Top executives claim to be training workers on AI, but managers and employees have differing opinions.

• According to an Upwork survey, nearly three-quarters (73%) of C-suite executives believe their company fully embraces generative AI, including training for the technology.
• Just 53% of senior managers agree with that sentiment.
• Employee feedback is the key to closing the gap through upskilling and reskilling.

Research indicates that there is a gap between the level of AI training that leadership teams believe they provide their employees and the level of training that managers and employees perceive they receive.

According to a 2023 Upwork survey, nearly three-quarters (73%) of C-suite executives believe their company fully embraces generative AI, including training for the technology. However, this rate decreases as you move closer to individual team members, with only 53% of senior managers agreeing. A recent report from learning experience platform Skillsoft confirms this trend, stating that only 37% of employees say training is included in the technology adoption process.

Dr. Kelly Monahan, managing director of Upwork's Research Institute, stated that the disconnect is due to altitude, or one's position within the organization and the tasks they are paid to focus on.

According to IBM research, executives cite a lack of AI skills and expertise as the primary obstacle to AI deployment. However, addressing this issue is not as straightforward as simply filling a gap and moving on.

"Apratim Purakayastha, chief technology officer at Skillsoft, stated that executives often take a broad-brush approach to AI training, and simply checking the box does not suffice."

According to Pew Research, retirees are surpassing new workers in terms of productivity. This revelation is significant for leaders who have long relied on the next generation of digital natives to fill the skills gap. Monahan emphasizes the importance of leaders becoming the generative AI supply they need by upskilling and reskilling.

The responsibility for this lies with both individuals and organizations. While there is more democracy in learning today than ever before, many workers are burnt out from the constant change. However, the call to action remains. Organizations must prioritize efficiency without sacrificing learning and experimentation.

How can leaders and employees collaborate effectively during AI training?

What generative AI workplace leaders do

Upwork analyzed the strategies of companies that are successfully closing the gap and found that work innovators were 2.2 times more likely to incorporate generative AI into their daily operations. Additionally, they were 1.9 times more likely to have a formal generative AI skills program in place for their workforce and 3.8 times more likely to have a well-defined generative AI strategy.

Monahan stated that for there to be harmony in the way all levels see generative AI, there must be a simultaneous need for strategy, training, and operationalized workflows.

A programmatic approach to generative AI can be helpful, but it should be combined with a grassroots creation of community around the technology, according to Skillsoft's Purakayastha.

He stated on the programmatic side, "The approach involves providing resources and strategically designing programs to effectively enhance and transform skills in a quantifiable manner."

Benchmark assessments can be useful in identifying employees who are already learning on their own, according to Purakayastha. Additionally, a portion of them may be further along than expected. By using benchmark results, targeted upskilling programs can be designed, which can be implemented at the onboarding level through AI boot camps.

""Attend to people's needs by designing upskilling and reskilling programs," Purakayastha advised."

Purakayastha suggests that organizations should foster a sense of community around AI learning by creating forums for sharing ideas, launching a "prompt-athon," and developing a leaderboard for best prompts. This, he says, will create both a programmatic push and bottoms-up excitement, creating a virtuous flywheel of learning.

Job redesigns and economic productivity

According to LinkedIn's 2024 Workplace Learning Report, 89% of learning and development professionals believe that proactively developing employee skills is crucial for adapting to the ever-changing job market.

Finding agreement on what constitutes sufficient training in AI is not a solitary issue. It is as significant as the internet or the personal computer itself. As Purakayastha stated, "Keeping everyone up-to-date is a challenge because technology is changing at a rapid pace."

In 1987, American economist Robert Solow stated, "The computer age is evident everywhere except in productivity statistics." This phenomenon, known as Solow's paradox, applies beyond just the computer itself. According to Monahan, generative AI has the potential to bring about a new era of productivity, but only if we allow it to do so. In order to realize the renewed promise of productivity gains, organizational and job redesigns must take place.

Centering learning in our work is crucial for Monahan, as she believes that our over-emphasis on efficiency and productivity has caused us to lose sight of its importance.

OliverWyman's AI report, released at the World Economic Forum's 2024 meeting in Davos, Switzerland, stated that the future promises innovation driven by necessity.

The recent revival of AI demands that all organizational players, from entry-level employees to top executives, come together to determine what it means to be AI-ready. Failure to do so could result in the short-lived success of AI in the future of work.

If employees don't receive what they want from their employer, they will search elsewhere, which will harm the company in multiple ways.