Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsEvaluate a newsroom vendor by whether it reliably improves a defined editorial or operational task—not by how impressive its AI demo looks. Before signing, test it on representative work, verify its outputs independently, map what happens to newsroom data, preserve human editorial control, and put performance, security, and exit terms in writing.
Start with the newsroom problem, not the product
“AI” and “analytics” describe broad categories, not what a particular service does. For each candidate, document the system’s inputs, the output it produces, and the action a journalist or editor is expected to take. A tool that flags documents for review, for example, is not the same as a tool that drafts a summary or recommends what an audience sees.
Write a testable problem statement
- Workflow and user: Name the task, the staff who perform it, and where the tool would fit.
- Intended outcome: State what should improve, such as discovery, turnaround time, completeness, or workload.
- Constraints: Identify editorial, legal, privacy, accessibility, and technical requirements.
- Failure conditions: Specify which errors, omissions, biases, or delays would make the system unsuitable.
Compare the proposed service with the current workflow and simpler alternatives. UK Government AI procurement guidance recommends requirements based on user needs and outcomes, with room for solutions other than the one initially proposed. Partnership on AI’s newsroom guidance likewise treats adoption as a lifecycle decision involving journalists, editors, and organizational leaders.
Set a baseline and name an owner
Before a pilot, record how the task performs today: time required, error rates, relevant coverage or discovery outcomes, and workload. Choose only measures that matter for this task. Assign one accountable person with authority to approve the test, assess the results, and own the system if adopted. Partnership on AI recommends comparing efficacy with newsroom benchmarks as well as provider metrics.
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Run a representative pilot and check the work
Ask each vendor to demonstrate the same realistic newsroom tasks using representative data and conditions. A polished demonstration is not evidence of production reliability. Decide what acceptable performance means before testing, then have newsroom staff independently check the results.
Measure usefulness after human review
- Correct results and material omissions.
- False positives and the severity of incorrect outputs.
- Performance across relevant subjects, content types, and groups.
- Time saved after verification, including time spent correcting or checking outputs.
- Whether the result is traceable and useful enough to support an editorial decision.
Keep examples of failures alongside successful outputs. A high apparent accuracy rate can still conceal consequential mistakes, uneven performance, or so much verification work that the tool does not improve the workflow. UK procurement guidance supports proof-of-concept testing and ongoing monitoring; the UK Information Commissioner’s Office (ICO) recommends defining acceptable accuracy before procurement and writing accuracy-based measures into agreements.
Ask how the system works and changes
Request documentation of the system’s purpose, data sources, model or analytical approach, known limitations, and evaluation methods. Ask how the vendor communicates material changes and whether the newsroom can investigate or reproduce important results. The ICO recommends due diligence on documentation, fairness evidence, explainability, and independent evaluation of trade-offs. If the vendor cannot explain a result or provide enough information to assess it, treat that as a limitation in the pilot and contract—not as proof that the output is dependable.
Map every data flow before sharing newsroom material
Make an inventory of what the system receives or collects. Include unpublished reporting, source documents, personal information, audience data, staff information, prompts, files, outputs, and telemetry. Partnership on AI recommends asking what data a vendor collects, whether it includes personal information, and how it may be reused.
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- Where is each category of data processed and stored, and which people or entities can access it?
- Does the vendor share data with subprocessors? If so, which ones and for what purpose?
- How long are prompts, uploads, outputs, and usage or diagnostic data retained?
- Can any of those materials be used to train models or for another purpose?
- How can the newsroom request deletion or return, and what confirmation is provided?
- What controls protect sensitive reporting, and what support is available after a security incident?
Do not put confidential source documents or unpublished reporting into a public AI tool unless the newsroom has established that the use is permitted and the data protections are adequate. ProPublica’s published AI policy says it avoids entering confidential source documents into public AI tools where doing so could compromise privacy.
Clarify privacy roles and local requirements
For personal information, document the parties’ roles and instructions in the contract, along with processing purpose and duration, data categories, security measures, subprocessors, breach support, and end-of-contract deletion or return. The ICO’s contract guidance addresses UK data protection requirements; newsrooms elsewhere must apply the laws and policies that govern their own work. UK procurement guidance also recommends assessing data governance and defining whether and how data is shared.
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Keep editorial decisions with people
Set rules for what staff may use the system to do, what requires editor approval, what must be independently verified, and what is prohibited. Name the person accountable for use, and retain a practical way to pause or deactivate the service. The Reporters Without Borders Paris Charter on AI and Journalism states: “Human decision-making must remain central to both longterm strategies and daily editorial choices.” It also calls for independent evaluation before use, clear human responsibility, and disclosure when AI significantly affects journalistic content.
