch process, severity model and customer notification.
Likely accessVisible publicly
ReferenceOpen source
Security and privacy

18. What happens during downtime, breach or service disruption?

Why it mattersContinuity and recovery affect patient safety, workflow and organisational exposure.
Useful evidenceBusiness continuity, disaster recovery, recovery targets, breach response and fallback workflow.
Likely accessConfidential under NDA
ReferenceOpen source
Technical integration and data

19. Which systems, standards and data formats are required?

Why it mattersIntegration feasibility depends on the buyer’s actual environment, not a generic compatibility claim.
Useful evidenceSupported systems, APIs, standards, formats, infrastructure and dependency list.
Likely accessVisible publicly
ReferenceOpen source
Technical integration and data

20. What integration work is required from the buyer and vendor?

Why it mattersHidden technical labour can change the real cost and feasibility of adoption.
Useful evidenceResponsibility matrix, integration sequence, technical prerequisites and effort assumptions.
Likely accessShared after a serious enquiry
ReferenceOpen source
Technical integration and data

21. Which data-quality assumptions affect performance?

Why it mattersA model may perform differently when local data is incomplete, delayed, inconsistent or outside its training conditions.
Useful evidenceRequired fields, quality thresholds, missing-data handling, data provenance and failure conditions.
Likely accessShared after a serious enquiry
ReferenceOpen source
Technical integration and data

22. What local acceptance testing is required before go-live?

Why it mattersLocal testing connects vendor evidence to the buyer’s environment and intended use.
Useful evidenceAcceptance-test plan, sample requirements, pass criteria, owners and release decision.
Likely accessTesting for the proposed use case
ReferenceOpen source
Technical integration and data

23. How will drift, degradation and data changes be monitored?

Why it mattersA safe decision must account for performance after deployment, not only before purchase.
Useful evidenceMonitoring metrics, thresholds, alert ownership, investigation and retraining or rollback rules.
Likely accessShared after a serious enquiry
ReferenceOpen source
Technical integration and data

24. What technical resources and support are required over time?

Why it mattersThe operating burden continues after implementation and should be visible before commitment.
Useful evidenceSupport model, staffing assumptions, service hours, maintenance, upgrade and escalation responsibilities.
Likely accessShared after a serious enquiry
ReferenceOpen source
Operations and implementation

25. What changes in the current workflow?

Why it mattersOperational fit depends on how tasks, handoffs, exceptions and accountability change in practice.
Useful evidenceBefore-and-after workflow, role changes, handoffs, exception routes and decision points.
Likely accessVisible publicly
ReferenceOpen source
Operations and implementation

26. What new work, training and exception handling will be required?

Why it mattersA productivity claim can hide new review, correction, monitoring or coordination work.
Useful evidenceTraining plan, review burden, exception volume assumptions, support and ownership.
Likely accessShared after a serious enquiry
ReferenceOpen source
Operations and implementation

27. What is the implementation sequence, timeline and ownership model?

Why it mattersA credible transition requires more than a destination. Teams need to see how the change will be made survivable.
Useful evidencePhases, milestones, dependencies, internal owner, vendor owner and readiness criteria.
Likely accessShared after a serious enquiry
ReferenceOpen source
Operations and implementation

28. How will a pilot be designed and judged?

Why it mattersA pilot without success, failure and exit criteria can consume resources without producing a decision.
Useful evidencePilot question, scope, baseline, measures, responsibilities, success criteria and stop rule.
Likely accessTesting for the proposed use case
ReferenceOpen source
Operations and implementation

29. What happens when the system does not perform as expected?

Why it mattersException and fallback design protects workflow continuity and clarifies responsibility.
Useful evidenceFallback workflow, manual alternative, issue ownership, communication and correction path.
Likely accessShared after a serious enquiry
ReferenceOpen source
Operations and implementation

30. How will adoption, feedback and refinement be managed?

Why it mattersA product can technically launch while failing to become usable or accepted in the real workflow.
Useful evidenceAdoption measures, feedback route, review cadence, training refresh and improvement ownership.
Likely accessShared after a serious enquiry
ReferenceOpen source
Finance and procurement

31. What current problem, cost or constrained capacity is the investment intended to change?

Why it mattersA value case should start with the existing condition, not the product’s feature list.
Useful evidenceBaseline problem, affected volume, current cost, resource constraint and consequence of doing nothing.
Likely accessShared after a serious enquiry
ReferenceOpen source
Finance and procurement

32. What costs exist beyond the licence price?

Why it mattersImplementation labour, integration, training, governance, monitoring and switching costs form part of the effective price.
Useful evidenceTotal-cost model covering internal labour, technical work, training, support and ongoing oversight.
Likely accessShared after a serious enquiry
ReferenceOpen source
Finance and procurement

33. Which outcomes will be measured, over what period and by whom?

Why it mattersA measurable value case needs defined outcomes, timing, data sources and accountable owners.
Useful evidenceOutcome definitions, baseline, measurement plan, time horizon and reporting owner.
Likely accessTesting for the proposed use case
ReferenceOpen source
Finance and procurement

