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Popular starting points

Documents and back office

AI can interpret variable documents while binding rules, amounts and approvals are checked deterministically.

Three detailed examplesAll use cases

Interpret variable content and validate fixed rules reliably.

Document workflows are strong candidates when recurring inputs must be read, checked and transferred into structured systems. AI helps interpret different formats; data models, business rules and clear exception paths keep the process controllable.

Typical starting signals

These situations indicate potential. They are not an automatic decision to use AI.

  • Emails, PDFs, scans and forms are manually sorted and entered.

  • Missing information is detected late and causes follow-up work.

  • Several documents must be assembled into a complete case.

  • Teams repeatedly check the same fields, dates and evidence.

  • Exceptions and processing status are not consistently traceable.

Three detailed examples

The three examples explain the starting point, target state, systems, controls, measures and a sensible pilot scope.

Document and inbox processing

Classify emails and documents, extract relevant data and transfer complete cases to the right system.

Starting point

Emails, PDFs, forms and scans are manually sorted, read, re-entered and forwarded.

Possible target state

An intake workflow classifies incoming items, extracts relevant fields, validates required information and transfers complete cases to the correct system. Low-confidence or incomplete cases enter a review queue.

Data and systems

  • Email, SFTP and scanners
  • Document management
  • CRM and ERP
  • Ticketing and specialist applications

Controls and boundaries

  • Validate extraction against a defined schema
  • Use confidence thresholds for manual review
  • Maintain a complete audit trail
  • Account for retention and personal data

Useful measures

  • Classification and extraction quality by document type
  • Cases requiring manual correction
  • Reasons for exceptions and follow-up
  • Cycle time from receipt to transfer

Supplier onboarding and procurement

Collect documents, check completeness, request missing information and prepare master data for approval.

Starting point

Master data, forms and certificates arrive through different channels. Missing documents lead to repeated follow-ups and delays.

Possible target state

A workflow collects documents, checks completeness and validity dates, requests missing information and prepares a master-data record for approval.

Data and systems

  • ERP and supplier relationship management
  • Document management and email
  • Supplier portals
  • Approved external verification sources

Controls and boundaries

  • Require final approval by an accountable person
  • Preserve segregation of duties
  • Record the provenance of external data
  • Monitor expiry dates and changes

Useful measures

  • Completeness on the first review
  • Type and frequency of missing information
  • Time to approved setup
  • Manual corrections to the prepared record

Invoice and purchase-order matching

Extract invoice data, match it with purchase orders and receipts and route discrepancies through controlled approval.

Starting point

Invoice data is entered and checked against purchase orders, deliveries and account assignments. Exceptions must be identified and resolved manually.

Possible target state

The workflow extracts invoice data, matches it with orders and goods receipts, proposes an account assignment and routes discrepancies into an approval process.

Data and systems

  • Finance systems and ERP
  • Document management and email
  • Procurement systems
  • Expense and approval tools

Controls and boundaries

  • No automatic posting outside defined thresholds
  • Validate taxes, currencies and totals
  • Preserve four-eye approval for defined cases
  • Maintain a complete log

Useful measures

  • Extraction and matching quality
  • Normal cases prepared without manual correction
  • Type and frequency of discrepancies
  • Corrections before posting approval

Further opportunities

Further tasks that may benefit from support depending on the workflow, available data and accountability.

  • Check order confirmations

    Compare line items, prices and dates with the approved purchase order.

  • Prepare expense claims

    Capture receipt data, validate required fields and route exceptions for approval.

  • Monitor certificates and validity

    Classify evidence and surface upcoming expiry dates.

  • Check form completeness

    Flag missing or contradictory information before expert processing.

  • Redact documents

    Mask defined personal or confidential content before further use.

  • Prepare archiving and retention

    Suggest document types, metadata and potential retention classes for review.

Data, systems and boundaries

Typical data and systems

  • Email, scanners, portals and file transfer
  • DMS, archives and workflow systems
  • ERP, CRM, finance and specialist systems
  • Data models, validation rules and retention policies

What requires particular care

  • Validate extracted values against data models and business rules
  • Route uncertain or incomplete cases to people
  • Do not allow AI alone to make legally or financially binding approvals
  • Address personal data, retention and audit trails throughout

Relevant next steps

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Practical knowledge

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Which use case fits your current situation?

We structure the task, data, systems and risks and propose a testable first scope.

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