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What customer data is needed for a pilot of AI document processing
AI document processing: Request the minimum data needed to answer the pilot's learning question.
Request the minimum data needed to answer the pilot's learning question. More access can increase implementation work and exposure without improving the experiment. Map each requested field to an actual product or evaluation need.
Start with the decision
List data sources, fields, access owners, storage locations, and deletion expectations. Start with a permissioned sample where feasible. Ask the customer to confirm the allowed use and involve the appropriate specialists for sensitive information.
The illustrative scenario
This is an educational workbook. The company or fund and all numerical inputs below are fictional. They are not ADIN results, customer claims, market benchmarks, or a forecast.
The fictional product extracts invoice data for an accounts payable team. Staff review exceptions before information enters the accounting system. Supplier formats and duplicate documents make the input stream uneven.
A misplaced decimal or duplicate record can matter more than an average extraction score. Define the fields and events that require review before comparing workflows.
Turn the scenario into an evidence decision
Consider a review of AI document processing in which a confident explanation arrives before the supporting records. Start with the first question in the table. Write down what an answer would change: the next interview, the experiment's scope, a request for specialist review, or a decision to wait. A question without a consequence can produce a longer document while adding little understanding.
Next, inspect the record named in the table and record its date, owner, permission boundary, and limitations. Use permissioned documents, field-level corrections, duplicate flags, and reconciliation results. Keep document type and supplier format visible instead of relying on one blended score. If the record contradicts the explanation, preserve both accounts and ask which definition, period, or workflow differs. Do not silently select the version that makes the opportunity look strongest.
Finish with a conditional statement: if the specified evidence supports the claim under these conditions, take the named next step; otherwise investigate the unresolved question. A data request is clearer when a buyer can trace every item to a defined purpose. A missing field may require a smaller experiment rather than a broader request for all available customer data. This worked exercise is about the decision process. It does not assert that a fictional company has met a real diligence standard or that a template can authorize an investment.
| Item | Illustration |
|---|---|
| Decision question | Which field is necessary? |
| Case-specific constraint | A misplaced decimal or duplicate record can matter more than an average extraction score. Define the fields and events that require review before comparing workflows. |
| Record to inspect | Use permissioned documents, field-level corrections, duplicate flags, and reconciliation results. Keep document type and supplier format visible instead of relying on one blended score. |
| Comparison to preserve | Compare correct, reconciled records with the current process. Include document intake, exception review, and corrections after export in the time and cost model. |
| Unresolved case question | Which fields require exact agreement? |
Use this worksheet
Answer the questions with a source, date, owner, and next action. Mark an unknown as unknown. Use public or permissioned information and involve a qualified specialist when a question requires expertise beyond the team’s competence.
- Which field is necessary?
- Who can authorize access?
- Where will it be stored?
- What is excluded?
- When is access removed?
Questions specific to this scenario
- Which fields require exact agreement?
- How are duplicate invoices handled?
- Who signs off on reconciliation?
Use permissioned documents, field-level corrections, duplicate flags, and reconciliation results. Keep document type and supplier format visible instead of relying on one blended score.
A concrete next test
Select permissioned invoices from different supplier formats and include a duplicate. Trace each field through correction and export to reconciliation. Ask the accounts payable owner which error would block use even if most fields were extracted correctly.
Interpret the result
A data request is clearer when a buyer can trace every item to a defined purpose. A missing field may require a smaller experiment rather than a broader request for all available customer data.
Compare correct, reconciled records with the current process. Include document intake, exception review, and corrections after export in the time and cost model.
Sources and method
These primary resources provide background for the concepts. The fictional scenario, calculations, and worksheet are ADIN educational examples; the sources do not report or validate those invented results. Reviewed October 11, 2026.