There's a disconnect between the level of AI training that leadership teams believe they're giving their employees and the level of training that managers and employees think they're getting, research shows.
Nearly three-quarters (73%) of C-suite executives believe their company fully embraces generative AI, including training for the technology, according to a 2023 Upwork survey. That rate dwindles the closer you get to individual team members, with just 53% of senior managers agreeing. A recent report from learning experience platform Skillsoft corroborates this: only 37% of employees say training is included in the technology adoption process.
"The disconnect is simply a matter of altitude, of where you are within the organization and what you're essentially getting paid to worry about," said Dr. Kelly Monahan, managing director of Upwork's Research Institute.
With executives reporting a lack of AI skills and expertise as the top barrier to AI deployment, according to IBM research, it seems that adequate training would be the answer. But it's not as simple as filling a void and wiping your hands.
"Executives sometimes have a broad-brush approach to AI training," said Apratim Purakayastha, chief technology officer at Skillsoft. "Checking the box does not really work."
Plus, retirees are outpacing new workers, Pew Research shows. "That is profound for leaders who have always planned to just rely on the next generation of digital natives in order to fill that skills gap," said Monahan. It's imperative, she notes, for leaders to become the generative AI supply they're looking for through upskilling and reskilling.
To Monahan, the onus for this is split, beginning with individual responsibility. "There's more democracy in learning today than ever before," she added, noting many workers are burnt out from so much change, but the call to action remains. Meanwhile, it's up to organizations to reprioritize efficiency so it does not come at the expense of learning and experimentation.
So how do leaders and employees meet halfway on the runway of AI training?
What generative AI workplace leaders do
Upwork dove into what companies that are actually closing the gap are doing. Work innovators, as they call them, were 2.2 times more likely to incorporate generative AI within their daily operations. Plus, they were 1.9 times more likely to have a formal generative AI skills program in place for their workforce, as well as 3.8 times more likely to have a well-defined generative AI strategy.
Noting the simultaneous need for strategy, training, and operationalized workflows, Monahan said, "When those three things happen, that disconnect begins to go away and there's much more harmony in the way all levels see generative AI."
Skillsoft's Purakayastha finds that a programmatic approach to generative AI helps, but only when it runs parallel with a grassroots creation of community around the technology.
On the programmatic side, he said, "It's a combination of making resources available, as well as pragmatically designing programs to seriously upskill and reskill in a measurable format."
Most likely, employees are already learning on their own, Purakayastha notes. That's where benchmark assessments — in which you benchmark your population against a skill set — come in handy. And a portion of them may be further along than you thought. "Based on benchmark results, you can design targeted upskilling programs," he said, adding this can even take place at the onboarding level by instating AI boot camps in early employment.
"Meet people where they are," Purakayastha said. "Design an upskilling program, reskilling program, and then people feel like they're being paid attention to."
At the same time, Purakayastha says there needs to be a pull from the employees, which organizations can foster by creating a community around AI learning. Creating forums where people share what does and doesn't work, launching a "prompt-athon" (similar to a hackathon) and even developing a leaderboard for best prompts are just some of the ways to drum up excitement, he notes. "Creating a programmatic push as well as bottoms-up excitement creates what I call a virtuous flywheel of learning," Purakayastha said.
Job redesigns and economic productivity
A majority (89%) of learning and development professionals agree that proactively building employee skills helps navigate the evolving future of work, according to LinkedIn's 2024 Workplace Learning Report.
This cohesion points to another issue: Finding agreement in what it means to sufficiently train in AI is not an isolated challenge. "This is as big as internet or the personal computer itself. How do we keep everybody fresh? Because things are changing very fast," said Purakayastha.
In 1987, American economist Robert Solow said, "You can see the computer age everywhere but in the productivity statistics." This became known as Solow's paradox, and it's applicable to more than just the computer itself. Generative AI, Monahan notes, can usher in a new era of productivity — if we let it. She said organizational and job redesigns must take place in order to actualize the renewed promise of productivity gains.
For Monahan, that redesign must centralize learning. "Learning has to be at the core of how we think about work, and somehow that's gone away because of our over-emphasis on efficiency and productivity," she said.
"The future beckons with a promise of innovation driven by necessity," stated consulting firm OliverWyman's AI report, released at the World Economic Forum's 2024 meeting in Davos, Switzerland.
As organizational players of all levels — from individual employees to C-suite executives — converge on what it means to be AI-ready, this necessity adds an urgency that we cannot ignore. AI is not new, but its recent renaissance could be short-lived if all players aren't in harmony about what it takes to make it a true part of our future of work.
At a simpler level, employees will look elsewhere if they're not getting what they want from their employer — and that will put a company behind in more ways than one.
