Latest / Future of Work Tech with Fexingo: Remote Tools, AI Productivity, and Workplace Software / How AI Is Reshaping Your Corporate Learning Budget
Transcript
- Lucas: There's a number that's been stuck in my head all week: the average large company spends about $1,200 per employee per year on learning and development. But something like 70 percent of that goes to content that nobody finishes. Luna: That stat is brutal. And it's exactly why a lot of CFOs are starting to ask their L&D teams hard questions about ROI. Lucas: Right. And the answer from a growing number of those teams is ai powered platforms that flip the old model on its head. Instead of paying for a library of courses, you pay for actual engagement and outcomes. Usage-based pricing, adaptive learning paths, real-time skill gap analysis. Luna: So instead of a flat annual license for a learning management system, you're talking about something more like a Spotify model for training? Lucas: Exactly. But even more targeted. Take a company like Axonify. They focus on microlearning — short, two-to-three-minute bursts of content delivered through workers' existing tools. The AI figures out what each person already knows and what they're about to forget, then serves up exactly the right refresher. Luna: And that drives completion rates way up, I assume? Lucas: Dramatically. Some of their clients report completion rates over 90 percent, compared to maybe 20 or 30 percent for traditional annual compliance courses. And because the pricing is based on active users per month, companies can scale up or down without being locked into a huge upfront commitment. Luna: So the CFO sees a variable cost that's tied to actual usage, not a sunk cost. That's a much easier sell in a belt-tightening environment. Lucas: Exactly. And it gets better. There's a platform called Howspace that uses AI to facilitate collaborative learning. Instead of a static course, you get an AI moderator that prompts discussion, summarizes key points, and even generates new content based on the conversation that's happening. Luna: That sounds like it could replace a lot of the facilitation work that consultants used to bill for. I've seen some case studies where companies cut external facilitator costs by 40 to 50 percent. Lucas: Yeah, and that's the kind of savings that gets noticed at the executive level. But I think the bigger shift is happening in how companies even decide what training is needed. Traditionally, you'd do an annual skills assessment — a survey, maybe some manager input — and then you'd design programs around that. Luna: Which is always out of date by the time you launch it. Lucas: Right. AI changes that because it can analyze actual work patterns. Tools like Degreed or EdCast can pull data from your project management software, your CRM, even your email, to identify skill gaps in real time. If the sales team suddenly needs to learn a new product feature, the system knows within days, not months. Luna: And then it can automatically recommend or even assign relevant microlearning modules to the right people. That's learning in the flow of work, as the buzzword goes. Lucas: Exactly. And that's where the budget math gets interesting. A traditional LMS might cost $30,000 a year for a mid-size company, plus content licensing on top. An ai driven platform like Axonify starts at around $5 per active user per month. For a company with 500 employees, that's $30,000 a year — but you only pay for the people who actually use it. Luna: And if you have high turnover or seasonal workers, you're not paying for seats that sit empty. That's a real structural advantage. Lucas: Yeah. And then there's the content side. Instead of buying expensive off-the-shelf courses, companies can use AI to generate custom content from their own internal materials — product specs, process docs, even recordings of expert employees. One platform I looked at, called 360Learning, uses AI to turn a subject matter expert's notes into a full interactive course in about an hour. Luna: Which means you're not paying for a content vendor either. That can be a huge line item in the L&D budget. Lucas: Huge. Some companies report slashing their external content spend by 60 to 70 percent. And the internal content tends to be more relevant to the actual job, so engagement goes up. Luna: But I want to push back a little. Doesn't this create a risk of algorithmic bias in who gets recommended what training? If the AI is pulling data from your email and calendar, it might reinforce existing patterns — maybe women get recommended more compliance courses while men get recommended leadership development. Lucas: That is a very real concern. And some of these platforms have been criticized for exactly that. The data inputs are only as good as the underlying work patterns, which can be biased themselves. A good system needs to have guardrails — explicit diversity checks on recommendations, and human oversight. Luna: And transparency. If an employee gets recommended a certain training path, they should be able to see why. Otherwise it's a black box. Lucas: Totally agree. And I think the best companies using these tools are pairing the AI with a human coach or manager to validate the recommendations. The AI is a force multiplier, not a replacement for judgment. Luna: So overall, the shift is real. But it's not just about cost savings. It's about making training actually work. Lucas: Exactly. And that's why I think we'll see more CFOs reallocating budget from traditional training to these ai powered models. The ROI case is getting stronger every quarter. Luna: It's also worth noting that, like a lot of what we cover on this show, the technology is only part of the story. The culture has to shift too — managers have to actually encourage learning during work hours, not just on lunch breaks. Lucas: That's a great point. And speaking of culture, something we're really proud of here at Fexingo is that we keep this show ad-free. No sponsors, no commercials, no interruptions. It's a choice we made from the beginning because we think the conversation should be the only thing that matters. Luna: And that choice only works if listeners who find value in it choose to support it. If today's episode gave you a useful framework or a concrete number to bring up in a meeting, you can help keep this going at buy me a coffee dot com slash fexingo. Lucas: Yeah, it's a small way to ensure this kind of deep-dive conversation stays available to everyone. And we genuinely appreciate everyone who's already done that. Luna: Okay, back to the learning budget shift — one more angle I want to touch on: what about the smaller companies that can't afford even the per-user pricing? Are there AI options for them? Lucas: There are. Some platforms offer free tiers with limited functionality, and open-source tools like Open edX can be self-hosted. But I think the bigger opportunity is in bundled offerings — like if your HR platform or project management tool adds an AI learning module. We're already seeing that with things like Microsoft Viva Learning. Luna: So the future might be that learning is just embedded in the tools you already use, not a separate system at all. Lucas: Exactly. And that's when the budget really disappears as a line item. It just becomes part of the tool subscription. Which makes it even easier for a CFO to say yes. Luna: And harder for an employee to avoid it. But if the learning is actually useful and personalized, that's probably a good thing. Lucas: Yeah, the key is the personalization. The old model was one-size-fits-all training that nobody wanted to do. The new model is adaptive, just-in-time, and embedded. And the numbers suggest it's cheaper and more effective. That's a rare win-win. Luna: Alright, I think we've covered the key shifts. For anyone managing an L&D budget, I'd say the takeaway is: look at your per-learner cost, your completion rates, and whether you're paying for content nobody uses. The AI alternatives are worth a serious look. Lucas: Agreed. And we'll keep tracking how this evolves. Thanks, Luna. Luna: Thanks, Lucas. See you next time.