Start With The Customer Problem, Not The Technology

Generative AI is still looking for its killer app. Sure, there is a niche number of people getting great results using LLMs for work and other activities to be more efficient and productive. Still, most of the existing generative AI solutions out there are hunting for a problem to solve.

Lots of experimentation going on, where teams are throwing ideas at the wall to see what happens. It’s all good, but you have to solve a real customer problem if you want to drive business results. Simply adding some AI to something won’t make it better. You have to start with the problem, not the technology.

“There is only one boss: the customer. And he can fire everybody in the company, from the chairman on down, simply by spending his money elsewhere.” – Sam Walton, founder of Wal-Mart

You have to start with the customer and work backward. “It all starts with the customer” is a keystone principle for business. The AI space is moving quickly, but the fundamentals of business don’t change:

  • Who is the customer?
  • What need are you solving for them?
  • How do you reach that customer?
  • What is your differentiation?
  • How are you ten times better than what they otherwise have?

Building a wrapper around an LLM such as ChatGPT or Claude is not a sustainable business. But if you’re solving a real customer problem and you have differentiation such as access to unique data, it could be unique insights that you have, or even how you bring it to market, your business will be on the right path.

It sounds catchy to be AI first, but it still comes down to who can solve real problems for people best. Also, customers don’t care if you’re using AI or not; they care about getting their problem solved.

With that said, ask yourself: What does the customer need to accomplish and how can we best use generative AI to help them?

Bottom line: Start with the problem, not the technology. Remember, technology is an enabler. It helps unlock new capabilities that didn’t exist before. Take the time to understand a problem, and then think about how generative AI can help.