AI has long been touted as the next big leap, but some argue it may instead close the current digital surge that began in the 1970s. Nicolas Colin, a strategy blogger, calls this the “late‑cycle now investment theory,” suggesting the surge in computing and networks is maturing rather than expanding. He cites Carlota Perez’s model of 50‑year tech cycles to support his claim today.

Colin points to three late‑cycle signals: the 2022 startup funding collapse, the rise of AI from OpenAI—backed by Microsoft—and the near‑saturation of digital transformation globally across industries. He argues that, like lean production refining mass manufacturing, AI optimises existing infrastructure instead of spawning a new wave. The result is deeper penetration into sectors that once resisted digital tools recently.

If Colin’s theory holds, investors will shift focus from chasing hype to backing companies that embed AI into established services, such as healthcare, education, and government. Market leaders will need to bundle AI with core products, as only 8% of users are willing to pay for it outright. The technology’s future hinges on practical, value‑driven deployments rather than rhetoric.