A Simple Ideation Framework for AI-powered Tasks/Systems

Every thing that we offer or build performs a "task" for the user/consumer or does a "job" for them. If we have built it right, the "job" done/performed is valuable, reliable, safe, and worthy of the consumer's time, effort, and money. Product practitioners often use the popular JTBD (or Jobs To Be Done) framework when trying to think through the need and utility of an idea, solution, service, widget, etc.

AI is a tool. The choice of how it gets deployed is ours.

When we narrow the context down to the idea of leveraging AI for performing our own or our customer's tasks/jobs, we must make decisions based on answers to the following 4 questions -

• Where/how can we leverage AI?
• Will the AI-powered outcomes be superior?
• Will we be able to manage the AI related risks in a responsible way?
• Will we be able to explain the inner workings of this AI system and its outcomes?

Now lets break each of these 4 questions down further.

Q. Where/how can we leverage AI?        

My proposed ideation framework lists 10 different use cases, tasks, or jobs that an AI agent or system can solve a lot better than a human (yes, there are always exceptions). So start by picking one or a few of these areas where you believe you can use an AI agent/system.

Q. Will the AI-powered outcomes be superior?        

Once you have identified the use case, next you will need to evaluate if AI will lead to a smarter and faster process and results for your organization and mission. Intuition is certainly handy here but it would be better to setup and run a small experiment (i.e. build a prototype), measure the results, and extrapolate from there.

Q. Will we be able to manage the AI risks in a responsible way?        

Lets say the results of the AI-powered system are promising. You will now need to understand the risks posed by the new system (or its skinny prototype), determine their likelihood and blast radius, and figure out how you will mitigate or manage the risk(s). These risks should cover all dimensions including business, brand, customer, operations, technology, and regulatory. It might just turn out that the risks far outweigh the benefits. Or you may deem the benefits are worthy of taking the risks!

Q. Can we explain how the AI system works and produces its outcomes?        

You will have to be able to explain in simple terms and plain English, how the AI system works, what all it uses, and why the results are superior, reliable, safe. Explainability is what can make or break trust and confidence with your stakeholders and regulators. So you must take this final piece of the puzzle very seriously.

To recap, I encourage you to use my framework or one of your own as long as it aligns with and/or exceeds mine. Do not try to be a hero or a first-mover or even a fast-follower. Approach the introduction of and need for AI as a product opportunity, and bring product thinking and responsible mindset to its analysis.

When it comes to AI, crawl before you walk. And you will always be on a solid footing!

PS: If I can be help you with your AI product strategy or initiatives, don't hesitate to reach out.

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