Define verification and disclosure
Treat generated claims as unverified until checked against reliable material. ProPublica’s published policy says, “We treat AI-generated material as unverified source material,” and states that staff remain responsible for published work, verify AI-generated material, disclose meaningful use, and protect confidential material. Translate those principles into newsroom procedures: identify who checks an output, what counts as sufficient verification, and when an AI contribution is significant enough to disclose.
Review audience-facing effects
If a system recommends or personalizes stories, assess how it affects the range of viewpoints and material audiences encounter. Consider whether users can access editorial content without personalization. The relevant test is not only whether recommendations perform well against a metric, but also whether the system changes the audience’s experience in ways the newsroom considers acceptable.
Compare vendors against the same criteria
Use common test tasks and set weights that reflect the newsroom’s needs. The criteria below synthesize Partnership on AI’s newsroom guidance, UK procurement guidance, ICO recommendations, and the Paris Charter; there is no universal weighting or vendor ranking established by those sources.
| Evaluation area | What to examine | Evidence to request or record |
|---|---|---|
| Task performance | Accuracy, completeness, error severity, robustness, and results on representative content. | Pilot results, documented limitations, and agreed performance measures. |
| Editorial fit | Human judgment, reviewability, traceability, disclosure needs, and effects on sourcing or audience experience. | Workflow demonstration, review rules, and examples of outputs that can be checked. |
| Data and privacy | Data provenance, collection, retention, reuse, training, access, location, deletion, and subprocessors. | Data-flow details, contractual terms, security information, and deletion or return process. |
| Bias and fairness | Known limitations, testing across relevant subjects and groups, mitigation, and evidence available to the newsroom. | Evaluation documentation, fairness evidence, and a way to investigate uneven results. |
| Security and resilience | Protection appropriate to unpublished or sensitive work, incident response, continuity, and recovery. | Security controls, incident procedures, and continuity arrangements. |
| Transparency and explainability | Documentation of inputs, methods, outputs, limitations, and system changes. | Technical and user documentation, change notices, and support for investigating results. |
| Operational burden | Integration, staff training, accessibility, support, and verification time. | Pilot observations, training plan, and support commitments. |
| Contract and autonomy | Permitted use, audit rights, performance commitments, portability, exit support, and vendor dependencies. | Proposed contract terms and a practical export and termination process. |
| Total value | Cost in relation to measured benefit and the continuing work needed to review and mitigate risks. | Comparison with the baseline, including verification and oversight workload. |
Put accountability and an exit plan in the contract
Resolve the important operating terms before adoption. UK procurement guidance recommends explainability and steps to reduce vendor lock-in; the ICO recommends written allocation of processing duties and clauses covering security and data deletion.
- Data and permitted use: Define roles, instructions, allowed purposes, security duties, subprocessors, and deletion or return.
- Performance and changes: Set measurable service or accuracy commitments, documentation obligations, and notice of material system changes.
- Accountability: Specify incident notification, support after an incident, audit access, and responsibility for relevant duties.
- People and operations: Agree on staff training, technical support, and any required verification or review procedures.
- Portability and termination: Establish what records the newsroom can export, in what usable format, what assistance is available to move to another supplier, and how data is removed at termination.
Ask what technical or contractual dependencies would make switching difficult. If the newsroom cannot retrieve needed records or end the vendor’s access to its data, the exit terms are not yet clear enough.
Best Value
Monitor performance after launch
Approval is not a one-time decision. Before launch, record who reviews performance, which metrics or incidents trigger escalation, how often the system is reassessed, and who can suspend it. Maintain a register of tools, purposes, data classes, and accountable owners.
Repeat relevant accuracy and bias tests after major vendor or model changes, or when newsroom data or task conditions shift. The Center for News, Technology & Innovation’s February 17, 2026 briefing notes that newsroom policies often emphasize transparency, human supervision, and verification without always translating those principles into practical controls or addressing subtle bias in third-party tools. A policy is useful only if staff can follow it and someone checks whether it works.
Questions to settle before signing
- What precise task is the system meant to improve, and what is the baseline?
- What results did the vendor produce on our representative pilot tasks, including failures and omissions?
- How much newsroom time remains after human review and correction?
- What data enters or is collected by the service, where does it go, and who can access it?
- Can data be retained, reused, or used for training, and how are deletion or return handled?
- Who owns editorial decisions, what uses require verification or disclosure, and who can pause the system?
- What performance, security, incident, audit, training, and change-notice commitments are written into the contract?
- Can we export our records and move to another supplier without losing access or control?
CNTI’s February 2026 briefing reported that about 80% of 221 Global South journalists surveyed said their newsroom had no AI policy; the finding draws on a Thomson Reuters Foundation survey from late 2024 and may have changed since then. It is a dated survey result, not a current estimate for all journalists or newsrooms, but it illustrates why selection criteria should become operating controls rather than remain informal principles.
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