ChatGPT & GPT-4 for most leaders: It’s not ready for you (yet)

There’s an interesting divide in how people talk about GPT technology. Tech professionals get genuinely excited about ChatGPT and GPT models: it’s a moment of “isn’t this just the coolest thing ever?” Meanwhile, in the general population, maybe ten to twenty percent actually know what ChatGPT even is.

For leaders, the value of any invention comes from translating it into something that provides real value to the customer. Through that lens, what the technology actually is doesn’t matter. We’ve been through this cycle many times before, watching innovations move through different stages of maturity. At times like this, I like to reference Simon Wardley’s idea of value mapping for innovation.

Pioneers, Settlers, and Town Planners

When it comes to measuring how mature a technology solution is, and whether you can adopt it, you can divide its life cycle into Pioneers, Settlers, and Town Planners.

Pioneers

Pioneers are the people at the forefront of creating new solutions. They’re the ones most excited about GPT models right now, screaming “we just created Fire 2.0!” Their minds are full of possibility that most people can’t yet see. They’re creating custom-built technology, right on the frontier.

Pioneers show you wonder, but they also fail a lot, and that isn’t always great for providing value to the customer. Sometimes a technology never reaches its full potential. It stays an interesting gimmick, just beyond a working prototype, usually with bugs or other failings, but arguably still useful.

Settlers

Settlers are the people who take the pioneers’ early work and scale it into something workable for a larger audience. They build trust and understanding. In short, they make the future actually happen.

Settlers take what the pioneers built and turn it into something usable: an actual product or rental service, with most of the rough edges smoothed out. Not everyone has adopted the technology yet at this stage, so it still offers a business edge, but it’s no longer completely fringe either.

Town Planners

Town planners are the people who operationalize the idea. By this point, the technology has become commoditized. It’s no longer novel, it’s expected, part of any business’s standard operating procedure. It’s a highly trusted tool that makes things faster, better, smaller, more efficient, and more economical.

Once the town planners have the technology, it becomes foundational. The pioneers then build on top of it to create the next innovation. Think of the cart: it led to the horse-drawn cart, then the car, then self-driving cars.

Each group steals from the others. Town planners steal from settlers, who steal from pioneers, who build on the work of town planners.

An example of this process: Cloud computing

Cloud computing is a great example of the pioneer-to-town-planner journey. Just over a decade ago, it was still very much frontier tech, in the hands of the pioneers. It took a while to become mainstream, and even now some people struggle with it.

But with cloud technology, it’s become expected, in the hands of the town planners. Now pioneers are building on top of it with things like serverless and Kubernetes. Serverless was a huge leap forward in cloud computing. It redefined how things work through event-driven architecture, a genuinely new way of thinking about the previous technology. And because it’s the new frontier, people are out evangelizing it, and not getting far with it yet.

ChatGPT and GPT-4 are still frontier tech

From a pure technology perspective, the technology is incredibly advanced. From a perspective of impact on profit and loss, it’s still very early.

Technologists are still very much in the honeymoon phase with GPT-based technology. Everyone’s out there exploring it, trying to break it. People are doing things like showing GPT-4 a photo of what’s in their fridge and asking it to come up with recipes in 60 seconds.

That’s very cool, and very novel, and you can see where it’s going. But what is really going to get it onto the market, where our aunts and uncles and everyone else see the benefits of it? What will it take to see it in truly mainstream applications? Most likely, when that happens, people won’t even know it’s ChatGPT or GPT-4, since it’ll be woven into some other use case. They’ll just know they’re suddenly getting a really great experience.

There’s a pattern with emerging technologies: the companies that win focus on the customer first. They work backwards from customer needs, looking for opportunities where the technology actually fits. Do it the other way around, and it doesn’t work as well.

Right now, companies are largely waiting for GPT-based technology to mature, letting the marketplace soften its edges and make it easier to consume. The technology still feels a bit rough in terms of how the APIs work and what you can do with them. It still needs more time for a proper ecosystem to form around it.

For leaders, picking the sweet spot to adopt

For leaders, the question of when to adopt is very real. When it comes to ChatGPT and GPT-4 applications, you don’t want to get in so early that you end up pioneering the space yourself, unless you’re planning to become an AI company. If you do want to build the product and be an AI company, go right ahead. But that’s a gold rush right now, everyone’s going after it, and there’s going to be a lot of fallout.

You can already see products trying to incorporate ChatGPT so customers can start using it right now, Microsoft being a prime example, with varying levels of success. For some of these companies, it seems like the goal is just to slap AI inside the product so they can say they’re on the forefront.

On the other hand, you don’t want to be too late either. If the space becomes overfilled, having the technology at all won’t set you apart. The only way to judge that is to keep a close eye on the space.

Right now, the best thing leaders can do is study the industry: get educated on what’s happening, and keep tabs on what people are writing about it.

Before you start thinking about AI, check your other tech fundamentals first

A lot of people get caught up chasing bright, shiny things like ChatGPT. But every day, we see companies still struggling to get the basic fundamentals of cloud computing into their culture and operating principles, let alone something like serverless.

One reason for this is the inertia of legacy practices. In large enterprises, it can be very hard to throw out the old and adopt the new. Cloud practices are here and now. The reality is simple: if your organization doesn’t have the fundamentals of cloud computing down, you’ve got a long way to go before you should be experimenting with generative AI.

You should also make sure your organization has the agility and structure to handle adoption, along with the right skills on your teams. Most importantly, leaders need the situational awareness to connect emerging technologies like ChatGPT to real customer value.