Jeffrey Moore
Over the past 50 years, Geoffrey Moore has made a name for himself as an original thinker and visionary. Moore has lived through cycles of technology-driven change, and his life’s work has focused on market trends surrounding disruptive innovation. This wasn’t the obvious path for Moore, who earned a BA in American Literature from Stanford University, a PhD in English Literature from the University of Washington, and taught at a university as an English professor. This was all before Moore found his niche in marketing consulting. Moore worked for Regis McKenna Inc, a technology marketing pioneer that made a name for itself by advising technology organizations such as the early Apple Computer.
It was Moore’s first book and it defined his career. Crossing the Gaphas become an industry classic, selling more than one million copies since its publication in 1991. With the book, Moore cemented his reputation as one of the leading visionaries and thinkers on the challenges startups face as they move from early adoption to mainstream customer success.
in Crossing the GapMoore said, Technology Adoption LifecycleStarting with innovators and progressing to early adopters, early majority, late majority, and laggards, Moore outlines the stark gulf between early adopters and early majority. Moore explains that early adopters are willing to make sacrifices for the benefit of being first, while the early majority will wait until they see that the technology actually delivers productivity gains. The challenge for innovators and marketers is to narrow this gap and ultimately accelerate adoption across all segments.
A 2023 Forbes article, “15 Years After the Financial Crisis: Data and AI Transformation Efforts Are Moving Slowly at Many Large Companies,” expanded on Moore’s thesis, explaining that “business transformation of any kind is never easy, especially for the legacy companies that are at the core of the Fortune 500.” A 2023 Economist article noted that only 52 of the Fortune 500 companies were founded after 1990, and that nearly 90% of the Fortune 500 is made up of legacy companies that are more than a generation old, with a significant percentage dating back more than a century. Like Moore, it has been my observation that legacy companies have a history of adopting new technologies at an incremental and measured pace over time.
I first got to know Moore through the Fortune 1000 Data and AI Executive Leadership Dinner and Roundtables he began hosting in the early 2000s in Boston, New York, and San Francisco, and continues to this day as intimate gatherings of Fortune 1000 Chief Data Officers and Chief AI Officers. “These executive roundtables provide an inspiring and intimate forum for C-suite executives to exchange perspectives,” Moore said at the time. With AI being heralded as the most transformative technology moment in a generation, I connected with Moore again to ask him, as an industry veteran who has been through much of the technology adoption lifecycle, about his current take on the AI moment and his outlook for the future of AI.
Moore began: “Disruptive innovations create what the Gartner Group calls hype cycles, which begin with a peak of inflated expectations, followed by a trough of disillusionment, followed by sustained adoption and value creation at a slower pace.” Moore continued: “In this context, AI, and generative AI in particular, is at the peak of inflated expectations. That said, given the ease of integration into existing workflows and the incredible amount of risk capital that has been put to accelerate the training of large-scale language models, we can expect a much faster adoption rate than normal — a pace more like the Apple iPhone than the World Wide Web.” And he added: “And for the first time, we see that the primary target for value creation is white-collar jobs that require creative intelligence, on a scale that is as unimaginable today as self-driving cars were a decade ago.”
Regarding the potential for AI to disrupt, Moore commented, “Today, AI can be directed at both disruptive and sustaining innovation challenges.” He continued, “Disruptive efforts address management challenges where the requirements for low latency, global scale, and massive complexity exceed the capabilities of human-led operations. Sustaining efforts address more routine workflows and replace robotic process automation (RPA) because they require little to no programming to deploy.” Moore cited disruptive opportunities in areas such as industrial plant management, cybersecurity, fraud detection, public safety, defense, supply chain management, social services, education, and healthcare, all of which “struggle today because of limited capabilities they can bring to the challenges they address.”
Moore spoke about the disruptive potential of AI in “white-collar jobs that require creative intelligence.” He explained that “professional services firms, including large consulting services organizations that scale with hourly fee-for-service operating models and are based on a finder-mind-grinder pyramid model, will be eroded by ‘cyborg’ consulting with AI-enhanced capabilities in much smaller teams.” He continued, “Higher education is at serious risk because the cost of the current model exceeds the value it is providing, forcing students into unaffordable debt.” He went on to point out that “healthcare is struggling to implement value-based care models, but doesn’t have the data or productivity tools to make it work.” He added, “AI will change that equation, but the industry will have to get past a protectionist resistance phase led by existing payers and providers to take advantage.”
Moore sees GenAI’s application as a “new user interface (UI)” as the most immediate game changer. “Most digital transformations to date have placed a training burden on the user community, limiting their adoption and usage,” he explains. “GenAI can remove that burden by making the UI an everyday, natural language conversation.” Moore adds, “It will still take some time to get used to talking to a computer, and it will require new peripherals so that conversations don’t interrupt others, but it will remove a major barrier and will undoubtedly result in faster downstream adoption.”
But not all is well. Much is written and said every day about the risks and potential dangers of AI running wild, especially issues such as misinformation and disinformation via social media. Moore understands that AI is a transformative technological tool like no other in history, and comments, “The greatest risk from AI in the near future comes not from the AI itself somehow getting out of control, but from empowering bad actors. This is the latest stage in a never-ending arms race, and we must find a way to adapt to hostile innovation.”
So where do we stand today with regards to AI, and what can we expect in the evolution of AI adoption going forward? How can we prepare for the future of AI? Moore concludes, “AI has already crossed the chasm in many use cases, including high-frequency trading, digital ad placement, and financial regulatory compliance.” He continues, “The next landing spot is organizations under insurmountable pressure to perform, such as air traffic control, public safety, primary education, and in-home elderly care.” Moore summarises, “In each case, your target market will shift from people who believe what you believe (the initial market) to people who need what you have (the frontline market).” He concludes with some hard-earned words of wisdom: “You don’t have to evangelize the technology, you just have to take their problems off the table.”
