How To Turn Your E-Learning Business Into An AI Coaching Solution

You’ve probably heard the hype about AI coaches. But most of what’s out there is either too vague to be useful or completely detached from how EdTech platforms actually work.

This webinar cuts through all of that. It’s a practical walkthrough for LMS, training, and EdTech providers who want to launch an AI coach into their product this month—and start seeing value immediately.

In under 30 minutes, we’ll cover:

• Why learners increasingly expect AI-powered support (and what that means for your clients)
• What makes an AI agent different from an AI coach
• How providers are positioning, pricing, and deploying AI coaches in real client-facing platforms
• A glance at the full implementation process

You’ll also hear real examples from providers like Training Industry, 5app, and Mintra—including how they’ve used AI coaches to drive re-engagement and recurring revenue.

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Why the shift toward AI coaching?

AI-assisted learning isn’t some emerging trend—it’s already reshaping how people consume content. About one-in-five U.S. adults have used ChatGPT to learn something new, and that number is expected to keep climbing.

That’s not great news for traditional learning platforms.

When learners want quick, contextual answers, they’re not browsing course catalogs or clicking through an LMS. They’re opening ChatGPT or asking their phone. Just consider the launch of Apple Intelligence: generative AI will soon be native on every iPhone. The bar for user expectations is rising—and fast.

Enterprise platforms like Microsoft Viva and LinkedIn Learning have already responded with AI coaching features of their own. Because they understand what’s at stake:

• Your customers have huge content libraries that are core to their revenue.
• But learners often get overwhelmed trying to find what they need.
• That leads to frustration, low return rates, and churn.

If your platform can’t help users access relevant learning in the moment they need it, they’ll go elsewhere — even if that “elsewhere” is free.

This is where AI coaches come in. They don’t replace your content. They make it useful again.

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Demystifying AI agents vs. AI coaches

Before you can launch an AI coach, you need to understand what it actually is—and what it isn’t.

Let’s start with AI agents.

An AI agent is a modular system that can:

• Access multiple content sources (your own, your clients’, or both)
• Execute planning and workflows: it doesn’t just answer questions, it decides how to solve problems.
• Use external tools for things standard chatbots can’t handle like calculations, surveys, file searches, etc.
• Collaborate with other agents, for example, a “librarian agent” can hand off to a “simulation agent” depending on the user’s request. These are called multi-agent systems. ‍
• Run inside any interface: Slack, Microsoft Teams, mobile apps, intranets, your client’s LMS — you name it.

That’s the foundation, but ifyouwant to learnmore about AI agents, check out our Agentic AI 101 Guide.

An AI coach builds on those capabilities and adds structure—so it can actually support development and drive learning outcomes. An AI coach has other core features, such as:

• Skills gap detection: It doesn’t just respond to a question. It figures out what someone needs to learn—through assessments, simulations, or quizzes — and uses that to shape the experience.
• Timely, snackable delivery: It meets users where they are—whether that’s Slack or Teams — and gives short, useful answers that match their context.
• The right resource, at the right moment: It connects the learner with the most relevant piece of content—whether that’s a 30-minute course, a 3-minute video, or a live support option — based on what they’re trying to achieve.

But the additional features and capabilities your AI coach takes on really depend on your needs. Also, if you are a bit unsure about what’s the difference between AI agents, virtual assistants, AI chatbots, workflows, and similar, take this AI agent quiz.

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Real AI coach use cases that work

AI coaches aren’t just theory. They're already deployed across EdTech, LMS, and training platforms—driving new revenue, increasing engagement, and giving customers a reason to renew.

Across different providers, we’ve seen AI coaches used to:

• Surface relevant content quickly from massive course libraries
• Deliver instant answers instead of forcing users to dig through LMS menus
• Guide reflection sessions that adapt to learner input
• Run simulations for skill development in context

Here’s what that looks like in practice:

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Mintra

Mintra, a large e-learning and training provider, built an AI coach to support learners post-course. Most users completed a course and didn’t return. The solution? An always-available AI tutor and mentor that delivers contextual, just-in-time learning—helping Mintra introduce a new subscription model for repeat engagement.

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Training Industry

Training Industry deployed an AI agent that supports learners across their full offering—courses, webinars, podcasts, and membership content. The goal: make sure learners can find and apply insights, wherever they came from. It turns passive content into an active experience. Their agent, Tia, attracted over 1,400 new trial users during their first three months of use and about 11% of those new users converted to a paid membership.

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5app

5app, a platform for partner and employee enablement, used AI agents to help users find files, complete workplace tasks, and reflect on challenges — without sifting through training materials manually. These agents are embedded into their platform with the company’s own branding and content rules in place.

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Whether it’s for sales enablement, compliance, leadership training, or partner enablement, AI coaches are proving value across multiple contexts—without requiring massive changes to the underlying platform. Read more usecase examples and customer stories here.

