What is an AI Use Case?

An AI Use Case is a specific business problem or opportunity where artificial intelligence can deliver measurable value. It defines what you want to achieve, why AI is the right solution, what data and resources are required, and how success will be measured.

For SMEs, identifying the right AI use cases is crucial for successful adoption. Strong use cases have several characteristics: clear business value, availability of quality data, feasibility with current technology, manageable scope, and stakeholder support. Examples include predicting customer churn, automating invoice processing, personalizing product recommendations, forecasting demand, or detecting fraud.

Developing an AI use case involves several steps: identifying the business problem, assessing data availability, evaluating technical feasibility, estimating costs and benefits, defining success metrics, and securing stakeholder buy-in. It's important to be specific—instead of 'improve customer service,' a good use case might be 'reduce average response time to customer inquiries by 50% using an AI chatbot.'

Prioritizing use cases requires balancing multiple factors: business impact, technical feasibility, data readiness, resource requirements, and strategic alignment. Many SMEs use frameworks like the AI Use Case Prioritization Matrix to systematically evaluate and rank opportunities. The goal is to identify 'quick wins' that deliver value quickly while building capabilities for more complex initiatives.

Successful use case implementation requires cross-functional collaboration between business stakeholders, IT teams, and data experts. Start with pilot projects to validate assumptions, measure results, and refine the approach before scaling. Document lessons learned and use them to improve future use case selection and implementation.