As the leader of one of the world’s first smartphone development projects, and having consulted for six years with Harvard Prof. Clayton Christensen as he translated his theory of disruptive innovation into recommendations for firms, I’ve seen a few industry disruptions. ChatGPT – and the generative, transformer-based neural network AI capability that underlies it – is a major disruptive technology in the making. With the smartphone being perhaps the most recent disruption of similar scale, let’s consider three lessons from the smartphone’s emergence and the business implications for ChatGPT and generative AI overall.
1. Sustaining Innovations Come First
The first smartphones were designed to address use cases that sustained existing businesses, who could readily see the value and adopt the technology. We integrated e-mail and calendars, linked to online news services, and made money by selling the phones to mobile networks. The paths to market penetration were well-established, and business partners didn’t need much convincing or novel technology to take advantage of the new medium. Because we knew that the development cycle for follow-on devices would be short, we figured we could iterate business models later – sustaining innovation was the best way to get going.
Shutterstock AI-generated image for the prompt "Early smartphone progression"
Over time, more companies started incorporating the smartphone into their efforts, e.g. WAP-based banking portals before apps even existed, or marketing based on pictures transmitted alongside text messages. Core businesses didn’t change, but the smartphone offered a different way of accessing their services. Incumbent firms dominated in these sustaining scenarios, partly because the offerings were tightly linked to web-based assets. Entrants could thrive by servicing these existing firms, e.g. by providing technology to ad agencies so that they could mobile-enable their campaigns.
Takeaway: With ChatGPT, we can imagine that sustaining use cases will be rapidly embraced – from customer service to fact-finding to search itself. These will create important innovations in Customer Experience, for example.
2. Disruption Ensues
I recall meeting the CEO of Psion PLC, where I worked on the smartphone, when I was just a few years out of business school and mightily intimidated. He commanded me, “Don’t build a duck.” He meant my team should make something that excelled on some dimensions rather than doing many things sort-of-okay. With hindsight, we delivered a duck. All early smartphones were, until the Blackberry sorted that out by focusing primarily on messaging. Because we produced a duck, it wasn’t really good enough to disrupt even fairly undemanding customers of other industries – yet.
Within a few years, basic cameras started appearing in phones. They couldn’t rival a standalone digital camera or film. However, they were immediately available for use in-the-moment, and they caught on instantly. Mobile networks became fast enough to support video downloads, and web-based video was disrupted rapidly. The list of disrupted industries became ever-longer, and it keeps growing to this day. In keeping with the pattern of disruptive innovation, the firms that won out were rarely those that dominated on the web, although there were highly notable exceptions of companies that pursued distinctive, mobile-appropriate business models aggressively (see: Google and its embrace of Android, among many other smart moves).
Takeaway: Because ChatGPT and its competitors still have many imperfections, they may not disrupt other industries right away. But, as Clay Christensen laid out in extensive research, what starts out bad often gets better. Generative AI like ChatGPT doesn’t need to equal the performance of more traditional forms of performing key jobs to be done; it just has to satisfy some undemanding users first.
3. New Markets Then Blossom
With the smartphone, it took a while for new industries to take root. I led one of the first mobile marketing firms, then one of the first mobile commerce companies – plenty of potential customers were interested in the technology, but they hesitated to adopt it until others had proven out the reliability and usefulness of these innovations. This is normal. New markets often require several ingredients to reach their full potential, and initial users are wary. They may do some tentative experiments, but the real money takes a while to materialize.
However, early leaders can create major advantages. Uber, Match Group (including subsidiaries like Tinder), and many others built a large gap against competitors through being among the first to pioneer their categories using smartphones. Sometimes these built upon existing web presences, but those companies quickly pivoted to be mobile-first in their orientation (e.g. Match Group). Usually, the creators of new markets were entrants.
Takeaway: In generative AI, we’ve certainly seen new markets start to take root, in fields as diverse as performing data analytics and creating unique images. ChatGPT is likely to enable new types of businesses as well. Counseling sessions with a bot? Business introductions through a bot-moderated network? The possibilities are endless. Ultimately, fortunes will be made as these new markets form, and early movers will create significant competitive barriers to entry.
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In his book The Innovator’s Solution, Clay used business history to lay out the dynamics behind sustaining, disruptive, and new market innovations. We see these patterns recur in industry-after-industry, and particularly in cases of major disruption. Generative AI like ChatGPT should be no exception. Money can be made in each setting, but the timeframes for profit and components of competitive advantage vary among them.
It’s natural to view disruptive technologies initially as a threat. And, certainly, ChatGPT threatens many. But riches flow to those who frame this change as an opportunity. With generative AI, the opportunities seem to abound.
