We are living through a generational technology shift—one that comes along only once or twice in a lifetime, reshaping how humans interact with the world. Just as electricity, automobiles, computers, the internet, and mobile computing were transformative, AI is doing the same today. However, history shows us that in the early days of a new technology, people often misunderstand the power that it unlocks. This article will examine some of the historical technology shifts and the lessons we can learn from them.
Lessons from History
Practical applications of electricity began to take root in the 1880s and 90s, with the first electrical power station opening in Manhattan by Edison. The uses were initially targeted at consumers, with rich New Yorkers able to electrify their homes and replace their gas lights with electric ones. Industry, on the other hand, was slow to adapt, despite the evident advantages. Most industries simply replaced steam-powered equipment with electric ones, or added electric lights, without considering how their industry could operate differently.
The engineering breakthrough came when Henry Ford reimagined the factory in the 1910s. He utilized electric motors' precise speed control and distributed power to create the moving assembly line in 1913—a feat impossible with centralized steam engines that required complex systems of belts and pulleys. These improvements cut the Model T build time from 12 hours to about 93 minutes—a systemic redesign that enabled scale, lowered costs, and transformed labor and manufacturing fundamentally.
A similar lesson comes from the introduction of the television. In the early days of television, content was heavily borrowed from radio—simply filmed broadcasts of radio shows without inventing for the new medium. The real shift came when creators embraced television's potential: drama anthologies, magazine-format shows like Today and The Tonight Show, recording and editing footage from multiple cameras, and new storytelling formats were designed for television. By the 1950s, TV overtook radio: between 1950 and 1960, U.S. household ownership jumped from about 9 percent to over 60 percent, nearing 90 percent in the early 1960s.
The lesson: Early adopters who treat a new medium like the old one often miss its full value. The true winners reimagine processes, experiences—and even entire business models—when they adopt these new technologies.
Parallels with Today’s AI Adoption
It is evident from the above examples that there are parallels with the adoption of AI into our products and businesses. Pressure to add AI or to be the AI for x industry results in many uninspired implementations. Many organizations today bolt on an AI assistant—like lighting a few bulbs in a steam-powered factory—but miss the opportunity to reimagine workflows end-to-end. The real transformation occurs when considering how AI can transform the user experience.
The difference between the past technological shifts and the AI one we’re experiencing today is the incredible velocity of the change.
- It took about 13 years for Ford to sell 1 million cars.
- It took Google 1 year to reach 1 million searches per day.
- Apple’s iPhone launched in 2007, heralding the smartphone revolution, and sold 1 million units in just 74 days.
- ChatGPT, on the other hand, reached 1 billion searches per day in under a year—a metric that Google took over 10 years to achieve.
Within just two months of its November 2022 launch, ChatGPT surpassed 100 million users—the fastest adoption rate ever recorded for a consumer software product. This rate of adoption suggests that companies that don't learn from history and adapt to the AI era face an existential threat, not just a competitive disadvantage.
GrowthBook’s Journey with AI
At GrowthBook, our initial step was adding the lightbulb: we launched an AI chatbot to help users navigate our documentation (a helpful concierge, if you will).
Simultaneously, we conducted several brainstorming sessions to reevaluate our product and explore the potential impact of AI on our business. We ran the 11-star brainstorming sessions and planned our roadmap to reimagine what AI will mean in the A/B testing and product analytics space. We built Weblens.ai as a demonstrator of some of the features that AI can unlock for AB testing—and we have many more features coming very soon.
Conclusion
From electrification to television to AI, each technological shift has rewarded those who reimagined systems entirely. They didn’t just adopt new tools—they rewrote workflows, content, and the way they delivered value.
Here are the lessons:
- Treat AI as a new paradigm—not just as an add-on. Like Ford reengineered production or TV creators abandoned radio formats, design products from an AI-native perspective.
- Focus on user journeys and tasks that AI can redefine—insights, decisions, personalization—rather than isolated features shoe‑horned onto existing interfaces.
- If you don’t adapt now, someone else will. AI has experienced an explosive rate of growth, resulting in significant productivity gains and a reduction in the time it takes to bring products to market.
