Pilot Programs
AI customer-facing assistants
Assess customer-facing AI assistants by approved answers, human handoff, unavailable questions and careful review of conversations.
Archive
October 2026
Task Testing
AI image and design tools
Choose an AI image or design workflow by commercial use, text accuracy, editability and the file your team needs to deliver.
Meeting Tools
AI meeting tools
Choose an AI meeting workflow by the record you need, who can access it and the work required to check decisions and actions.
Task Testing
AI output quality testing
Set acceptance rules, check AI outputs against approved sources and compare the work needed to reach a usable result.
Writing Tools
AI presentation tools
An AI presentation tool can turn an outline or source file into a draft deck, but the buyer still owns the argument, figures and final format. Compare tools with …
Pilot Programs
AI procurement and pilot programmes
Screen AI suppliers, run a bounded business pilot and use its evidence to make a purchase decision.
Writing Tools
AI research tools
Choose an AI research tool by source access, citation checks and review effort across web, document, report and paper workflows.
Cost & Limits
AI tool costs and usage limits
Assess AI tool costs, staff effort and the usage limits that could interrupt ordinary business work.
Data Handling
AI tool integration
Trace a task from source to approved result, then assess browser, workflow, connector and API routes, including permissions and failures.
Data Handling
AI tool privacy and data handling
Check what enters an AI tool, who can access it, how long it may remain and whether it can be used for training before approving business use.
Task Testing
AI tool reliability
Assess AI tool reliability through repeated results, realistic inputs, failure recovery and the availability terms for your business account.
Writing Tools
AI writing tools compared
Compare Copilot in Word, Grammarly and Jasper by writing task, documented limits, review effort and the quality of an approvable draft.
Task Testing
Building a rubric before reading competing outputs
Turn a defined task into observable quality criteria, pass and fail anchors, and a decision rule before reviewing AI outputs.
Data Handling
Checking API and export options before adoption
Check how an AI tool exchanges task data and how you would retrieve records, workflows and run history before adopting it.
Task Testing
Checking export quality before choosing a slide tool
Choose a slide tool using the file that recipients will actually open. A deck that looks right in the editor can reflow, lose animation or become difficult to revise after export.
Task Testing
Checking failure behaviour when an answer is unavailable
Test absent knowledge, unclear questions and technical failures to see whether a customer assistant admits limits and provides a useful next step.
Task Testing
Checking how a tool handles a failed request
Trace an AI request failure through diagnosis, safe retry, account fix or human takeover, and check the final state of work.
Cost & Limits
Checking licensing terms before using generated assets
Trace inputs, AI outputs and library elements before approving a generated asset for commercial use or client handover.
Task Testing
Checking limits that interrupt ordinary business tasks
Map AI feature, rate and spending limits to an ordinary task, then record reset rules and a recovery route.
Task Testing
Checking whether a writing tool preserves the source meaning
Compare source and rewrite for changed actors, certainty, conditions, attribution and missing propositions before approving AI-written copy.
Data Handling
Check whether an AI vendor uses submitted data for training
Find the training rule for the precise AI product, account and feature, including prompts, files, feedback and connected services.
Pilot Programs
Choosing a pilot owner and approval criteria
Assign an AI pilot owner, record decision rights and set adoption gates before seeing results.
Task Testing
Choosing and documenting an AI tool test set from real work
Select routine, varied and difficult work items for an AI trial, prepare an answer key and report results by case type.
Data Handling
Browser tools vs business-system integrations by task
Compare a person-led browser handover with a connected AI workflow by tracing the input, review, final action and failure path.
Task Testing
Comparing design tools on a clearly defined commercial task
Set one commercial design brief, apply the same acceptance gates to each tool and record the work needed to approve the asset.
Task Testing
Comparing document-grounded research with open-web research
Choose between selected documents and open-web sources, compare their gaps and reconcile conflicting answers.
Task Testing
Comparing editable slides with image-only outputs
Editable slides let a colleague correct a number or move a chart without recreating the page. An image-only result may preserve appearance but becomes expensive to …
Task Testing
Comparing editing quality without rewarding longer answers
Use a fixed brief, meaning gates and repair effort to compare AI edits without giving extra credit for longer answers.
Meeting Tools
Comparing human handoff options
Compare live transfer, queued follow-up and human review by tracing a customer request through routing and the first useful human reply.
Task Testing
Comparing outputs with a blinded review
Prepare anonymised AI outputs, vary their order, score against a fixed rubric and resolve reviewer disagreements before revealing providers.
Task Testing
Comparing table extraction from different document layouts
A table can be transcribed word for word yet lose the relationship between a row label and its amount.
Meeting Tools
Comparing meeting transcription and summary features
Compare meeting transcripts and AI summaries by coverage, meaning, attribution, correction work and access.
Task Testing
Comparing vendor claims with observed results
Check AI supplier claims against the proposed plan, applicable terms and bounded pilot observations.
Task Testing
Dating a review to the tested product version
Separate test, documentation and page dates, and describe the product version or account conditions behind an AI review.
