Rethinking Your L&D Tech Stack
The last time you had a question at work, what did you do? Did you ask AI? Go to an intranet? Maybe even Google it?
Whatever you did, I’d bet you didn’t go to your LMS.
Employees rarely see the LMS as their go-to source of information. And only about half of L&D practitioners expect it to remain the backbone of their tech stack in the next few years, according to Synthesia’s AI in L&D 2026 report.
That’s a problem, especially when it’s one of the most significant investments in the L&D budget.
When people can get answers instantly, in the flow of work, they stop going out of their way to use separate systems.
AI is now the fastest way to get an answer, right where work is happening. That should change how you think about (and frankly invest in) your tech stack.
What’s really in your L&D tech stack?
A tech stack is the collection of tools and systems your organization uses. But it also refers to how data flows (or doesn’t), and how employees use them.
When I talk about an L&D “tech stack,” I’m referring to the ecosystem across an organization where people share and apply knowledge.
This includes tools and systems for:
- Content management and delivery
The usual suspects: Learning Management Systems (LMS) or Learning Experience Platforms (LXP) and internal learning portals - Content creation
Things like: eLearning authoring tools or AI video platforms - Third-party content and programs
You know, the massive subscription libraries or cohort-based learning platforms - Work systems
Everything from AI tools to survey and feedback platforms, intranets, shared workspaces, and videoconferencing
If you're assessing a specific tool or system, I've linked guides above where we have vetted recommendations. One caveat: most enterprise pricing is negotiated, so treat any figures you see as directional.
Learning shows up across all of these in an organization. That’s what makes the tech stack harder to think about. It’s how all of these systems work together.
Mapping this ecosystem is only the first step. You need to know what you have, how people use it, and where they don’t. Where the systems are disconnected.
That’s where L&D has the greatest opportunity with its tech stack: to find ways to work better within systems that employees are already using.
What AI is revealing about your tech stack
Every day, I hear about a new AI tool (I only wish that was an exaggeration), and I work at an AI company.
What I'm seeing is L&D decision-makers being overwhelmed with AI tools, many of which promise to solve problems we didn't know we had. This wave has sent teams scrambling to partner with their procurement teams to understand and vet these tools, either as wholesale replacements or additions to their tech stacks.
This is understandable. For years, we've been stuck with perfunctory systems that are limited by delivery formats like SCORM. AI is genuinely exciting in its potential to liberate us from those constraints. Just don't get distracted by the shiny new tools.
A word of caution. No tool is going to solve the problems in your L&D team without your expertise. If you're struggling to measure training, an AI tool isn't going to fix that for you. In fact, I've seen the opposite. Teams are unlocking faster content creation and delivery, but struggling to catch up with measurement. I call this a readiness gap. If we create content faster and faster, but are still unable to determine if a training is changing behavior or driving the desired outcome, then we're widening the readiness gap.
The second thing to watch: a lot of what's being marketed as AI is SaaS vendors bolting new features onto old products without fixing the underlying issues (in the product or in your learning). The AI features being added to existing tools deserve the same scrutiny as anything new. A tool that can't keep pace with how AI is changing how instructional designers work or how L&D teams are implementing AI in their strategy is a liability.
Some food for thought as you contemplate adding anything new.
How to assess your tech stack
It might seem counterintuitive, but to assess your tech stack, I want you to go talk to people. IT, HR business partners, department leads — anyone who can narrate how knowledge transfer is happening on a daily basis.
Be curious. Ask where people are going when they have a question. Are they searching using an AI tool? Messaging a colleague? Where is the tacit knowledge documented?
I want you to start there because you likely have data readily available about the tools you own. You can go into an LMS and see how many active users there are on a daily basis. But you can't go into an LMS to find out that the only time people are logging in is when they've been assigned eLearning.
You need this context to answer the following questions about every tool and system in your stack:
- How is it being used?
Follow ups: Why is it being used? How often? - How hard is it to use?
Follow ups: How many steps does it take to get what you need? Where do people drop off? What workarounds have appeared? - What value are you driving from it?
Follow ups: What does it cost to run? What problem is it solving? If you removed it, what would actually break?
You're evaluating the use, friction, and value. Three things that will help you make a data-informed decision.
Decide what stays, what changes, and what goes
You've done the assessment, and now it's time to make some tough calls. Here's how I think about it:
- Keep it if it's working.
- Repurpose it when it still has value, just not in the current use case.
- Remove it when the cost and complexity outweigh the benefits.
A few caveats.
It is rarely simple to remove an enterprise tool or system. It usually involves cancelling a contract or giving notice, either of which may lead to losses. Plus there's the change to manage. Before moving forward with a decision, speak to your procurement team and brainstorm any downstream impacts of removal: from migrating content to notifying teams and training them on new tools.
Second, if you're considering replacing a tool (notice how I didn't list that as an option), ask yourself whether you need a tool at all to accomplish your goal. You may find there are other reasons to add to your tech stack that have nothing to do with a direct swap. If your LMS isn't driving value, consider whether adding a new LMS is going to solve that problem.
The tool is probably not the root cause.
What to do with the capacity you create
When you repurpose or remove something from your tech stack, the upside is likely freed up capacity and resources. The question is what to do with that time or money.
This is where most teams default to adding something new. Instead, focus on how you could take something you've already created and deliver it better. How can you reduce the friction between the employee and the learning experience?
You're competing with AI for attention.
So here's what you're going to do about it. Take one piece of content and make it as easy as possible for someone to access when they need it. The good news is, you may already have some of this data from your tech stack analysis.
Here are five examples of how to do that.
The bottom line
Your employees are learning, with or without your L&D tech stack.
That's why whatever decisions you make about tools or systems are fundamentally about measurement. You know what you're spending, but do you know what you're getting?
You can calculate the per-employee cost of an LMS license, but can you show that a course completion inside the platform led to behavioral change tied to business impact? That's the harder question, and the more important one.
If you're accountable for the L&D budget, you have to justify the investments you're making. And if someone comes to you with an AI tool that promises miracles, like reliably tying an eLearning to a business KPI with a click of a button, ask them to show you the methodology.
Be sure to connect whatever decisions you make to your strategy.
Amy Vidor, PhD is a Learning & Development Evangelist at Synthesia, where she researches learning trends and helps organizations apply AI at scale. With 15 years of experience, she has advised companies, governments, and universities on skills.