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How to launch an AI coach (without rebuilding everything)

If this all sounds like a huge integration project, it’s not. Most providers are up and running with Mindset AI within 30 days, some launch in less than a week, and one customer deployed it into their mobile app within 48 hours.

You’ve got two main options:

1. Embed into your existing platform (Mindset AI Embed)
   Use just three lines of code to drop the AI coach into your product—whether it’s as a chat assistant on the side, a full-screen interface, or both. Read more about our SDK.
2. Launch a branded standalone app (Mindset AI App)
   Web, mobile, or tablet—entirely white-labeled, with AI coaching built-in.

The setup process is designed for real-world content situations (and yes, that includes messy SCORM files, random PDFs, and 10-year-old training videos).

Here’s what it looks like:

• Content ingestion: Drop content into a synced location (Google Drive, SharePoint, AWS bucket, etc.). The agent pulls from there automatically. Updates are synced in real-time — no manual maintenance required.
• Content clean-up (optional): Old SCORM packages can be converted. There's even tooling for turning HTML-heavy courses into usable formats. Mindset AI has partners to support this if needed.
• Agent creation: Create an agent, configure its tone, personality, and rules (e.g., stick strictly to source material for compliance use cases). You decide how exploratory or conservative it should be.
• Workflow setup: No coding required. You can build simulations, coaching flows, reflection tools, even RFP assistants — using natural language instructions.
• Testing and QA: The platform auto-analyzes what content the agent has access to. You can review, flag, and remove anything that doesn’t belong. You also get test prompts and output scoring to check performance before going live.
• Deployment: Embed it, brand it, and release it. In many cases, all it takes is a couple hours from a content manager, a PM, and a technical lead.

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Go-live in 30 days

Let’s be real: most “30-day” implementation promises are generous with the math. This one isn’t. Here’s what you’re actually looking at if you want to get an AI coach live inside your product:

What you need:

• Content: Wherever it lives now—GDrive, SharePoint, AWS—doesn’t matter. The Mindset AI platform ingests and syncs it automatically. When you update it, your agent updates too.
• One branded AI agent: You set the tone of voice and compliance rules (e.g., “only cite official source content”).
• Some basic workflows: These are built in plain English—no coding or dev time needed. You can configure things like coaching simulations, reflection sessions, or scenario-based support (e.g., sales objection handling or RFP writing).

Who’s Involved:

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And that’s it. If you’re thinking this will slow your roadmap down, it won’t. You can build, test, and ship with minimal effort from your team—so they can focus on delivering other features.

Once live, the agent will supports real users—learners, partners, employees—without dragging your dev team into endless follow-up work.

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What’s next in AI coaching?

Most AI tools just react. You ask a question, it gives an answer. But the next evolution of AI coaching isn’t just about faster search. It’s about becoming a consistent part of the learner’s experience—without adding pressure to your client’s team.

Here are eight predictions about the future of AI agents in general—but in a nutshell, this is where things are heading in EdTech (and what’s already in motion):

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1. Accuracy + Exploration

Your AI coach should be excellent at surfacing the right course, file, or resource—fast. But it should also help users explore related content they didn’t know to ask for. That balance between precision and discovery is key to re-engagement.

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2. Learning + Coaching

Think beyond Q&A. We’re talking about agents that can:

• Guide users through self-assessments
• Trigger reflection sessions or simulations
• Adapt recommendations based on prior interactions

All built from your existing content—not a massive redevelopment effort.

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3. Personalization + Memory

Short-term memory is already possible—like remembering what a user asked earlier in a session. But we’re moving toward long-term memory too. Not “remember everything”—but selectively remember variables that you choose (e.g. scores, preferences, topic history).

This lets you design adaptive experiences that get more helpful the more someone uses your platform.

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4. Engagement on Autopilot

The long-term vision: coaches that don’t wait for users to initiate. Instead, they proactively check in:

• “You didn’t finish that leadership module—want to pick it up?”
• “Based on your last session, here’s something you might find useful.”
• “Your team’s policy training is due next week—ready to practice?”

This isn’t about nagging users. It’s about giving your platform a low-friction way to stay useful—especially in subscription environments where repeat engagement matters.

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So should you launch an AI coach?

If you’re an EdTech, LMS, or training platform provider, the shift is already happening. Your customers are overwhelmed with content. Their users want instant, contextual help. And they’re not getting it from traditional learning systems.

AI coaching absolutely does not replace your product. It makes your content more usable. More relevant. More valuable. It also happens to create:

• A faster way to deliver learner impact
• A reason for customers to come back (and stay subscribed)
• A new monetization model your competitors haven’t figured out yet

And, to reiterate: no, it doesn’t require you to rebuild your platform, rewrite your content, or invest six months of dev time.

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Watch the webinar and book a demo

The webinar is packed with examples, walkthroughs, and lessons learned from launching AI coaches inside real EdTech products. Watch it. Send it to your team. Use it to build your business case.

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Or if you’re already thinking about where this fits into your roadmap, we’re happy to talk through what a pilot could look like.

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