Recently, we were facilitating a big workshop with a major technology company. The presenter— schooled in design thinking but not a tech expert—presented an exercise for the group to map technologies against a two-by-two matrix: solution versus problem and known versus unknown. While introducing the matrix, the presenter rather sarcastically made the suggestion that AI should be in the “known solution / unknown problem” quadrant of the matrix, meaning that AI is a solution looking for a problem.
The technology experts in the room bristled. His comment demonstrated a fundamental misunderstanding of AI.
AI is what’s called a “general purpose technology” that has the potential to affect an entire economy or society. Adoption of a GPT initially has a lot of room for improvement but eventually it diffuses widely across an economy. Examples of GPT’s include written language, electricity and the internet.
In the early days of the internet, companies response to the new technology fell into three classes:
Companies that ignored the internet (#1) fell behind in their industries and some never recovered. Thinking of the internet as a solution looking for a problem was clearly the worst decision to make.
Companies that just followed the herd (#2) didn’t make an effort to understand what the web was about. These companies didn’t develop the capabilities and skills at all levels of the organization. They didn’t figure out what the world would be like when everyone was connected, all the time. They saw the web simply as a staging post for their physical world. They thought their “problem” was expressing their brand to potential customers and thought the “solution” was a website. They didn’t understand that the internet created a new, interconnected and dynamic online world that required understanding their problems in new ways.
Companies that made the effort to understand the internet (#3) thought differently. These companies understood that the web would change the economics of everything—the power of the “long tail” to completely disrupt brands is now obvious only in hindsight. These companies didn’t think of problems and solutions; instead they reframed everything they did around the economics of the internet.
We’d never recommend applying technology for technology’s sake. Any investment in technology needs to provide value, address pain points and solve problems. That is true for AI as well. But, given the scale of potential applications, companies need a new approach to identifying problems that AI may solve. And creatively exploring those solutions is a valuable exercise if gone about in the right way.
The most advanced companies today understand the scale of AI’s potential impact. They aren’t acting like luddites (#1) and they aren’t just following the herd and with a simple, linear solution (#2). Instead, they are evaluating their business problems from new perspectives. They are using the inspiration of how others are solving problems with AI to find new problems. They understand that AI’s solutions allow them to address problems they couldn’t before.
Ignoring AI is not an option. Waiting has a huge opportunity cost. And dismissing AI as a solution looking for a problem is the path of failure. Exploring what AI opportunities you have—old problems that now have solutions, new inspiration from others’ experience and developing the skills and assets to leverage this powerful technology—is how to create the greatest business value through more revenue, lower costs and lower risk.