u/ResidentAstronaut736

Been trying to figure out what's actually shipping under the "agentic AI" label versus what's just a pitch right now. Here's what I found:

Microsoft is putting Copilot straight into LMS platforms starting this spring.

Absorb has a thing they're calling a readiness gate. Instead of just checking if you finished a course, it checks whether you can actually do the thing before it lets you move on. So instead of a manager finding out three weeks later that training didn't stick, the system catches it right there.

The pattern I keep running into is systems that just act without anyone telling them to. A manager used to have to notice someone struggling and go assign training manually. Now some platforms are supposed to catch that dip themselves and push a quick module out, sometimes even loop in a coaching bot before anyone's even flagged a problem.

"Agentic" is turning into a buzzword the same way "AI-powered" did a couple of years back. Might be worth checking whether something's actually taking action on its own or just responding a bit quicker than before.

Anyone actually seen this working for real, or still mostly hearing about it in demos?

I've been evaluating platforms for a client and got tired of every vendor call starting with "we have AI now." So I actually went and looked at what shipped recently, not the roadmap slide, the actual released feature.

Here's where things stand on 5 things that matter if you're picking an LMS in 2026.

Content personalisation: Docebo is still ahead here. Auto-tagging, content recommendations, and a genuinely large marketplace. This has been their core bet for a while, and it shows.

Roleplay-based practice: Lyearn is the strongest here right now. The practice sessions aren't a standalone exercise; they feed directly into a skill signal that shows up elsewhere in the platform. Cornerstone shipped something similar, an AI sales coach through their Galaxy AI agents, decent if you're already in their ecosystem, but it stays siloed as a coaching tool rather than connecting to a broader skill record.

In-course learner support: This is where most platforms are still weak. A learner gets stuck mid-course and either Googles it or gives up. Lyearn's AI Coach sits inside the course itself and answers questions from the actual course content, not a generic model guessing at context. Nobody else I looked at has this working cleanly yet.

Content authoring speed: TalentLMS is solid here for smaller teams, fast, accessible, and gets a course out the door quickly. Not the deepest AI stack, but it does the job without a steep learning curve.

Talent and performance integration: Cornerstone wins this one by default since it's a full talent suite, not just an LMS. If you need learning tied to succession planning and performance reviews in one system, this is the category leader.

Curious if anyone has performed similar research and what the results look like?

Unpopular opinion: low completion rates are not a content problem. They are a support problem.

Here is what the data actually shows. Learners do not drop off because a course is too long or too boring. Engagement data consistently shows drop-off spikes at specific points, usually where concepts get harder or instructions become ambiguous.

In other words, people quit the moment they get confused and have nowhere to turn.

Think about how absurd that is. We spend months building training content, then leave learners completely alone the moment they actually need help. The assumption is that good enough content should explain itself. It never does.

The entire e-learning industry has optimised for content delivery. Nobody has seriously solved, for the moment, that learning actually breaks down.

How are the tools you use tackling it?