How to Build an AI Use Case Inventory

Artificial intelligence is becoming part of everyday business operations, from customer support and data analysis to workflow automation and decision-making. As more teams adopt AI tools, organisations need better visibility into where these systems are being used and how they impact business processes. T3 helps organisations understand and manage AI systems through governance, risk management, and assurance services that support safer AI adoption. 

An AI Use Case Inventory gives businesses a clear record of their AI applications, helping teams track ownership, usage, risks, and compliance needs. It creates a foundation for organisations that want better control over their growing AI landscape.

 

 

Key Takeaways

1. An AI use case inventory is a tool that enables an organization to discover and monitor every application of artificial intelligence within various departments.

2. Maintaining a healthy inventory facilitates the building of AI governance frameworks and enhances transparency around AI-related risks.

3. Documenting details such as ownership, data usage, and risk levels helps businesses prepare for AI compliance requirements.

4. A structured inventory makes it easier for teams to review AI systems and support responsible AI adoption.

5. Organizations can use an AI Use Case Inventory Template to create consistency when recording AI applications.

What is an AI Use Case Inventory?

An AI use case inventory is a key inventory that provides details about all AI systems, tools and applications being employed across an organisation. It offers information regarding the functions/processes of the AI system, its management, the data it processes and its use to enable business activities.

There are multiple AI solutions in use across various teams within many organisations without a clear view of how they are being utilized. Employees can use AI assistants, automated tools, or other third parties without formal tracking processes.

An inventory can assist businesses in answering some key questions:

1. What currently existing AI systems are being used?

2. Which entity is responsible for every AI use-case?

3. What type of data does the system process?

4. What risks should be reviewed?

Having this information allows companies to build stronger Enterprise AI governance practices and create better oversight of their AI environment.

Why Do Organisations Need an AI Use Case Inventory?

While AI presents new opportunities, it also introduces areas to be managed. Without proper documentation, organisations may struggle to identify security concerns, compliance gaps, or unclear ownership.

An AI use case inventory can assist businesses:

1. Improve visibility across AI applications and departments

2. Risk Assessment Prior to Deployment

3. Help internal review and governance procedures

4. Monitor the use of third party AI tools in the organisation

5. Compile information for future regulatory requirements

A clear inventory also aids in AI risk management by providing teams with guidance on which systems deserve more scrutiny, depending on their intended use, data usage, and effects.

A documented record of AI systems can help organisations align with the AI compliance framework and its changing requirements, particularly for regulated industries.

What Should be in an AI Use Case Inventory?

A useful inventory should be able to provide enough information for teams to consider and review each individual AI system.

Some aspects that might be covered are:

Inventory Information	Purpose
AI Use Case Name	Identifies the application
Business Department	Shows where the AI system is used
Owner	Defines responsibility
Purpose	Explains the reason for using AI
Data Sources	Shows what information the system processes
AI Provider	Identifies internal or external solutions
Risk Level	Helps prioritise reviews
Review Date	Keeps records updated

Including these details helps teams develop a comprehensive understanding of their AI environment.

How to Build AI Use Cases Step by Step

Many organizations begin by asking how to develop AI use cases that align with business objectives while ensuring adequate oversight. Building an inventory requires gathering information from different teams and documenting each AI application carefully.

1. Identify Existing AI Applications

Before you begin, review existing tools, systems and projects that members of your organisation are already using that involve AI.
This includes:

• • Applications that already incorporate AI.

• • Internally-developed AI models.

• • Third-party AI platforms

• • Generative AI tools

• • The use of AI in current software applications. 

Conversations with other departments could identify possible uses of AI that are not documented.

2. Record key details and assign ownership

Every AI system should have a responsible owner who understands its purpose and usage.

Put the following information in a Record:

• • Business purpose

• • Users involved

• • Technology provider

• • Data handled

• • Expected outcomes

Having clear ownership facilitates the effective management of AI systems within an organisation.

3. Review Risks and Compliance Needs

Any use of AI should be assessed on a case-by-case basis, taking into consideration how it might be used and how it could affect people.

Businesses may assess:

• • Data security concerns

• • Privacy requirements

• • System reliability

• • Regulatory obligations

AI risk assessment services can assist organisations in pinpointing potential risks and implementing appropriate risk controls.

What to include in the AI Use Case Inventory Template?

An AI Use Case Inventory Template is a tool that can be used to gather information in a standardized format. While every organisation may have different requirements, a basic template can include:

• • AI system name

• • Business function

• • Description of the use case

• • Data sources

• • System owner

• • Risk category

• • Compliance status

• • Review schedule

A structured template makes it easier for teams to maintain accurate records as new AI applications are introduced.

How AI Governance Helps Manage Your Inventory

An inventory is an essential component of an overall AI governance plan. It enables organisations to appreciate their AI position before developing their policies, controls and review procedures.

Good governance practice can involve:

1. 1. Regular inventory reviews

1. 1. Risk classification

1. 1. AI system documentation

1. 1. Security evaluations

1. 1. Performance monitoring

AI model testing and assurance services can also help organizations assess AI systems and ensure they meet their requirements.

Good governance approaches foster responsible practices with regard to the use of AI and assist businesses in readiness for upcoming regulations and internal needs.

Gathering accurate data from various functions

Common Challenges When Creating an AI Use Case Inventory

Building an inventory could be difficult for organisations with numerous teams and AI applications.

• • Common issues include:

    Recognizing undocumented AI tools

• • Gathering accurate data from various functions

• • Maintaining records that are current with the changing nature of AI systems.

• • Being aware of the risks associated with third-party solutions

Regular reviews and clear ownership help organizations maintain a reliable inventory over time.

Final Thoughts

AI adoption is growing across industries, making visibility and governance essential for organisations that want to manage their AI systems effectively. An AI use case inventory offers a meticulous method for managing applications, comprehending risks, and informing more effective decisions.

Building this foundation helps businesses create stronger governance processes and prepare for future AI requirements. Through AI governance solutions, expert advice, risk assessments, and assurance services, T3 empowers organisations to enhance their governance frameworks and ensure the secure and responsible use of AI.

Looking for enhanced visibility throughout your AI systems? Explore how T3 can help your organisation build a stronger AI governance strategy and manage AI risks with confidence.

FAQs

1. What is an AI Use Case Inventory?

An AI Use Case Inventory is a record of all AI systems and applications used within an organisation. It includes details such as ownership, purpose, data usage, and risk level.

2. Why is an AI use case inventory important?

It helps organizations understand where AI is being used, identify risks, improve governance, and prepare for regulatory requirements.

3. What should be included in an AI inventory?

An AI inventory should include information about the AI system, business purpose, owner, data sources, provider, risk classification, and review schedule.

4. How often should an AI inventory be reviewed?

Organisations should review their inventory regularly to capture new AI applications, system updates, and changes in compliance requirements.

5. How does AI testing support inventory management?

AI testing helps organisations evaluate system performance, reliability, and risks. Services such as AI model testing and assurance can support stronger oversight of AI applications.