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Transforming L&D with AI: Accessible Knowledge Insights for LIFOW
“Employees aren’t asking for more courses; they’re asking for answers the moment they need them.”
This revelation, posed during Panopto’s recent webinar The Future of Learning Isn’t More Training—It’s Accessible Knowledge + AI, set the tone for a conversation that challenged how organizations think about learning and development.
The discussion, featuring Dr. Katie Campbell, Senior Director of Learning and Talent Management at Equifax, Bill Sodeman, Ph.D., business coach at Focal Point, Jillian Moulton, VP of People at Fabric, and Inna Horvath, Senior Learning Strategist at Panopto, explored a simple truth: the modern workplace doesn’t suffer from a training problem; it suffers from an access problem.
Across industries, employees aren’t struggling because they lack content. They’re struggling because they can’t find or apply knowledge when it matters most. And as AI becomes woven into every workflow, this challenge and opportunity has never been greater.
From Courses to Context: The Shift to Access
For years, organizations have equated “learning” with “courses.” Structured modules, completion certificates, and learning paths dominated L&D strategies. But as Dr. Katie Campbell pointed out, “What professionals expect today is to have a problem solved at the exact time they face it.”
The audience laughed knowingly when she added, “Why wouldn’t I just use my organization’s platform the same way I use ChatGPT—to get a quick solution when I need it?”
That comment captured the heart of a transformation already underway. In the age of instant answers, the traditional course model often feels too slow and too detached from the flow of work. Instead of designing long, linear learning programs, organizations must create systems where information is findable, contextual, and actionable.
As Bill Sodeman described it, “People aren’t going to go through the same door in the mall to get to where they want to go or even go into the mall anymore.” The walled gardens of corporate learning are giving way to open ecosystems where employees navigate their own pathways, guided by curiosity and relevance.
Ownership and the New Architecture of Knowledge
A central theme that emerged was ownership: who truly “owns” knowledge in an organization? Is it IT, HR, or the L&D department?
Jillian Moulton framed it as a question of freedom and enablement. “With AI customization, we’re getting closer to true enablement,” she said. “L&D used to be about maintaining content, keeping it current and compliant. Now, it’s about making knowledge more future-forward, more personalized, and closer to what employees actually need in their jobs.”
That freedom comes with complexity, especially in regulated industries like finance or healthcare. Dr. Katie Campbell acknowledged that compliance can’t be sacrificed for flexibility, but the two aren’t mutually exclusive. “The challenge is balance: preserving regulatory integrity while providing autonomy where it makes sense.”
In this evolving landscape, knowledge isn’t something owned by a department; it’s co-created, distributed, and continuously refreshed across the organization. AI, when used thoughtfully, becomes the connective tissue that turns scattered expertise into accessible, living knowledge.
The Human–AI Partnership: Technology as a Teammate
If there was one idea that united all three speakers, it was that AI should be seen as a partner, not a replacement.
“The best learning happens through the partnership between humans and AI,” said Jillian Moulton. “There’s enormous potential when experienced professionals bring their judgment and context, and newer employees bring technical fluency. Together, they can use AI to synthesize information and accelerate performance.”
Bill Sodeman built on this, referencing the emerging concept of technology as a teammate. “AI isn’t here to replace people; it’s one part of a much greater whole that strengthens the team,” he explained.
Practical applications already abound. AI tools can generate personalized learning paths, summarize discussions, suggest relevant micro-learning resources, and even provide “safe spaces” for practice. As Campbell described, “Practicing with your boss can be intimidating; practicing with AI isn’t. If I can make mistakes with AI first, I’ll be better when I step into the real moment.”
This theme that AI expands psychological safety for learning resonated strongly. Rather than automating humans out of learning, AI can humanize the experience by making feedback more immediate, private, and supportive.
Building Learning in the Flow of Work
One of the webinar’s most actionable discussions focused on how to design learning that happens in the flow of work, not apart from it.
