Paul Daugherty: 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.”
And again this is at the research and development stage, so I wouldn’t say it’s a product out there yet but it shows the kind of innovation and creativity and way that we can use technology itself to help prepare workforces for the changes that are coming down the road.
There’s a lot of voices out there that are very well-regarded voices – Elon Musk, the late Stephen Hawking, who talked very eloquently about the perils and dangers that we face with AI.
I do think we need to consider those and we need to think about the longer term implications of AI, like we do of any technology.
Every technology that’s ever existed from, the first stone wedge that the cavemen carved or the first fire that was lit, was used for good, and it could be used for bad as well.
AI is no different, and the thing that I think concerns people sometimes is the pace of AI and the ability of AI to make decisions that are not in the interest of us as human beings. The reality is that the risk of that happening is far away. We should be thinking about it. There are organizations that are set up to think about those implications, and we support and are involved in some of those organizations. But that’s for the distant future, and not something that we need to think about in our generation right now in terms of real, serious consequences.
The opportunity for us now is to think about how do we apply this to live more effectively on the planet, to better use our resources and to operate businesses and educational institutions and our governments more effectively?
There’s massive opportunity for this, so rather than be consumed and stuck by what might happen with the technology in the future we need to think about that and prepare for it, but let’s apply the technology in a responsible way, which is what we talk about in Human + Machine: to solve these problems today.
Source: Big Think