A winner-takes-all mentality marked the early days of ChatGPT. The major AI labs were all openly chasing Artificial General Intelligence. An AGI breakthrough would supposedly kick off an intelligence explosion. This in turn would trigger a chain reaction of recursive self-improvement; whoever got there first would be forever uncatchable. Generative AI research was positioned as a national security imperative. It was the US vs China. Whichever country won the AI race would permanently dominate the globe. The finish line wasn’t decades out; it was behind the next research breakthrough. AI labs wanted to go all-in and sprint; the environment, safety, copyright, and humanity be damned.
AI’s influence on the world of work reflected a similar philosophy. The saying, “AI won’t take your job. Your coworker who uses AI will”, set the tone for the battle each of us would face to keep a job in this new world. It wasn’t nation-states battling for world domination, but the consequences and timeline were as clear and present. Talk of Universal Basic Income and Dario Amodei’s “Machines of Loving Grace” painted a dystopian picture of a brave new world of employment (or lack thereof) that was right around the corner.
Knowledge workers were already struggling from the many challenges of working through the COVID-19 pandemic. GenAI’s emergence announced that there was no rest for the weary. Skill up or die, learn to embrace AI. Many people heeded this call to action and dove headfirst into AI skilling and AI-focused roles. Take a look around your LinkedIn connections, and you will likely see many new titles and certifications related to AI. It was a sprint, a veritable stampede, to make it to the right side of the AI intelligence explosion before everyone else got left behind.
Generative AI’s story hasn’t quite played out how the marketing teams and lab leaders predicted. People are still here and largely the beings doing the work that needs to be done. At many companies, there are fewer of us than before. AGI and the promised AI Agent workers haven’t yet shown up to help most of us. The intelligence explosion feels much further away than it did a year or two ago. Many organizations are struggling to realize value from AI products, and there are significant hurdles for AI companies to generate profits, let alone cover massive capital expenditure on rapidly depreciating assets.
The race to stay employable suddenly feels much slower, and the finish line is now out of sight in the distance. If you have ever come out of the gate running too quickly in an actual foot race, you know the pain that awaits you. As you gas out, other runners will pass you by. It can be demoralizing as well as physically challenging to keep up.
The early AI adopters who sprinted down the beach to jump into the clear, blue ocean now find themselves in a sea of red. The sharks have arrived. AI has become the new shiny object, the One Ring to rule them all. Politics and turf battles are the new norm. Early skills like prompt engineering are now largely irrelevant. Organizations will have to decide how many people should be focused on AI and how many of the remaining workforce will deliver the day-to-day work.
AI skilling appeared to be the path to job security. Now it is not so clear what those skills are, who will need them, and when. It appears more uncertainty is in store for knowledge workers. We will need to continue to learn, to adapt, and to question. Ultimately, we will have to run our own race to keep pace with the demands of the labor market.