A tailored course, built for your situation
Fixing the AI Governance Spreadsheet That Breaks Every Month
A 12-module system to automate compliance tracking for AI initiatives without waiting for central teams
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
The AI governance tracking spreadsheet that breaks every time a new project is added or a column is changed
The situation this course is for
Every month, the same thing happens: a new AI initiative launches, someone adds it to the master compliance tracker, and the validation rules break. Tabs get duplicated. Statuses go stale. Stakeholders revert to email chains. You end up rebuilding the view from scratch , again , just to get sign-off. This isn't governance failure. It's a tracking system that can't scale to real-world velocity. And you're paying senior time to duct-tape a process that should be automatic.
Who this is for
Senior AI and data leaders in regulated environments who are accountable for compliance but lack dedicated tooling or central support to operationalize it
Who this is not for
Teams already using GRC platforms with AI modules, or those with dedicated AI governance tooling supported by central engineering
What you walk away with
- A working, version-stable AI compliance tracker that updates automatically when projects change
- Elimination of monthly rework cycles for governance reporting
- Stakeholder-aligned dashboards that reduce follow-up questions by 70%
- A reusable template library for AI risk classification, model tiering, and control mapping
- Confidence to scale AI governance across 10x more initiatives without adding headcount
The 12 modules (with all 144 chapters)
Module 1. Why the Spreadsheet Breaks (And What to Put in Its Place)
Break down the structural flaws in current AI compliance tracking methods and introduce the core replacement pattern: lightweight, stakeholder-driven templates with automated validation.
12 chapters in this module
- The myth of the single source of truth
- Three failure points in shared spreadsheets
- Why permissions cause cascading errors
- How version drift undermines audit readiness
- The cost of manual reconciliation
- Sign-off delays from unclear ownership
- When real-time updates become impossible
- Over-reliance on individual expertise
- Template sprawl across teams
- Lack of integration with project intake
- How control mapping gets lost in cells
- The false economy of free tools
Module 2. Mapping Real AI Governance Workflows
Identify the actual decision pathways your team follows , from project intake to audit , and map them to repeatable, trackable steps that don’t depend on memory or email.
12 chapters in this module
- Stages every AI initiative actually passes through
- Where approvals bottleneck
- Common handoff gaps between teams
- How risk tiering gets inconsistently applied
- Tracking model development vs deployment
- Identifying decision dependencies
- Documenting exemption requests
- Handling retrospective tagging
- Integrating legal and ethics reviews
- Managing cross-jurisdictional rules
- Capturing model updates and retraining
- Closing out retired models
Module 3. Designing Stakeholder-Aligned Templates
Build templates that serve both compliance needs and delivery speed by aligning fields to what reviewers actually care about , not just what auditors ask for.
12 chapters in this module
- The three questions every reviewer asks
- Reducing fields to decision essentials
- Naming conventions that prevent confusion
- Color coding without ambiguity
- Status definitions everyone agrees on
- Automated routing triggers
- Embedding evidence links directly
- Versioning without duplication
- Role-specific view filters
- Audit-ready formatting by default
- Handling multilingual teams
- Mobile-accessible layouts
Module 4. Automating Validation Without Code
Set up rule-based checks that flag misclassified projects, missing controls, or expired reviews , using tools already approved in regulated environments.
12 chapters in this module
- Validation rules that prevent errors
- Flagging high-risk models automatically
- Deadline reminders for review cycles
- Detecting unapproved framework changes
- Blocking incomplete submissions
- Validating ownership assignments
- Checking for cross-border data use
- Enforcing model documentation standards
- Auto-failing missing evidence links
- Detecting duplicate or shadow projects
- Scoring compliance completeness
- Escalating overdue items
Module 5. Integrating with Project Intake Early
Shift governance left by embedding compliance checks at the start of every AI initiative, so tracking begins before development starts.
12 chapters in this module
- The ideal project onboarding flow
- Required fields for intake forms
- Auto-creating tracker entries
- Assigning initial risk tiers
- Routing to reviewers based on scope
- Capturing data sources upfront
- Flagging third-party dependencies
- Recording intended use cases
- Identifying affected stakeholders
- Setting initial review timelines
- Linking to architecture blueprints
- Triggering control mapping
Module 6. Building Dashboards That Reduce Follow-Up
Create live views that answer the same stakeholder questions before they’re asked , reducing email churn and meeting time.
