The buzz around artificial intelligence is deafening. Every company wants a piece of the AI pie (and who can blame them?). But before you go full AI mode, it’s crucial to have a game plan. And that starts with covering your bases: shaping the AI use case, so you can start discussing it with ML experts.

How? Start with these 3 logical steps. 

Step 1: Identify the problem

The journey begins with a clear understanding of the problem you aim to solve. If there’s no problem, it’s useless to start looking for solutions. Using the battle-tested user story format can help you state the challenge effectively:

• We want to…: Address your core problem
• For…: Identify the target audience or stakeholders.
• Aiming to achieve…: Define the desired business impact of your solution. 

This simple, yet all too often overlooked, basic approach ensures you’re aligned about which actual problem your AI feature or product is trying to solve. Time for step two. 

‍Step 2: The path from data to action

Now, no solution with no data. It’s crucial to define your journey from raw data to actionable insights. This involves understanding your data sources, extracting relevant information, making informed decisions and triggering actions. Or explained in simpler terms:

• Data: What raw data do you start from?
• Information: What key insights are derived from the data?
• Decision: How are these insights used to make decisions?
• Action: What actions are triggered based on these decisions?

Ready for step three?

Step 3: Validate & measure

Validation and measurement are cornerstones of any successful product, feature or business decision. The same goes for every AI initiative. It’s key to define early indicators of success and establish metrics to measure that success. Always try considering these data buddies:

• Values: Identify the potential impact of the AI solution. Is it a time-saver? Revenue generator? Or for scoring some innovation points? 

• Metrics: Define key performance indicators to measure the success of your AI solution. Compare current performance with the expected outcomes to gauge your effectiveness.

By setting clear benchmarks, goals and metrics, your business can easily track progress, stay aligned and make informed decisions throughout the AI implementation process. 

Take it up a notch?

Following these three steps already gives you a solid foundation for evaluating AI opportunities and mitigating risks. However, businesses can further enhance their strategic approach with tools like our AI Value Canvas. A great way for organisations to explore, test, and refine AI concepts before betting the bank. Download it here for free and go test out your AI feature.

Need help? We’ve done this hundreds of times for a wide range of industries. Give us a shout and we’ll help you get started.