AI Production Governance Toolkit – Excel XLSX

BENEFITS OF THIS DOWNLOADABLE EXCEL DOCUMENT

1. Closes the gap monitoring tools leave open. Turns an assumption -- "governance is probably happening" -- into a documented, scored record that can be produced on demand for an auditor, regulator, or board.
2. One weak criterion can't hide behind a good average. The automatic No-Go trigger fires on any single criterion scored 1, so a strong overall Gate Score never masks one serious unresolved gap.
3. Runs without pulling an ML engineer into the room. All 15 monthly indicators are dropdown-based and designed for a Programme Manager or Governance Lead, so ongoing oversight doesn't stall waiting on technical bandwidth.

ARTIFICIAL INTELLIGENCE EXCEL DESCRIPTION

AI Production Governance Toolkit is an Excel template (XLSX) with a supplemental PDF document available for immediate download upon purchase.

Once an AI model reaches production, monitoring dashboards report what the model is doing minute to minute. They say nothing about whether the human oversight built into the deployment plan is still functioning: whether the review process agreed at go-live is being followed, whether the business owner has looked at this month's outcomes, whether overrides are being logged, or whether regulatory obligations are being tracked rather than assumed. Those are governance questions, and no MLOps platform answers them.

The AI Production Governance Toolkit is a Microsoft Excel workbook – six tabs, no macros, no password protection – that gives AI programme teams a structured instrument for both moments: the deployment decision and the ongoing oversight that follows it.

Module 1, the Pre-Production Gate, assesses 19 criteria across five weighted dimensions – model performance validation, operational infrastructure, human oversight and controls, business readiness, and documentation and compliance. Each criterion is scored 1 to 5, producing a weighted Gate Score and a formal Go/No-Go recommendation. Any single criterion scored 1 triggers an automatic No-Go, so a strong average cannot conceal one critical gap.

Module 2, the Monthly Governance Review, checks 15 indicators across four categories – oversight and controls, platform and operations, business and adoption, and risk and compliance – once a month for as long as the model stays in production. Every indicator is a dropdown response designed for a Programme Manager or AI Governance Lead, not an ML engineer, and produces a Governance Health Score with a Healthy, Watch, or At Risk status.

An Executive Dashboard rolls both modules into a single view – Gate Score, Governance Health Score, indicator status, and a six-month trend – built for a steering committee agenda item. An Evidence & Log tab archives up to two years of monthly snapshots, giving audit and regulatory reviews a documented trail.

The toolkit does not instrument models, connect to data pipelines, or replace monitoring platforms such as MLflow, Azure ML, Vertex AI, or Prometheus – it governs the human layer that sits above them. References to EU AI Act and DPDP Act obligations are structured prompts to act, not legal advice; compliance determinations should be confirmed with qualified counsel.

Delivered as an Excel workbook (.xlsx) with a full user guide, compatible with Excel 2016 and above, including Microsoft 365. Organisation-wide licensing beyond the scope of this listing is available directly from the publisher

Source: Best Practices in Artificial Intelligence Excel: AI Production Governance Toolkit Excel (XLSX) Spreadsheet, Viksya