Crossing the Chasm is a classic book by Geoffrey Moore on software strategy. It describes how new technologies are established and how they scale to mass market adoption and eventually to obsolescence. The model is a useful guide to understand the path that AI will follow as AI itself, the market for AI products, evolves over time.
The chasm model
The premise of the chasm model is that there are multiple stages of market adoption and different buyers, with different purchasing motives depending on the stage. The big idea, hence the name, is that there is a chasm between early adopters and early majority. Crossing this chasm is the most critical step to successfully scale your technology.
To see successful adoption of your products, you must understand who your customer is, what they want from your product and where the technology/product is in the life cycle curve and build your product in that context.
Buyer segment: Early adopters
According to Moore, early adopters are visionaries. Early adopters see beyond what the technology is “today” — in many cases it is not yet fully mature — and ahead to what it can become. They see the future and believe investing in this technology will give them a competitive advantage — and are therefore willing to make an outsize bet relative to their peers.
If you were to try to sell your technology to this early adopter (buyer), you would want to convince them of the possibilities of the future. Through your interactions with them, you would hear them making comments about what the future looks like with your technology. They may make statements like, “This will get me ahead of my competitors” or “I see the future with this technology, and it looks like…”. This is the visionary buyer.
Buyer segment: Early majority
On the other side of the chasm is the early majority. The early majority is pragmatic, they want to buy proven technology. Unlike the visionary, early adopter, the early majority tends to be more risk averse. This group will buy when there are demonstrable results, preferably from referenceable peers in their own market.
If you were to try to sell your technology to this early majority (buyer), you would need to convince them of the benefits of implementing the technology, backed with case studies and results from other reference companies in their peer group. Throughout your interactions with them, they would say things like, “Who else is using this?” “What are the benefits?” “What is the ROI?”
What is the chasm, and how to cross it
The chasm is this gap between the visionary, early adopter buyer, who is investing ahead of the technology’s real maturity, and the pragmatic buyer who will not adopt the technology until it has shown (proven) results. The key challenge is that, while these two groups are fundamentally different, you must reach them both — and you must successfully cross the chasm to do it. So, how would one accomplish this?
The way to bridge the gap is to create a “beachhead.” This is accomplished by targeting a well-defined segment of the early majority. This is a group of buyers united by a common problem for which there is no known solution. Within that segment, you must target the reference leader for your targeted segment — but, a visionary, early adopter.
You must “sell to them” and then demonstrate success with this leader. With success in hand, this early adopter will then become a reference, lighthouse customer, which is the key to selling into the pragmatic, early majority. Then, having obtained real results with both the early adopter and some of the early majority, you then can add more early adopter customers, one after another — per Moore, like the analogy of knocking over adjacent bowling pins.
Scaling in the early majority to mainstream adoption
Next comes scale. Having established a niche segment of customers in the early majority, it is time to expand. This is “the tornado,” a time when you’ve finished building the whole product and now everybody wants it. Your business must scale horizontally and exponentially to keep up with crushing demand. This is a period of rapid growth. During this period every effort within the organization should be devoted to shipping the product as efficiently as possible.
Eventually, the market is established. The technology is widely adopted. At this point, the opportunities for growth are limited in scale but high in margin. You are the leader and you will enjoy the lionshare of the market — i.e. revenue and profits.
Case study: AI for Developers
As an example of this in practice, AI has “crossed the chasm” with developers. Ten years ago, there were no AI developer tools available for “the masses.” Historically, AI was unavailable to developers because the techniques were highly sophisticated — typically the domain of advanced/PhD computer scientists. That said, even if you knew how to use the technology, the general developer market could not use it both because they lacked easy access to the data and to the computing resources needed to train the models.
In the last few years, the largest names in the industry have started to adopt and promote AI technology (Microsoft, Google, Meta, IBM). Their aim was to utilize AI in their own products, but some also build developer tools (APIs, etc.) for their customers. Over time, the industry has seen these technological giants release a steady stream of AI accomplishments — both technology feats as well as adoption by their own marquee customers.
Fast forward to today, both because of advances in cloud computing and the explosion of data, these same organizations have now provided AI tools to developers — no PhD required. We now have AI developer tools “for the masses” and there are countless examples of organizations that have implemented AI in their products. As a case in point, today AWS boasts “over 100,000 customers are using AI in their products.” AWS has a library of 500 case studies, segmentable by customer size, industry, use case and more. Talk about a lighthouse — and the list is growing daily.
Conclusion
The chasm model describes how technology evolves — and guides how technology companies can match their strategy based on that evolution. The model is a useful guide to understand the path that AI will follow as AI itself, the market for AI products, evolves over time.