Bill Sodeman noted that employees are increasingly drawn to platforms like LinkedIn Learning, precisely because they provide bite-sized, just-in-time access. But the key, he argued, isn’t just content format; it’s architecture.
“We need learning systems that employees can navigate as naturally as they navigate their work tools,” he said. “When AI is embedded directly into the systems they already use — whether it’s a CRM, a helpdesk tool, or a video management platform — that’s when true in-the-moment learning happens.”
Katie Campbell offered a vivid metaphor: “It’s like adding a new smart wing to a home you already live in. If the technology makes life easier, not more complicated, people adopt it naturally.”
The takeaway: learning technology must disappear into the workflow. The less employees think about “doing training,” the more time they spend actually learning.
Measuring What Matters: From Completions to Performance
For decades, L&D teams have reported on metrics like completion rates and participation. The panelists agreed that the era is over.
“We measure what’s easy, not what matters,” Sodeman said bluntly. “Completion doesn’t equal competence. The real measure is performance.”
Campbell emphasized the need for business-aligned outcomes. “If you don’t start any learning initiative, AI or not, with a business outcome in mind, you shouldn’t start it,” she said. Her own boss’s mantra stuck with the audience: “HR and learning should operate like a profit center.”
Moulton described how her team redefined measurement by engaging business leaders directly. “We ask department heads: What does success look like for your people? More deals closed? Faster integration after an acquisition? Those are the metrics we should align to, not just whether someone completed a course.”
The shift is clear: in the age of AI and data-rich platforms, learning teams can finally connect knowledge to impact. Dashboards that link learning activity to sales performance, customer satisfaction, or product innovation aren’t a distant dream; they’re becoming standard practice.
Redefining the Role of L&D: From Administrator to Change Leader
The conversation also turned introspective. As AI transforms the profession itself, what does it mean to be an L&D practitioner today?
“We’re being asked to do more than ever, often more than our roles officially include,” Campbell reflected. “But maybe that’s because L&D is becoming the driver of change, not just the responder.”
Moulton agreed, arguing that the profession must evolve from administration to aspiration. “If you’re just receiving requests, you’ll fall behind. We need to be proactive to build what the business will need next, not just what it asks for today.”
Sodeman added that the best L&D work he’s seen lately focuses on excitement, not compliance. “Change management gets people excited about where the organization is going and about their own journey within it.”
In that sense, AI is not only transforming how people learn but also how L&D leaders lead as strategists, data translators, and connectors of cross-functional innovation.
The Access Revolution: Leading, Not Catching Up
In response to the question of whether L&D is leading the AI revolution or scrambling to keep up, the panelists were optimistic.
“This is our moment,” said Moulton. “AI adoption isn’t just coming from CIOs anymore; it’s also being led by CHROs. That’s a huge opportunity for HR and L&D to step forward and show what responsible innovation looks like.”
Sodeman pointed out that AI is breaking down silos inside organizations, but only when L&D helps coordinate efforts across departments. “Everyone’s excited and experimenting,” he said, “but not always together. L&D can be the bridge that gets everyone rowing in the same direction.”
That collaboration between HR, IT, operations, and leadership may be the key to transforming AI from a buzzword into a sustainable, human-centered advantage.
Looking Ahead: Learning as a Living System
By the end of the discussion, it was clear that learning is no longer something that happens in a classroom or an LMS. It’s a living, evolving system—one that must adapt as quickly as the organizations it serves.
The future of learning, the panelists agreed, will be defined by three principles:
- Access over accumulation. Knowledge must be available in the flow of work, not locked inside courses or folders.
- Partnership over automation. AI should amplify human insight, not replace it.
- Impact over activity. What matters isn’t how many courses employees complete, but how their learning changes business outcomes.
As the moderator closed the session, she echoed a powerful reminder:
“The future of learning is already here. It’s just not evenly distributed yet. It’s our job to make knowledge accessible, findable, and useful when it matters most.”
In a world overflowing with content, that mission may be the most strategic advantage any organization can build.
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