The Next Great Technology Cycle

Every technological revolution feels unique while we are living through it. But look closely at the past seventy-five years and a remarkable pattern begins to emerge.
Television transformed the post-war household. Semiconductors made modern computing possible. Personal computers created the software industry. The internet connected the world. Smartphones put that world into our pockets. Cloud computing built the infrastructure beneath it all.
Now artificial intelligence may be opening the next great technology cycle.
In The Next Great Technology Cycle, Conner Davis looks beyond the daily headlines and asks a bigger question: Is today's AI boom already approaching its limits—or could we still be in the early stages of a transformation that extends well into the next decade?
Drawing lessons from previous waves of technological change, the book follows a recurring progression from invention to infrastructure, infrastructure to adoption, adoption to new economic ecosystems, and eventually to excess, correction and renewal.
At the centre of the book is the Eight-Year Hypothesis: the possibility that the technology cycle unleashed by generative AI may still have years to develop. Rather than presenting this as a prediction, Davis tests the argument from both sides—examining AI investment, semiconductors, data centres, electricity demand, corporate adoption and productivity alongside the risks of excessive valuations, overinvestment, competition, regulation, recession and technological disappointment.
The story then moves beyond generative AI to what could become the next major frontier: physical intelligence.
Robotics. Autonomous systems. Smart factories. AI-enabled vehicles. Intelligent devices. Data-centre infrastructure. Energy and power networks. New forms of consumer computing.
As intelligence moves from screens into machines and the physical world, the economic consequences could spread far beyond today's leading AI companies.
But technological transformation does not guarantee investment success.
One of the book's central lessons is deliberately simple:
A great technology does not automatically create a great company—and a great company does not automatically make a great investment.
To help readers navigate that uncertainty, the book develops three possible futures through 2035 and introduces the Electronic Renaissance Scorecard, a practical Green-Amber-Red framework for monitoring whether the long technology-cycle thesis is strengthening, weakening or changing direction.
The Next Great Technology Cycle is not a promise of an eight-year bull market, nor an attempt to predict exactly what comes next.
It is a framework for understanding how technological revolutions unfold, where capital and opportunity may migrate as they develop, what could derail them—and how seventy-five years of history can help us recognise the shape of the future before it becomes obvious.
For investors, entrepreneurs and curious readers trying to make sense of AI and the road to 2035, this book offers something more useful than a prediction:
a way to think about what comes next.