Pilot Programs
Deciding when a tool is not ready for business adoption
Use AI pilot evidence to approve a narrow use, hold for a specific fix or decline adoption.
Task Testing
Defining a repeatable task before comparing AI tools
Turn a vague AI use case into a task card with fixed inputs, outputs, acceptance rules, exceptions and a human owner.
Writing Tools
Disclosing affiliate relationships without changing the verdict
Explain affiliate commissions clearly while keeping AI review coverage, ranking and verdicts grounded in editorial evidence.
Cost & Limits
Estimating cost per accepted output
Calculate AI cost per accepted result, including paid usage, staff review, corrections, setup and rejected attempts.
Pilot Programs
Evaluating AI tools for business tasks
A practical framework for choosing and trialling AI tools against real business work, accepted outputs, operating limits and review effort.
Writing Tools
Evaluating text accuracy inside generated graphics
Use an answer key, transcription check and final-export review to catch wrong words, figures and conditions in generated graphics.
Task Testing
Explaining exactly what was tested in an AI review
Show readers the cases, conditions, attempts, results and limits behind an AI review’s test-based claims.
Writing Tools
General-purpose assistants versus specialised AI products
Understand when a flexible assistant or a task-specific AI product fits better, with documented workflow examples and limits.
Data Handling
Keeping confidential data out of a public tool trial
Set an input boundary, prepare fictional examples and check every upload route before trialling a public AI tool.
Task Testing
Measuring correction effort after automated extraction
The cost of document extraction includes work after the model responds.
Task Testing
Measuring performance with longer input documents
Check whether an AI tool accepts longer documents and finds the right evidence, using a controlled length comparison and separate format checks.
Task Testing
Publishing evidence-based AI reviews
A publication standard for AI reviews: distinguish observed results from vendor claims, bound the verdict, disclose commercial ties and maintain the page.
Task Testing
Recording failure cases instead of publishing only successes
Keep original AI failures, their test conditions and the work needed to repair them so a quality report reflects the whole evaluation.
Task Testing
Recording unsupported claims in a research tool evaluation
Keep a reproducible record of unsupported AI research claims, source gaps, consequences and corrections.
Cost & Limits
Reviewing availability commitments for business use
Read an AI provider’s availability terms by checking covered traffic, downtime rules, exclusions, credits and your own recovery deadline.
Data Handling
Reviewing conversation logs without exposing customer data
Use aggregate patterns, limited access and carefully prepared excerpts to review AI assistant conversations while reducing customer-data exposure.
Task Testing
Reviewing layout quality with the same source material
A fair layout comparison gives each tool the same content, audience and constraints. Otherwise a tool that received a clearer brief may look better for the wrong reason.
Data Handling
Reviewing recording permissions before using a meeting bot
Check participant notice, host approval, auto-join, sharing and stopping controls before a meeting bot captures a call.
Data Handling
Reviewing retention settings before uploading business files
Trace chats, uploaded files, projects and compliance copies before deciding whether a business file may enter an AI tool.
Cost & Limits
Reviewing the effort needed to replace an AI vendor
Inventory records, prompts, mappings, permissions and approvals to estimate the work of moving an AI workflow to another vendor.
Pilot Programs
Running an AI tool pilot with non-sensitive test data
Set an input boundary, rehearse the full workflow and report what a non-sensitive AI pilot can establish.
Data Handling
Separating attractive images from usable production files
Inspect exported AI artwork for dimensions, transparency, editability and handover quality before approving it for web or print.
Task Testing
Separating factual errors from style preferences
Use two review passes to identify wrong or unsupported AI claims before making tone and wording edits.
Task Testing
Testing an AI step inside an existing work process
Follow an AI step from the normal trigger to an approved record, including field mapping, review, failed runs and recovery.
Task Testing
Testing extraction from invoices with known answers
An invoice-extraction test needs a verified answer key.
Task Testing
Testing factual accuracy in AI writing outputs
Build an answer key, verify each claim and qualification, and report consequential factual errors in AI-generated writing.
Task Testing
Testing repeated runs on the same task
Repeat one AI task under recorded conditions, judge every first attempt against a fixed rule and report variation that matters.
Task Testing
Testing speaker attribution with a sample recording
Use a known-speaker recording to check wrong, missing, split and merged labels before relying on meeting notes.
Task Testing
Testing whether a presentation tool preserves figures
AI presentation tools can make a number look convincing even when they copied it incorrectly or dropped its qualification. Test data fidelity separately from visual appeal.
Task Testing
Testing whether an assistant stays within approved information
Build an answer key and test public, restricted, outdated and absent information before an AI assistant replies to customers.
Task Testing
Testing whether cited sources support an AI answer
Check an AI answer claim by claim against cited passages, including dates, conditions, inaccessible sources and omitted evidence.
Task Testing
Updating a review after a material product change
Decide when an AI product change warrants a review update, recheck affected claims and explain the revised verdict without erasing old tests.