AI STRATEGY
Operationalize AI Governance from Day One
Stay Legal as You Scale
As regulations for AI tighten worldwide, aligning early with data protection, consent, and transparency requirements will keep your product on the right side of the law.
Why it's Important
Avoids legal penalties or forced product changes
Streamlines investor and partner due diligence
Future-proofs your product for international growth
Builds user trust through transparency and consent
Improves internal understanding of compliance boundaries
How to Implement
Review major frameworks (e.g., EU AI Act, GDPR, CPRA, Bill C-27)
Map product features to relevant compliance domains
Track data lineage from source to inference
Draft internal AI use and model documentation
Secure legal and privacy team review
Create user-facing disclosures and opt-in flows
Monitor regulatory changes and update policies
Available Workshops
Regulatory Readiness Workshop
Feature-to-Framework Mapping
Data Lineage Diagram Jam
Consent Language Review
Global Launch Risk Assessment
Compliance Partner Deep Dive
Deliverables
Compliance checklist by jurisdiction
AI use and limitation doc
Legal sign-off tracker
Consent and disclosure UI copy
Regulatory change monitoring plan
How to Measure
Number of applicable laws mapped to product features
% of updates triggered by regulation change
% of features with privacy/compliance review
Audit pass rate for model documentation
Stakeholder alignment on compliance priorities
Legal team satisfaction with review pipeline
Pro Tips
Maintain a shared compliance wiki
Host cross-functional regulation-readiness check-ins
Include “AI governance” in investor FAQs
Use model cards and datasheets as documentation aids
Plan for extra review time in regulated industries
Get It Right
Build a regulatory risk register
Assign a compliance lead or advisor
Proactively disclose limitations in your product
Make legal review a phase in product launch
Prioritize transparency over legal minimalism
Don't Make These Mistakes
Assuming North American standards apply globally
Hiding complexity from legal or compliance teams
Using vague terms in disclosures or opt-ins
Delaying regulatory prep until just before launch
Not tracking changes in AI laws quarterly