Adaptability is the most sought-after trait in employees today. Our Accenture survey of CXOs and the 2019 World Development Report both found this to be true. Indeed, as companies increasingly adopt artificial intelligence technologies, the impact on work will require people to adapt their skills to collaborate with intelligent machines.
When it comes to AI, business leaders may be skeptical that their people can adapt. This is what makes them go out to hire talent, instead of investing in their own. Sometimes that’s a valid response, as when certain skills are not found inside or there is an urgent need in the business (see graphic). But according to our survey, CXOs believe only 26 percent of their workers are prepared to work with AI—which explains why companies are not investing enough in skill-development programs. Why invest if it won’t pay off?
The antidote to such thinking is a “growth mindset”: the belief that effort or training can change one’s qualities and traits. This is usually discussed in the context of why workers need to have a mindset for lifelong learning. But do leaders have the growth mindset to reimagine business processes to support their workforce? More than 40 percent of executives we surveyed said hard-to-change processes are hindering their efforts to train employees in new skills.
We interviewed Vivienne Ming, neuroscientist and cofounder of Socos, whose scientific study challenges the notion that people either have the motivation and capability—or don’t. The reality is a grey zone in between—leaders can do lots to help people develop their own sense of purpose, and likewise, capability. Of course, employees must do their part to meet in the middle.
Three critical elements of this process are:
Essentials for finding common ground for a world of human-machine partnerships.
I recall how I felt when Accenture Research launched a data science team offering AI-based services. I might have resisted the change—usually I am a tech-laggard personality (upgrading my iPhone 6s to Xs is a 2020 plan); moreover, what could a bunch of data scientists offer a seasoned researcher like me?
It’s impressive how our global leadership hit on all three elements—including envisioning the strategy with senior leads; communicating to all and highlighting the personal benefits, training, certifications, the platform to exchange ideas, and the resources to experiment regardless of potential failure. We hired several specialists who then trained all 250+ researchers to rotate to the “new”—thus growing our team without displacing anyone. Today, I’m a huge fan of our AI service and constantly scout for opportunities to apply it more. (Rest assured, AI did not write this blog—we’re not there yet!)
So, can people adapt their skills to thrive with AI? If you believe they can, they can (with the right support). Take a look at our report “Missing Middle Skills for Human-AI collaboration” to plan your journey to future skills and learning in the age of AI.