Can we trust the figures without checking them?

No. Reporting AI produces review-ready drafts; figures are validated by people before being shared or acted on. It never presents unvalidated numbers as final.

What data can it use?

Only approved, connected data sources, accessed with scoped permissions. It does not fabricate data to fill gaps.

AI Workforce · Reporting

Reporting AI

Reporting AI is a worker that assembles recurring reports and dashboard narratives from approved data sources into review-ready drafts. It removes the repetitive assembly of periodic reporting, while figures and interpretation are validated by people before anything is shared or acted on.

Adil Mektoub

Published 13 July 2026Last reviewed 13 July 2026

Business responsibilities

Assembling recurring operational and management reports.
Drafting narrative summaries around the numbers.
Consolidating data from multiple approved sources.
Highlighting notable changes for review.

Supported systems and integrations

Subject to integration scope, connected through official APIs with scoped access:

BI and analytics tools
Spreadsheets and databases
CRM and operational systems (read access)
Document storage

Actions it can perform

Key takeaways

Assemble reports from approved data sources.
Draft narrative summaries and highlights.
Flag notable changes and anomalies.

Actions requiring human approval

These actions never run automatically — they wait for explicit human approval:

Any report shared with stakeholders or clients.
Interpretations that drive decisions.
Publishing figures as official.

What Reporting AI does not do

Limitations & honest caveats

It does not present unvalidated figures as final.
It does not make decisions from the reports it produces.
It does not fabricate data to fill gaps.

Data and knowledge requirements

Access to approved, reliable data sources.
Defined report structures and definitions.

Monitoring and auditability

Audit trail of data sources and report versions.
Human validation of figures before sharing.
Checks for data completeness and consistency.

Relevant KPIs

Measured against KPIs defined before deployment — never against invented figures:

Reporting preparation time
Report accuracy after review
Data consolidation time
On-time reporting rate

Risks and limitations

Limitations & honest caveats

Report accuracy depends on the quality of source data.
Narratives require human validation before they inform decisions.
It assembles and drafts; it does not decide.

FAQ

Frequently asked questions

Can we trust the figures without checking them?: No. Reporting AI produces review-ready drafts; figures are validated by people before being shared or acted on. It never presents unvalidated numbers as final.
What data can it use?: Only approved, connected data sources, accessed with scoped permissions. It does not fabricate data to fill gaps.

Author

Adil Mektoub

Founder · Engineering & AI Infrastructure

France-based AI platform engineer. Age 36. E-mobility AI background; SAP and Vitol.

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Related resources

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