Best Practices in AI Upskilling: Start with a Strong Philosophy

With the rapid and disruptive emergence of generative artificial intelligence (GenAI) tools, organizations of all kinds are scrambling to understand their potential applications; create policies to protect company assets, intellectual property, and brand value; and provide employees with the information and training they need to effectively and efficiently use these tools. This comes at a time when company leaders and learning and development (L&D) professionals may themselves lack expertise in the tools or their applications in the workplace.

Saying that companies have been scrambling to keep pace with the proliferation and ongoing enhancements of GenAI tools would be an understatement. Employers know these tools hold both potential value and potential peril. But they also know that many employees aren’t familiar or even comfortable with what these tools are, what they can do, or what risks they pose.

However, it’s likely that there are employees in your midst with the skills and potential to step into AI-related roles, if they are given the right training and coaching.

Skills Needed Now

While GenAI is a recent development—emerging in late 2022 and throughout 2023—AI itself is not.

Ramona Schindelheim is editor-in-chief at the nonprofit media organization WorkingNation and has written extensively on how AI is changing the nature of jobs. AI is really not “new” technology, she said. It’s been around for decades. But because GenAI tools such as ChatGPT are relatively new products that employees can use at home, she said, “it’s becoming part of the conversation more and more.”

Despite the buzz around AI, and especially GenAI, few workers feel they’re up to speed on the technology.

Research from WalkMe, a digital adoption platform company being acquired by SAP, indicates that only 15% of Americans consider themselves to be AI experts, and only 7% have received extensive AI training.

The good news, though, is that 84% think AI tools are becoming more important for having a good job and advancing their careers. And vendors are certainly pushing these tools.

Schindelheim attended CES (formerly the Consumer Electronics Show) in January and found that “nearly 99% of the companies on the exhibition floor had AI this, AI that.” But when she took the time to talk to exhibitors, she found that “they don’t have the manpower to follow through.” That creates a gap in terms of training and development for employees who need to learn how to effectively use these tools.

“Companies need people who are good with data and good with analysis,” Schindelheim said. “They need people with good cognitive skills and strategic minds.” Unfortunately, HR leaders are struggling to find the talent they need to fill AI-related skills gaps.

“Seventy-three percent of HR leaders in the U.S. and Canada say they are having a hard time finding people needed to do these jobs,” she said. “It’s a confusing time.”

Developing Skills Internally

“HR leaders should look inside their own organizations and try to identify what skills people already have,” Schindelheim advised. “It’s more expensive to go outside your company to recruit people than it is to look inside your own organization and upskill.”

Marc Booker, vice provost of strategy at the University of Phoenix, said employers often overlook their own workers. “Believe that your existing employees can lean into AI and have the skills and abilities to be upskilled instead of going outside of the organization,” he said. “Several roles tied to AI—like prompt engineering—do not need long-form credentials like a data science or programming degree. Taking existing personnel and unlocking their potential through training may be a cleaner and more efficient path that also drives better employee engagement than hiring externally.”

Before embarking on an internal AI upskilling program, though, some important initial steps must be taken.

Organizations should create an overall philosophy on how they will approach AI and upskilling employees, Booker said. Success “requires a clear path and direction on what is necessary to learn and apply for the improvement of an organization,” he noted. In addition, “AI and its uses, models, applications, and designs are vast and varied. An organization that has not taken the time to create a philosophy, determine ethical use, and identify goals will have a hard time directing employees to the right trainings or programs to get involved in to properly upskill, so focusing on this will create clear pathways of development that benefit both the employee and the organization.”

In addition, HR and L&D leaders need to assess and upskill their own capabilities and competencies.

HR leaders must familiarize themselves with AI, Schindelheim said. “The more knowledge you have, the better off you are.” She recommended that HR leaders understand how AI might impact workflows in both positive and negative ways, make sure they’re using credible sources and vendors, and understand what their companies are going to be using AI tools for.  

A Case in Point

Professional services firm EY is an example of an early adopter of AI—and an early implementer of robust upskilling efforts, said Simon Brown, EY’s recently named global learning and development leader.

About 220,000 people have gone through the company’s core AI training, called “AI Now.” More in-depth programs are also being offered in AI engineering and applied AI, with different levels of proficiency. About 60,000 people are either working on or have completed these programs.

Leaders are also being trained and coached in how to incorporate AI into their strategy and how to use it within their teams. In-depth boot camps are being used to bring people together for a look at what AI is and how to apply it, Brown said.

As a professional services firm, EY is likely ahead of the curve when it comes to AI adoption and education, he said: “Very early on, EY took the view that AI is super important and needs to be something that we have a very strong capability in. We have a global head responsible for AI, we have committed to a billion-dollar-plus investment into AI, and we’re going full steam ahead to make sure that we not only build the internal capability, but also that we stay ahead of the curve so we can support our clients as well.”

A strong philosophy and infrastructure and a commitment to ongoing training and education positions the firm and its employees to effectively leverage AI tools, even as new tools emerge and technology continues to change, Brown explained.

Best Practices

There are some important best practices for organizations to consider as they embark on their own AI upskilling efforts.

First, suggested Brown, don’t take a one-size-fits-all approach to upskilling. “Segment the audience, recognize that not everyone needs the same thing, and then build out solutions for different segments to make sure they get what they need,” he said. In addition, “try to learn from others and don’t be afraid to be bold and ambitious—in a safe and responsible way.” Brown added that it’s through experiments that companies will best find out what works and what doesn’t. Therefore, they should create a “culture of curiosity.”

Booker also recommended employers create an environment that encourages the exploration of AI solutions in the workplace. “There is no better teacher than hands-on practice, and hands-on practice that leads to improvement is a powerful agent for change,” he said. “This approach has a myriad of benefits, from learning more about AI models, improving the skills of users, limiting risk from employees using unsupported tools, and improving organizational processes with outcomes of the AI experimentation.”

In addition, suggested Booker, companies should look beyond formal training programs to implement mentorship and community-of-practice opportunities.

Lin Grensing-Pophal is a freelance writer in Chippewa Falls, Wis.