12 chapters in this module
- Top five stakeholder questions
- Building status-at-a-glance views
- Filtering by risk tier
- Showing control coverage gaps
- Highlighting upcoming deadlines
- Displaying approval chains
- Tracking team workloads
- Visualizing deployment velocity
- Mapping compliance by business unit
- Showing audit readiness scores
- Exporting readouts for leadership
- Embedding dashboards in portals
Module 7. Handling Exemptions and Escalations
Design a transparent, auditable process for exceptions that doesn’t become a loophole , and doesn’t stall projects.
12 chapters in this module
- Defining valid exemption reasons
- Required justification fields
- Setting expiration dates
- Routing to approvers by risk level
- Capturing mitigating controls
- Tracking temporary vs permanent exceptions
- Notifying when reviews are due
- Linking to incident history
- Reporting on exemption frequency
- Auditing approval chains
- Auto-closing expired exemptions
- Flagging repeated requests
Module 8. Scaling Across Teams Without Chaos
Replicate the system across multiple delivery pods while maintaining consistency, ownership, and audit integrity.
12 chapters in this module
- Defining central vs local ownership
- Standardizing templates across units
- Managing domain-specific variations
- Training team champions
- Auditing local compliance
- Sharing best practices
- Handling conflicting priorities
- Resolving version conflicts
- Merging regional requirements
- Tracking adoption rates
- Reducing cross-team duplication
- Enabling peer reviews
Module 9. Preparing for Audit Without Panic
Generate evidence packs automatically so audits become routine , not crisis events.
12 chapters in this module
- Common auditor requests
- Pre-building evidence folders
- Linking controls to frameworks
- Showing decision trails
- Exporting approval histories
- Generating compliance scores
- Highlighting high-risk areas
- Documenting exemption patterns
- Proving consistency over time
- Showing training completion
- Demonstrating update cycles
- Archiving retired models
Module 10. Maintaining the System Without Burnout
Put ownership, monitoring, and updates on autopilot so the system stays alive without constant oversight.
12 chapters in this module
- Assigning system stewardship
- Setting up health checks
- Monitoring for drift
- Updating templates safely
- Versioning change logs
- Training new owners
- Automating backups
- Alerting on anomalies
- Reviewing access permissions
- Handling offboarding
- Auditing system changes
- Planning for scale
Module 11. Connecting to Broader Risk & Control Frameworks
Align the tracker to existing the firm risk taxonomies and control libraries so it integrates , not competes , with enterprise practice.
12 chapters in this module
- Mapping to internal risk categories
- Linking to control IDs
- Aligning with data governance
- Integrating with security frameworks
- Connecting to privacy programs
- Feeding into risk registers
- Reporting to oversight teams
- Using standard nomenclature
- Avoiding duplicate entry
- Syncing with compliance calendars
- Supporting internal audit
- Demonstrating policy adherence
Module 12. Sustaining Adoption Through Change
Ensure the system sticks , even after leadership changes , by embedding it into rituals, incentives, and review cycles.
12 chapters in this module
- Onboarding new team members
- Incentivizing accurate reporting
- Tying to performance reviews
- Holding lightweight standups
- Celebrating compliance wins
- Sharing improvement metrics
- Soliciting feedback loops
- Updating based on input
- Linking to promotion criteria
- Recognizing contributors
- Measuring time saved
- Scaling to adjacent domains
How this maps to your situation
- After a new AI initiative is approved
- When compliance tracking breaks mid-cycle
- Before audit season begins
- During tooling budget planning
Before vs. after
Before
Spending days each month rebuilding AI compliance trackers, chasing updates, and re-explaining status because the spreadsheet breaks when projects change.
After
Running a stable, self-updating system that reduces monthly rework to under an hour and gives stakeholders real-time clarity , no more version chaos.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed to be completed in parallel with ongoing work , most practitioners finish in under 6 weeks.
If nothing changes
Continuing to rely on fragile spreadsheets increases the odds of a control gap slipping through , not because of intent, but because of broken tracking. That creates exposure when scrutiny rises, and forces you to divert focus from innovation to cleanup.
How this compares to the alternatives
Generic GRC platforms require months of configuration and central IT support. Off-the-shelf templates don’t reflect how the firm teams actually operate. This course delivers a working system in days , tailored to the realities of high-velocity AI delivery in professional services.
Frequently asked
Is this about replacing our GRC platform?
No. This is for teams without one , or those waiting for access. It’s a lightweight, immediate alternative that works with what you already have: spreadsheets, shared drives, and email.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this work if we’re using Microsoft 365 or Google Workspace?
Yes. The system is tool-agnostic and works within both environments using built-in automation and permissioning.
$199 one-time. Approximately 3 hours per module, designed to be completed in parallel with ongoing work , most practitioners finish in under 6 weeks..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours