The Complex Journey of Technology Adoption

This is a very bad attempt at sketching a concept that I had in my mind for the past few days. I wanted to combine the Gartner Hype Cycle with the Technology Adoption Lifecycle from Geoffrey's Moore Crossing the Chasm and the Strauss-Howe generational theory. My goal is to establish a framework that explains why I don't believe GenAI is a disruptive innovation in the localization industry, as I discussed in my previous article. I am trying to justify why I don't view this as the impending demise of the industry as a whole.?

While I acknowledge the possibility of being mistaken, I've been fascinated to observe the adoption cycles of new technologies like LLMs and GenAI. In my experience, the uptake of groundbreaking innovations is far more nuanced than people predict. Understanding the intersection of frameworks like the Hype Cycle and the Technology Adoption Lifecycle has helped me grasp the psychological and practical complexity behind embracing new tech.?

I often think back to when I first created the Localization Maturity Model with Don DePalma. We were trying to capture how localization teams engage with new technologies as they gain experience and sophistication over time.?

It's intriguing to compare the hype versus reality when breakthroughs like ChatGPT emerge. As an innovator myself, I'm always absorbed by the potential of new tech. However, observing its adoption across society has taught me that widespread integration can take much longer than other experts predict. Just because a technology is accessible and simple to use, immediate adoption is not guaranteed. In other words, just because the technology is easy, cheap, and accessible, it doesn't mean that everybody will use it.

Generational influences add more complexity to the mix. Strauss and Howe's theory of cyclical generational cohorts implies that attitudes toward emerging tech will differ across age groups. While some segments may dive in headfirst, others may take years to embrace new innovations. This also has to do with the historical framework of the time and what generation is in the leadership positions.

The adoption of technologies is influenced by industry-specific needs. For instance, despite advancements in software and connectivity, healthcare communications in the United States still largely depend on fax machines, a technology ingrained in the regulatory and legal frameworks when it was cutting-edge. This example highlights how legal and regulatory environments can shape technology adoption and how hard it is to change regulated environments even if the technology exists.

These new technologies are amazing at processing audio and video content, but we shouldn’t forget about print. There's still a vast amount of content in print form, presenting a unique challenge and opportunity for technologies like GenAI. This underscores the multi-layered complexity in the adoption of new technologies – it's not just about availability and simplicity but also about navigating a tapestry of generational, industry-specific, and regulatory factors.

So, while GenAI may revolutionize certain areas overnight, true integration into our lives and work will likely be more evolutionary. Understanding this complexity is crucial for innovators like myself who want to drive widespread adoption. We must account for the diverse mindsets, structural barriers, and generational perspectives that shape how emerging technologies become part of our world.

In my opinion, even though you are able to create your own GPT now with very little effort, you will probably wait until it is embedded in the technologies that you use today, be it a TMS or an MT system. Ultimately - because of your laziness, fear, or the competence of the salespeople of your existing providers - these technologies will become a feature in your environment of choice. Until something new shows up, and the cycle starts again.

P.S. This article I found while looking for images makes a similar point but has much better graphs (and a blatant typo when referring to Early Adopters).