34. What evidence and assumptions support the projected value?

Why it mattersA projection should separate observed evidence from assumptions and buyer-specific estimates.
Useful evidenceAssumption register, source evidence, ranges, dependencies and sensitivity analysis.
Likely accessShared after a serious enquiry
ReferenceOpen source
Finance and procurement

35. What contract, service, liability and exit conditions apply?

Why it mattersCommercial terms can change operational risk, accountability and the cost of reversing the decision.
Useful evidenceService levels, support, data return, termination, liability, transition and continuity terms.
Likely accessConfidential under NDA
ReferenceOpen source
Finance and procurement

36. What would justify scaling, renegotiating, pausing or stopping?

Why it mattersA decision is more defensible when continuation and exit conditions are agreed before commitment.
Useful evidenceDecision gates, thresholds, review dates, escalation and exit criteria.
Likely accessTesting for the proposed use case
ReferenceOpen source
Executive sponsor

37. How does this opportunity support a current organisational priority?

Why it mattersStrategic relevance determines whether the opportunity deserves scarce attention, resources and political support.
Useful evidenceNamed priority, affected objective, executive owner and expected organisational contribution.
Likely accessShared after a serious enquiry
ReferenceOpen source
Executive sponsor

38. Why is AI the appropriate approach compared with non-AI alternatives?

Why it mattersA defensible decision considers substitutes, process redesign and the option of doing nothing.
Useful evidenceAlternative analysis, comparative advantages, constraints and conditions where AI is not preferred.
Likely accessShared after a serious enquiry
ReferenceOpen source
Executive sponsor

39. What benefits, risks and opportunity costs are concentrated across the organisation?

Why it mattersValue and burden may fall on different teams, creating resistance even when the overall case looks positive.
Useful evidenceStakeholder value map, resource demands, risks, dependencies and distribution of accountability.
Likely accessShared after a serious enquiry
ReferenceOpen source
Executive sponsor

40. Who owns the outcome and which resources are committed?

Why it mattersExecutive sponsorship is meaningful only when decision rights, resources and accountability are explicit.
Useful evidenceNamed sponsor, operating owner, budget, staffing and governance commitments.
Likely accessShared after a serious enquiry
ReferenceOpen source
Executive sponsor

41. What evidence would justify advancing, pausing or rejecting the opportunity?

Why it mattersPredefined decision criteria reduce ambiguity and prevent momentum from replacing evaluation.
Useful evidenceDecision criteria, required evidence, risk tolerance, stage gates and stop conditions.
Likely accessTesting for the proposed use case
ReferenceOpen source
Executive sponsor

42. What must leadership monitor after implementation?

Why it mattersLeadership still needs visibility into value, safety, adoption and material changes after go-live.
Useful evidenceExecutive dashboard, review cadence, thresholds, incident reporting and strategic reassessment.
Likely accessShared after a serious enquiry
ReferenceOpen source
Internal champion

43. Which stakeholders must support the decision and what does each need to understand?

Why it mattersThe champion cannot carry one generic case into a decision made by several functions.
Useful evidenceStakeholder map, decision task, evidence need, concern and approval role.
Likely accessVisible publicly
ReferenceOpen source
Internal champion

44. Which evidence can be shared publicly, after qualification, under NDA or through local testing?

Why it mattersA clear access path prevents the champion from repeatedly requesting or reconstructing information.
Useful evidenceEvidence register with access level, owner, request route and freshness date.
Likely accessShared after a serious enquiry
ReferenceOpen source
Internal champion

45. What do the strongest public claims establish and where are their boundaries?

Why it mattersA champion needs language that is persuasive without asking colleagues to accept more than the evidence supports.
Useful evidenceClaim-to-evidence map, context, limitations, applicable setting and approved wording.
Likely accessVisible publicly
ReferenceOpen source
Internal champion

46. Which unanswered questions currently prevent the next step?

Why it mattersA useful case separates what is known from what must still be resolved.
Useful evidenceOpen-question register with owner, evidence required, decision affected and due stage.
Likely accessShared after a serious enquiry
ReferenceOpen source
Internal champion

47. Which cross-functional meetings are required and what decision must each produce?

Why it mattersMeetings become useful when participants, evidence inputs, questions, output and decision gate are defined.
Useful evidenceMeeting designs covering participants, inputs, questions, required output and next decision.
Likely accessShared after a serious enquiry
ReferenceOpen source
Internal champion

48. Can the case be circulated without rebuilding it manually?

Why it mattersA decision slows when the champion must translate scattered pages into a new narrative for every stakeholder.
Useful evidenceA concise decision pack with stakeholder routes, evidence boundaries, open questions and source register.
Likely accessVisible publicly
ReferenceOpen source
Boundary: These questions help teams structure evaluation. They do not determine whether a vendor is safe, compliant, clinically appropriate or suitable for a particular organisation.
Apply the questions to your company

Can each stakeholder find and use the evidence required for their part of the decision?

Open the Evidence Coverage Matrix Explore the Assessment