Does this mean that machine learning will take away great jobs and displace much of the workforce? Absolutely not. Machine learning, artificial intelligence, and other technologies will make people more efficient by empowering computers to do the things that are more routine and more error-prone due to distraction, repetition and boredom. True, there are jobs that will eventually be replaced by machine learning, but these are such undesirable jobs that they typically average a turnover rate of around 30-35 percent.
As CEO you will likely hear arguments from HR about how they must radically change the way they train people to prepare them for the evolution to the machine learning-powered business world. Like training people in all jobs for the next career step, one needs to look at an employee’s current role and determine the natural evolution of their skill set. Ideally, if you have a division of transaction processors, you retrain them for more stimulating jobs that require they analyze what the transactions mean based on their experience processing hundreds of transactions per day. These people know the transactions better than anyone else in the company, they just need to be trained and given the “go ahead” to use their brain to think vs. do.
Having lived through this, I know this can be done without firing people, but I also know that the majority of the people in these roles are not going to go back to school to pursue PhDs and complete the requisite classwork and years of lab experience to become ML scientists. In fact, some won’t even be easily transitioned into more sophisticated versions of their former jobs. In those instances, there is a huge opportunity and demand for people to clean up the data! After all, ML solutions are only as good as the data that powers them.
When I worked at a Fortune 500 company, I was able to redirect 21,000 roles to analyze transactions, do data clean-up (admittedly this is grunt work, but transaction processing is also grinding work), or to deal with the new client work that was coming in the door. The reality is that it can be done, but it’s hard. Many companies will be tempted to take the easy way out and let people go if they don’t plan ahead and don’t fully understand the opportunity.
Machine learning can have a positive impact on your top line, your bottom line, and if you do it right, your people. Remember that although part of the cost reduction piece is reducing full time employees, it is also about making better use of your people. To do this, my advice is to start planning for the inevitable change in roles and define how skill requirements will shift. Commit to spending the same amount of time figuring out what you will do with your people as you do on all other components of your machine learning strategy.
Don’t ever forget that your people are the business. If you do this right, you will make business impact (increase revenues and decrease costs) by transitioning your people from uninspiring, high-turnover jobs to more impactful data-centered careers, which will be core to your future business success. As you have heard me say before, if you lose the people, you will lose the business. So plan now around these machine learning concepts as it will make you, your shareholders, and your people much happier.
Read more: Machine Learning Misconceptions CEOs Should Know