Finding Problem-Solution Fit With Generative AI

Have you heard of the shiny object syndrome?

In the unforgiving race of technological advancement, businesses often find themselves facing a challenge: how to drive value with emerging technologies like Artificial Intelligence (AI), and especially its most recent form, generative AI. The temptation to just jump in and experiment is high, but it is critical to take a strategic and targeted approach that will yield results justifying the investment. This is where Lean Startup's principle of Problem-Solution Fit comes into play.

Embracing the Problem-Solution Fit Principle

The Problem-Solution Fit is all about establishing a match between a market need (a problem) and a specific offering (a solution). This involves deeply understanding your customer's needs and then designing a product or solution that adequately addresses those needs. Consider it an antidote to the widespread issue where businesses sink resources into chasing technically impressive solutions that fail to satisfy a clear market need or engage its target users.

It's about not just building things right, but building the right things.?

Step One: Get to Know Generative AI’s Strengths

Generative AI brings to the table an impressive array of capabilities, such as knowledge management, question answering, content creation, text completion and summarization, text and image generation, and more. But instead of focusing on the capabilities, we’ll look at the business problems it’s especially adept at solving.

Step 2: Finding the High-Match Areas

The next step is to identify areas in the business where there's a high match between problem areas and the strengths of generative AI.

For example, if a business struggles with streamlining internal communication, a chatbot with question-answering capabilities could be a feasible solution. If content creation for marketing is time-consuming, generative AI can help automate and enhance the process. This assessment can be done a number of ways, but consider starting with areas in the business where (a) operational efficiency is low (b) or high-stakes areas of business that can drive revenue.

Share the list of GenAI strengths and have business segment leaders evaluate (e.g., a 1-5 rating) how relevant those challenges are for their teams. You can then focus on the teams who expressed the highest problem-solution match. The goal here isn’t simply to find one interesting problem but to cast a wide net so you can build a portfolio of use cases. Then, with your opportunity list, you can start to dig into the next level of questions – value potential, number of employees facing the challenge, applications/systems used, etc.

Driving Real Value with AI

Remember, the power of AI doesn’t come from its technical prowess alone. It comes from the ability to apply it to the right problems. Identifying these problems, understanding them deeply, and then strategically deploying generative AI to solve them – that's where the true power of AI lies for your business.