Founder Insights
Every L&D vendor claims AI fixes everything. It doesn’t — and pretending otherwise is how teams end up disappointed.
I’m Fred, CEO of Thirst. Over the last eighteen months I’ve sat in more conversations than I can count where “AI” gets treated as a single, magic lever — one tool, one answer, the obvious next step for every L&D team regardless of what they’re actually trying to solve. It isn’t that simple. Some of what AI does for learning and development right now is genuinely transformative. Some of it is overhyped, half-built, or quietly making things worse when it’s left unsupervised.
So this is my honest attempt to draw the line: where AI is already doing real work in L&D, where it still falls short, and how we’ve tried to build Thirst’s AI capabilities around that distinction rather than around the hype cycle.
Where AI is already changing L&D
Strip away the noise and there’s a short list of places where AI is doing real, measurable work in learning teams today — not “someday,” today.
Content creation & curation
Drafting first-pass modules, quizzes, and summaries from existing material in minutes, and repurposing long-form content into microlearning that’s actually built for how people learn day to day.
Personalisation at scale
Adjusting pace, format, and sequencing to how each learner actually engages, and recommending remediation automatically rather than waiting for someone to notice a gap.
Assessment & feedback
Generating quizzes from source material and giving instant, contextual feedback — taking the manual grading load off instructional teams so iteration happens faster.
Learning analytics
Moving beyond completion badges to detect skill gaps, predict dropout risk, and flag where engagement and performance are quietly drifting apart.
of learning leaders now say digital learning is central to their strategy, according to the State of Digital Learning Report 2025 — and AI is the fastest-growing part of that shift, not a side experiment anymore.
Used well, this isn’t AI replacing L&D. It’s AI removing the parts of the job that were never a good use of a skilled team’s time — the content backlog, the manual grading, the searching for who-knows-what buried in a shared drive.
What AI in L&D still can’t do
This is the part most vendor pitches leave out, so I’ll say it plainly: AI has real limits in learning and development, and pretending it doesn’t sets teams up to be disappointed later, not sooner.
It can’t define your learning strategy. AI isn’t yet capable of setting business-aligned learning goals or building a competency framework from scratch. Ask it defining questions if you like — don’t hand it the pen.
It can’t build culture or motivation. AI can recommend relevant content, but it can’t create a learning culture, drive intrinsic motivation, or replace leadership. That has to be organisational, not algorithmic.
It can’t fix bad source content. Garbage in, garbage out. If the policy document you feed it is outdated, AI will confidently replicate the mistake rather than catch it.
It can’t replace human coaching. AI has a role to play in coaching support, but it can’t navigate the political dynamics or nuanced judgement that high-stakes leadership development genuinely requires.
It can’t manage change on its own. Behaviour change needs systems and accountability. AI can link learning to performance data, but it can’t enforce manager follow-through or make new habits stick after training ends.
Training magazine’s 2025 Industry Report puts global corporate training spend at around $102.8 billion — and plenty of L&D teams still can’t answer a simple question: did any of it actually change performance? AI doesn’t solve that by itself. Left unsupervised, it just makes the question easier to ignore.
Where we’ve drawn the line at Thirst
Thirst is built with AI woven through the platform, not bolted on as a chatbot. An AI assistant helps subject-matter experts turn what they know into structured content in minutes. Adaptive learning paths adjust to how each person actually engages. Skills-gap analytics tell L&D teams exactly where to focus next. Natural-language search means learners get a straight answer instead of a folder to dig through. Every one of those is built with human review kept firmly in the loop — because we don’t believe AI should run unsupervised in anyone’s learning strategy, including ours.
Using AI in L&D without losing the human part
The teams getting the most out of AI in L&D right now aren’t the ones who adopted it fastest. They’re the ones who were deliberate about where it fits.
Start with the biggest bottleneck, not the flashiest feature
Point AI at what’s genuinely slowing your team down — content backlog, onboarding time, invisible skills gaps — not whichever capability got the most airtime in a demo.
Give AI clear, correct source material
AI can create content, but it can’t add substance to content you give it. Check the documents it’s working from are accurate and current before you ask it to build on them.
Keep a human reviewing what AI produces
Treat AI output as a strong first draft, not a finished product. Someone with context should always check accuracy and tone before it reaches a learner.
Measure outcomes, not activity
Completion rates tell you AI sped up delivery. Time-to-competency, retention, and performance data tell you whether any of it actually mattered.
a week is roughly what knowledge workers spend searching for information or tracking down colleagues who hold it, according to McKinsey’s research into workplace productivity. That’s the single biggest opportunity AI-powered search and knowledge capture has in front of it right now.
What this means for growing teams in 2026
If you’re leading L&D at a growing business, you don’t need an opinion on every AI tool on the market. You need three things: a clear view of where AI genuinely removes friction for your team, a way to keep humans reviewing what it produces, and a platform that treats AI as infrastructure rather than a feature you switch on separately.
We’re not trying to hand the keys over to AI at Thirst, and I’d be sceptical of anyone who tells you they already have it all figured out. We’re trying to use it where it genuinely helps — capturing what your best people know, personalising how it reaches each learner, and surfacing skills gaps before they become expensive — while keeping a person firmly in charge of the decisions that matter.
AI won’t make L&D easy. It’s already making it faster, sharper, and a lot less reliant on any one person’s memory — and that’s a trade worth making. If you’d like to see what that actually looks like day to day, we’d love to show you.
Got 2 Minutes?
Thirst brings AI-assisted content creation, adaptive learning paths, skills-gap analytics, and natural-language search into one place — built to help growing L&D teams do more without adding to their admin load.
Take a quick guided tour today and see how Thirst’s AI could support your team →
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For more expert insights and tips, check out the Thirst blog.
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