Don't want A.I. to take your job? Learn to use it as a tool. | Paul Daugherty

As the Chief Technology Officer for global management consulting firm Accenture, Paul Daugherty knows that there's a lot of people out there, in many industries, who are afraid of losing their jobs to artificial intelligence. Here, he offers some sage advice in dealing with AI: lean into the change. Read more at BigThink.com: https://ift.tt/2sjZDo3 Follow Big Think here: YouTube: http://goo.gl/CPTsV5 Facebook: https://ift.tt/1qJMX5g Twitter: https://twitter.com/bigthink As you think about your talent and your workforce for the age of AI and where we’re moving to, there’s a few things that are very important to think about. I think about two broad categories of skills that you need to prepare for. One is what I’d call the Talent or the skills – the people that “do” AI. Who’s going to develop the AI? Those are the machine learning experts, the data scientists, the people with the STEM skills and coding skills that are going to build the technology of the future. And that is an important area that every organization needs to be preparing for in developing and building those types of skills. And that’s one important thing. The bigger set of skills that I think every organization needs to think about are the people who use AI. Not the ones who do and build it, but the people who use AI. And that’s going to be basically everybody in the workforce, or almost everybody in the workforce, in your workforces or organization. And I think that’s an area where organizations haven’t spent enough time. Everybody knows they have to develop and hire the AI experts and the coding experts; I think how the rest of your organization is going to adapt and use AI is the big question that we’re really trying to address in Human + Machine. There’s a few things that I’d say that are really important there. One is you need to think about the learning platforms that you’re developing for your organization. One thing that we found in the survey in the research work we did is two-thirds of organizations, roughly, believe that their workforce isn’t ready for AI, broadly for using AI – a big number. Only three percent of organizations plan to increase their training spending to account for that, which isn’t appropriate. That means that generally, people think it’s somebody else’s problem to prepare the workforce. And we believe that that’s not the right answer. At Accenture, we’re investing about a billion dollars a year in training and retraining our workforce, in developing talent platforms that continually retrain people. And we think that that’s the approach you need to take because we’re in an age of continuous innovation. The roles of your workforce are going to continue to change, and you can’t flush and replace the workforce, and that’s not the right way to view it. How do you look at your employees as an investable resource, where you’re investing in the talent and developing the right learning platforms that they can learn how to use AI in the initial applications you’re rolling out now, and continue to learn so that their skills are relevant and they’re productive contributors to your organization as you continue to progress? Another area that we really overlooked and where there’s huge potential is using AI itself to help prepare the workforce. And I think there’s huge opportunities for innovation here. We’re starting to see some real interesting possibilities coming. One experiment we’ve done as an organization, and this is still in the research and development stage, we’ve looked at all of our employees in our Accenture organization (and we have over 430,000 people, so it’s a large workforce). We’ve developed a machine learning model using artificial intelligence that can take the resumes and experience of any one of our employees – and this is something our employees can use to understand how their job will be impacted by AI. So it might say that as you feed in all of your information, it’ll compare it to external job postings and trends in the marketplace. And it might say “Well, your skills are at risk in about one to three years.” And it doesn’t stop there, but it says “and based on what you know here’s the adjacent types of jobs that you should start looking to train yourself for.”