How to Enhance Learning Strategies with Generative AI

Artificial intelligence remains a key investment area for many organizations, and the reasons vary. 

Some plan to launch their own applications, some will consult on solutions, and others want to make best use of the tools available to speed up tasks or become more productive. 

But before any of that can happen, many organizations are still trying to make sense of it all. 

They’re asking questions like: What exactly is AI, generative AI or machine learning? How does it impact employees across departments? How should I manage all of this change? 

And that’s key here: Change, understanding. 

Those were the overarching themes of a panel discussion with learning and development leaders at Skillsoft’s annual event Perspectives. 

The panelists represented industry leaders in banking, technology, retail and the federal government: 

• Joellen Jarrett, Chief Learning Officer and Division Director for Organization Effectiveness at the Small Business Administration
• Michael Wynn, Senior Vice President, Academy Innovation and Learning Technology Executive at Bank of America
• Gina Johnson O’Reilly, Director of Learning and Development at NTT Data
• Ryan Samia, Senior Manager of Talent and Leadership Development at Tractor Supply 

Together, they focused the conversation on how they see and anticipate generative AI, specifically, to impact learning at their organizations. 

Here are the takeaways of their conversation: 

Over the past few years, the buzz around AI has never been so loud. But through all the noise, people are still trying to make sense of what it is and why it matters. That was true for panelists. 

Joellen Jarret, with the Small Business Administration, explained there’s still a good deal of discovery happening in the federal government. “We are still in that cautious phase of implementation when it comes to AI,” she said. 

Front and center for the department is bolstering skills in domains such as AI fundamentals, the impact to privacy and information security, and data literacy. Building a strong foundation of technical knowledge is importance, she said, but what’s even more pressing is dealing with all the change. 

“The biggest skill sets are around change,” she said, explaining that employees of all levels are still making sense of the change and learning about the tools they have available to manage it. Generally, employees are faring well, given the break-neck pace, but there’s a lot to learn. 

Much of the conversation around AI focuses on a central concept: Change. AI is changing the way people work, how they learn and much else. 

How are people managing during a time of intense, constant change? 

Panelists gave their advice on how to handle it: 

1. You’ve got to be dogged. “You can’t give up,” Wynn said. “It can all be done, but it’s going to take a person who does not take ‘no’ for an answer.” 
    
2. Have a clear vision of the mission. “Making sure we have a compelling reason why,” Jarrett said, explaining it’s important to marry the objectives of learning programs to the organization’s overarching goals. 
    
3. Cross-functional collaboration. “In any organization, you have to make sure you’re not acting in a silo,” Samia said. Whenever he launches programs, it’s always a partnership with different functional departments. Doing so ensures better outcomes. 
    
4. Leadership’s direction and support. “We literally had our CEO come to us in July and said ‘Hey, by March 2025, we want all 149,000 employees to know their role with AI,” Johnson O’Reilly said. If leaders see AI as a priority, the chance of successful learning programs is that much greater.

“It’s going to be revolutionary when you really think of the potential of what AI can bring to the table,” Wynn said. 

AI may usher in more dramatic changes to the way people learn — which for a long time, Wynn pointed out, hasn’t changed a whole lot. 

“Especially traditional learning, it hasn’t evolved quickly enough,” he said. “The problem is that our people don’t want to learn that way anymore.”

Today, developing training that keeps pace with change and stays relevant often feels impossible. Because of that, those who use AI to develop learning programs will find it easier to overcome this insurmountable challenge. 

“The technology is only going to make our trainers’, our facilitators’, our managers’, our leaders’ jobs so much easier because our associates are going to get the information they need so much more quickly,” he explained.

The future certainly looks bright when it’s put that way, but what’s it going to take to get there? 

Gina Johnson O-Reilly, with NTT Data, says that the first step is acceptance. “The real need is to understand how exactly our organization needs to accept AI,” she said. “For us, the big drive isn’t being out front of all this… but understanding role by role where AI comes into play.” 

AI’s ubiquity is becoming more apparent for people regardless of their role. Tools are plentiful. The technology, powerful. Yet, it’s still unclear how workers should use it in their day-to-day work. That’s what they’re trying to figure out at NTT Data, she said. This exploration is influencing their learning programs and which tools they onboard. 

Johnson O’Reilly said that NTT Data is using Skillsoft’s CAISY to help people interact with AI and practice topical conversations and also Skill Benchmarks to measure how much people learn over time. Knowing which tools are available and how they can help individuals is key, she said. 

Ryan Samia, with Tractor Supply, echoed similar ideas. The team at Tractor Supply is taking a multifaceted approach to help employees learn about the technology itself, how it can be applied on the job, and how leaders can support their teams during a salient time in the tech’s use. 

“It’s been an intentional approach over the last couple of years to slowly embed AI into some of our programs,” he said, adding Tractor Supply launched an academy with programs aimed at teaching AI fundamentals and its relevance at work. 

Wynn mentioned early in the panel that traditional learning programs feel more like checking a box. But now with AI’s capabilities, he says it’s an opportune time for change. And it’s playing out at Bank of America. 

Wynn says their approach is focused more on practical application now. “It’s all about implementing more practice and engagement into our programs,” he said. 

The idea is to give people more ways to demonstrate their newfound knowledge and skills in hopes that the teachings will sink in. 

For Jarrett, it’s a similar story. As CLO, her strategy at the Small Business Administration is to go beyond the content. 

“We’ve moved to try to implement cohorts wherever we can,” she said. “We did implement CAISY, and on an individual basis it’s a great tool, but we have more success, more excitement when we bring people together to talk about their experience with CAISY.” 

Similar work is being done at Tractor Supply and NTT Data.

At Tractor Supply, several cohorts of leaders come together to work with CAISY on an individual basis as a complement to practicing with their peers. Likewise, learning communities exist at NTT Data, where many employees pursue technical certifications. 

Often, groups will study together or help one another as they prepare for exam day. Doing so helps reinforce the subject matter, while bringing a sense comradery to learning.  

“That piece is invaluable,” Johnson O’Reilly said. “That human element… is really what’s pushing all of the technology we have at our fingertips.”

Every year, Skillsoft invites industry leaders to Perspectives with the main goal to learn from one another. Everyone’s expertise and experiences surface during panels and Q&As, keynote speeches and spontaneous chats in passing. 

If you missed out this year, don’t fret. You can catch up on all that was covered during the panels on demand.