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What does AI mean to you?
That’s the question we put to the audience at our recent webinar, AI in L&D: past the hype, into practice. The answers were telling: efficiency, ideas, a team member and intelligent opportunities, to name a few. It’s clear that plenty of people in L&D are already finding their footing with AI.
But hesitancy in the industry remains. Governance concerns and workforce apprehension are, understandably, tough barriers. And even among those already using AI, many feel they’re not getting as much from it as they could.
If this resonates, this webinar recap is for you. Or if you’d rather watch our session back in full, the link is below.
👉 AI in L&D: past the hype, into practice | On demand
The hosts
🎤 Himani Bailey, Director of Presales, Omniplex Learning
🎤 Caitlin Bigsby, Director of Solution Marketing, CYPHER Learning
The current landscape
Everyone’s racing to get started with AI. The numbers show just how widespread rollout is:
- 42% of large enterprises are already deployed.
- 26% of small to medium businesses (SMB) are already invested.
- 40% of enterprise and SMB plan to start soon.
Adoption and impact aren’t the same thing, though. It’s estimated 60 to 80% of AI projects fall flat – most commonly due to limited skills (33%), ethical concerns (23%) and integration or scaling issues (22%).
It’s a pattern playing out in L&D too. “What we’re seeing in learning specifically is that AI gets introduced as a new tool, rather than being part of a workflow,” Himani Bailey said, adding: “It’s almost adopted bottom-up, without any guardrails. Or it’s locked down so tightly that no one ends up using it.”
The gap, as Himani framed it, isn’t down to a lack of ambition or technology, it’s about readiness: “Until organisations address skills, confidence and governance, AI will stay stuck in the experimental stage, no matter how good the tech is.”
👉 Sharpen up your AI skills with our next webinar: Prompt like a pro
The AI maturity journey
Where are you on your AI journey? Are you an early-stage explorer or a seasoned optimiser? According to CYPHER Learning, there are five distinct stages – running from hesitant first steps through to fully-fledged strategy and systems.
1. The reluctant explorer – aware, but not yet convinced
2. The explorer – curious, but lacking direction
3. The experimenter – testing, but missing a framework
4. The integrator – structured, but not fully aligned
5. The optimiser – embedded, optimising and evolving
Want to know exactly where you sit? Read our stages of AI adoption in L&D blog for more.
The 90-day framework
Knowing where you sit on the maturity curve is the starting point. Acting on it is what moves things forward.
Each stage of the AI maturity journey comes with a clear framework – broken down into actions for the 30, 60 and 90-day mark. As Caitlin Bigsby put it, it’s “what you should be doing if your goal is to advance along this pathway, and what you should be considering depending on where you are.”
For the full 90-day framework, whatever stage you’re at, you can access our downloadable resource here.
What really moves organisations forwards?
During the session, we asked attendees: what’s the number one thing holding your organisation back from AI adoption? Governance, sensitive data, regulatory factors and cost all came through as strong concerns.
These are understandable answers – and ones that need to be taken seriously in any AI rollout. But as Caitlin made clear, technology decisions are only part of the picture.
“It’s never about how great the technology is. You can have the best technology in the world, but if you have not aligned your people or your processes behind it, you’re not going to see results. You’re not going to see successful adoption.”
Effective AI rollout needs three things working together: people, processes and technology.
People and processes
Start with education. Share the vision and help your people understand what you’re trying to achieve with AI and why. Where there’s resistance, don’t push past it; listen to the concerns and address them.
Clear policies matter here too. Define how AI should be used, communicate it consistently, and make sure everyone knows what good and safe usage is.
Think carefully about your processes as well; where does AI fit, and how does it change the way work gets done?
Technology
The right technology should manage risk, support growth and keep humans meaningfully in the loop. When evaluating your options, here’s what to ask:
- Data and security: Where does your data go, is it used to train models, who can access it, and how is it governed and retained?
- Integration and architecture: How is AI integrated into the platform (plug-in, partner-powered or embedded), how does it connect to existing workflows?
- Accuracy and oversight: What controls are in place to ensure accuracy, prevent bias and allow administrator oversight of AI-generated content?
- Scalability and roadmap: Does the vendor have a cohesive AI vision, and will the platform evolve to support future use cases and deeper integration?
- Functionality and flexibility: Which AI capabilities are available (e.g., content generation, personalisation), and how configurable are they to your organisation’s needs?
AI in L&D: progress your roadmap
Whatever stage you’re at on your AI journey, Omniplex Learning can help you take the next step. Get in touch to find out more.