How to launch a successful AI Use Case discovery campaign

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From chaos to clarity: How to launch a successful AI Use Case discovery campaign

As organizations scale their use of Artificial Intelligence (AI), the ability to identify and track all AI use cases across departments becomes both a compliance necessity and a strategic asset. This is especially true under frameworks like the EU AI Act, where ignorance is no defense: if it’s in production, it’s in scope.

At Yields, we believe robust AI governance starts with something deceptively simple: visibility.

The Challenge: You can’t govern what you can’t see

Before any risk assessment, documentation, or validation can happen, organizations must first know what AI systems they are actually using. Sounds obvious, right?

Yet many institutions, even highly regulated ones, struggle to answer basic questions like:

• Are they compliant by design?
• What AI systems are in production?
• Who owns them?
• What data powers them?

The Solution: The AI Inventory Attestation Campaign

This is why Phase 2 of our AI governance framework centers on a structured, organization-wide use case identification campaign. Here's how it works:

1. Familiarize with definitions: Ensure key roles understand what counts as an AI use case, a model, a component, or a dataset. (Hint: not everything with an algorithm is a model, and not all models are AI.)
2. Mobilize your AI ambassadors: These trained champions help drive adoption across the business, bridging technical and operational silos.
3. Launch the campaign: With support from the AI Board, reach out to business lines, data science teams, IT, and third-party vendors to uncover all AI-related initiatives.
4. Register each use case: Use structured templates (like those in our whitepaper) to collect business context, lifecycle status, responsible parties, and technical specifics.
5. Break it down: For each use case, clearly identify its models, components, and datasets. This decomposition is essential for future risk tiering and auditability.
6. Close the loop, but keep it alive: Publish campaign statistics and schedule the next round. AI governance is a living process, not a one-off project.

What you gain

• A central AI inventory that supports transparency and audit readiness.
• Clear ownership and accountability for each use case.
• A scalable foundation for risk management, lifecycle governance, and EU AI Act compliance.

Ready to go beyond discovery?

This article is just one slice of a complete, practical guide to managing AI risk across the full model lifecycle. Our whitepaper covers everything from defining roles and responsibilities, to aligning with the EU AI Act, to running a risk-based governance program that works in the real world.

This whitepaper is your practical playbook for building robust, scalable, and EU AI Act-ready governance, without the bureaucracy.

This guide gives you:

• A clear, role-based AI governance model
• Concrete steps for identifying, assessing, and managing AI risks
• A lifecycle approach aligned with the EU AI Act
• Real-world case studies and common pitfalls
• Tips to embed trust and accountability into every AI system

Whether you're starting your AI journey or scaling fast, this is the governance foundation you need to move with confidence.

Download the whitepaper now and start operationalizing trust in your AI.