MAST Consulting Group · 8 September 2026 · Implementation perspective
Look beyond the data science team
AI may be embedded in SaaS products, employee copilots, customer-service tools and external APIs. Invite procurement, IT, business owners and security teams to identify both formally approved systems and informal adoption.
Record the decisions that matter
For each system, record its purpose, business owner, provider, data categories, users, affected stakeholders and lifecycle stage. Include links to risk assessments, approval decisions and supplier reviews so the inventory becomes an operational reference.
Make ownership explicit
Assign a business owner who understands the intended outcome and a technical contact who understands the implementation. An inventory entry should make it clear who can approve a change and who responds when something goes wrong.
Keep the inventory alive
Connect registration to procurement, use-case intake and change management. Schedule reviews and require updates when models, providers, data sources or intended uses change. Start with the AI System Inventory template in the toolkit and adapt the fields to your organization.
Put it into practice.
Explore the AI governance toolkit or discuss your organization’s next step.