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By Rob Enderle for Techspective
AI is reaching the end of its hype cycle. Reality stepped in when people realized it wasn’t as useful yet as they thought it would be, and the vast majority of AI deployments currently fail to meet expectations. This is due to a combination of low deployment skills and the lack of adequate technical knowledge as people race to deploy without adequate foundations. However, AI-focused companies like Silo have reached adequate competence and are being purchased by larger entities (in this case, AMD), suggesting that AI failures should drop significantly going forward.
Also we are seeing a significant increase in layoffs that appear to be at least somewhat connected to this AI ramp, which implies that, for many, the time to reskill to hold jobs has already passed. But we are only at the beginning of this trend, so the rest of us may still have time.
Earlier this week, I did a podcast on this topic for the World Talent Economy Forum out of Asia and I thought it would be an interesting topic to cover this week.
In prior industrial revolutions, the jobs that were lost were more than made up for by new jobs created by technology that was focused on mechanizing or automating existing processes. AI is different. AI is specifically designed to enhance and replace people, and it is being partially targeted at jobs in which there is a lack of people, like fast food, but also potentially includes people, like coders, who work on AI projects.
Thus, it is likely that many of the new jobs that will be created will also be done by AIs because we won’t have enough people to do them at first. And while people needed to build the machines that founded past industrial revolutions, we are training AIs to build, modify and enhance themselves, again suggesting the job uplift from AI will be far less than the job losses.
This is problematic for a lot of things, not the least of which is that AIs don’t consume. If we go too far in eliminating personal income, the economy will collapse due to a lack of buyers (granted, this is decades into our future, though AI is moving far faster than prior industrial revolutions).
This makes it very problematic to figure out how you should retrain, given retraining typically takes years, and there is a good chance that the job you are training for will not be there in sufficient numbers when you complete your training or initial college education.
This suggests a very different approach not only to retraining but to how you pick and stay with a particular training path to ensure that you have a career and don’t become obsolete.
Read the rest of the article to find out about Enderle's suggested path to preserve your future: How to Prepare for or Avoid Being Obsolesced by AI
About the Author:
Rob Enderle is the president and principal analyst at the Enderle Group, where he provides regional and global companies with guidance on how to create a credible dialogue with the market, target customer needs, create new business opportunities, anticipate technology changes, select vendors and products, and practice zero-dollar marketing. You can reach the author via email.
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