Hosted by Jackrabbit Learning Experience (JLX) in October 2025, the AI Forum for Learning Professionals is a series of webinars that brings together educators, instructional designers, technologists, and learning leaders to explore how artificial intelligence is reshaping the way we design, deliver, and imagine learning.
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Session 2: Recent AI Wins & Challenges
December 11th, 2025
Last week, like-minded professionals across the learning professions gathered for another AI Forum for Learning Professionals.
The best part was the tone: candid, practical, and grounded. This wasn’t a “look at this tool” session. It was a room full of learning leaders, designers, and educators comparing notes on what’s actually changing in our day-to-day work.
If you missed our previous forum recap, you can find it below.
A snapshot of our incredible team and collaborators at the AI Forum, organized on December 11th, 2025
The moment that stuck with me most
Several people shared a version of the same experience:
They’re being told to “experiment with AI,” but they’re not being given any real guidance or scaffolding, so they feel anxious or frozen.
That one line explains a lot of what’s happening in learning right now. We’re not short on tools. We’re short on leadership strategy, shared norms, practical workflows, and confidence about what “good” looks like.
What we did in the session
We kept it simple:
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- We started with AI wins, where people shared real examples of AI being used productively (not hypothetically).
- Then we moved into challenges, capturing them on a mural so we could see patterns, not just anecdotes.
- We compared what’s showing up across contexts: higher ed, nonprofits, corporate L&D, and learning-tech teams.
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We used Mural to build out a whiteboard for our challenges. Once it filled up, you could feel the collective exhale: “Oh, good, it’s not just me.”
The challenges people raised, in plain language
Here are the themes that came through most strongly, with the language cleaned up but the meaning preserved.
1) Tool overload, investment anxiety, and “AI slop”
People are trying to make decisions while the ground is moving: too many tools, constant updates, and a real fear of investing time in the wrong place.
Related tension: it’s hard to build consistent habits when everyone is chasing the next shiny thing.
2) Human judgment vs button-pushing training
One of the clearest threads: teams want “AI fluency,” but many organizations are defaulting to shallow enablement, meaning tool tours and quick prompts, instead of developing judgment, critical thinking, and domain-informed decision-making.
3) Assessment integrity (especially in higher ed)
The higher ed professionals in the room were blunt: guarding assessments against GenAI is one of the biggest immediate challenges, and it’s not going away.
4) Leadership expectations around replacing SMEs
A recurring, uncomfortable question: leadership hopes AI can almost fully replace an SME. People are trying to figure out what’s responsible, what’s realistic, and what quality looks like when the SME’s role changes.
5) “How do we design for deeper learning, not just faster output?”
This is the design problem underneath everything: how do we create AI-supported learning experiences that deepen understanding rather than reinforce shortcuts?
6) Trust, transparency, and the black-box problem
People want to know what’s under the hood: which model is being used, what layer is on top, what data is touched, and why the tool behaves the way it does.
That lack of transparency makes it harder to build confidence, and harder to set guardrails.
7) Budget and access constraints
A practical, underrated barrier: limited budgets keep teams on free plans, and hitting usage limits can kill momentum right when someone is becoming a “power user.”
8) Tactical build questions that are not actually “tactical”
Some questions looked tactical on the surface, but they’re really strategy questions in disguise:
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- How do we responsibly incorporate AI-generated visuals and explainers into learning?
- When does AI voice or video help, and when should we center humans?
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The “AI wins” people shared
We also collected wins, and these were the antidote to the anxiety. These are not promises. They’re examples of teams doing real work, right now:
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- A community-based organization hosted a student and parents’ AI event and saw kids demonstrate serious skill and confidence.
- Someone used Websets to search globally for people, with capabilities rated and organized.
- A team is using AI across roughly 2,000 hours of transcripts to pull relevant snippets and speed up edits across a large course library.
- Someone is designing and facilitating responsible AI workshops for IT teams, focused on human skills, domain expertise, and aligning AI use to actual learning goals.
- Someone is building an AI coach designed to strengthen human connection, with research support and an enterprise launch planned for January.
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A quiet takeaway from the wins: the best results weren’t “AI replaces the work.” They were “AI changes the shape of the work,” while humans stayed accountable for quality, intent, and judgment.
What’s next: A Slack channel, built with the community
We’re setting up the Slack channel we discussed. The goal is simple: a place to compare notes between forums without creating noise.
If you’d like to help set it up in a way that’s genuinely useful, I’d love collaborators on:
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- structure and channel naming
- norms and onboarding message
- lightweight moderation and governance
- ‘how to keep it active’ without turning it into another obligation
- structure and channel naming
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Please contact us if interested in helping: events@jackrabbitlx.com
One closing thought
The forum reinforced something I keep coming back to:
Most learning teams don’t need more AI hype. They need shared practices, clearer judgment, and space to learn together. If that’s what you’re trying to build too, you’re in the right company.
Podcast Alert: The Learning Experience Ops Show
We also have a podcast related to the forum, focused on the real work of building and running learning systems.
Podcast link: JLX Podcast | Jackrabbit Learning Experience