A structured approach to identifying high-value AI opportunities and making informed investment decisions
With limited resources and numerous potential AI applications, effective prioritisation is crucial to ensure you focus on use cases that deliver the most value. The AIVAL prioritisation framework helps you:
The potential value the use case could deliver to your organisation, considering:
How easily the use case can be implemented, considering:
High Impact, High Feasibility
These use cases offer significant value and can be implemented relatively easily. They should be your top priority as they provide the best return on investment.
High Impact, Low Feasibility
These use cases offer significant value but are more challenging to implement. They require careful planning and may need to be broken down into smaller phases.
Low Impact, High Feasibility
These use cases are easy to implement but offer less value. They can be good candidates for quick demonstrations or to build momentum for your AI initiatives.
Low Impact, Low Feasibility
These use cases offer limited value and are difficult to implement. They should generally be avoided or reconsidered.
Ensure each use case has a clear description, business problem statement, and expected benefits.
Include stakeholders from business, IT, data science, and subject matter experts relevant to the use cases.
For each use case, score both business impact and implementation feasibility on a scale (e.g., 1-10).
Place each use case on the prioritisation matrix based on its scores.
Review the matrix as a group, discuss any disagreements, and adjust scores if necessary.
Based on the matrix, create a roadmap for implementing use cases, starting with Quick Wins.
Business Impact:
Implementation Feasibility: