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The Future of Leadership Development: AI-Driven Manager Enablement
Learning technology has been evolving over the last few years to improve learning outcomes and help L&D be more effective.
The pace of change was evident in the offerings showcased by exhibitors at the 2026 Learning Technologies Conference, Europe’s largest workplace learning event, held in late April in London. A sister HR Technology show ran alongside the conference.
Table of Contents
- How AI Adds Value to Learning Technology
- Learning Platforms Approach AI From Different Directions
- AI and the Compliance Challenge
- Supporting the Skills-Based Organization
- Skills Data as Part of Workforce Intelligence
- New Opportunities for Analytics
- Gaps That Learning Vendors Still Need to Address
How AI Adds Value to Learning Technology
AI was everywhere at the 2025 event. Unsurprisingly, this was true for the 2026 exhibition too, but it felt as if the emphasis had changed. Individual learning tech vendors have been working to improve their products. But for customers, the crux is how this translates into tangible value and whether it makes a difference for learners.
“There’s a drive within buy-side organizations to become more AI-led or AI-powered. We heard from learning leaders in the conference that focusing on this can help unlock technology budget and investment,” said Kate Graham, global insights director at Cornerstone. But it’s difficult for buyers to evaluate how effective AI-driven solutions are, or whether AI is more there to tick a box rather than being embedded into the product, she added.
"18 months ago was the peak of the AI hype cycle. Now we're getting more into 'what is AI actually going to do?'” said Phillip Miller, CEO of adaptive learning platform Skillwell. “Learning providers have to figure out how they incorporate AI into a product in a way that makes it significantly better.” Skillwell, for example, uses generative AI to build personalized simulation training faster.
Learning and digital workplace consultant Simon Thompson has attended the exhibition for years and was disappointed not to see more examples of practical and effective use of AI from vendors. “It feels like we are just seeing more variations on chatbot interfaces or ‘magic’ AI buttons,” he said.
Learning Platforms Approach AI From Different Directions
“While some vendors are using their own AI models, others are creating products that will act as an interface to mainstream LLMs like ChatGPT or Claude, with sets of platform-level rules and organizational context,” observed Thompson.
Other providers focused on agentic AI. That included learning platform Zensai, which recently launched a “Human Success Agent” integrated into Microsoft’s Agent 365 agent orchestration offering. Now it wasn't only about the AI capabilities of your platform, but how it interoperates with other agents, said Andrew Roberts, Zensai’s chief product officer.
The rise of agents within learning technologies poses some intriguing questions, many of which may influence future development. “How are organizations training their agents, for example?” said Graham. “Agents aren't going to click through an E-learning course, but what inputs are you giving them to consume in order to train them? And how is that governed?”
AI and the Compliance Challenge
Compliance is a key box that must be ticked for all learning and HR tech, but regulatory compliance and AI innovation aren't necessarily aligned.
Everyone is racing so fast to get the competitive edge with AI and agents that they overlook safety and trust issues, warned Paul Conneally, CEO of Slick+. Consequently, risk averse organizations may hesitate in advancing some AI features.
The compliance question may also be preventing larger AI companies such as Anthropic and OpenAI from muscling in on the learning tech space. For example, when Anthropic released a legal plug-in for Claude in February, share prices for companies in the legal AI space fell sharply. But so far, no similar threat to learning tech has emerged.
While everybody wants to build solutions using AI, no one wants to maintain them, Graham said. “There’s a reason why specialist software solutions exist in HR and learning,” she said. “Payroll and people data are complex and the maintenance required around that sprawl can escalate very quickly. They need compliance, frameworks and governance.”
Supporting the Skills-Based Organization
One of the most exciting directions for learning technology providers using AI is to support skills management and produce accurate skills data, an area that has received more attention due to the urgent need to upskill workforces around digital technologies and AI.
“Until recently, the ideal of the skills-based organization has yet to be fully realized, but new technology can change that,” said Graham.
For example, at Skillwell, skills data drives real-time, adaptive learning. "We generate a lot of skills data, and people use that in different ways," said Miller, such as identifying gaps or determining whether levels of compliance have been reached. But it also affects the learning experience, he said.
"Skills data doesn't just become a report, but feeds back into our machine learning algorithms to create a learning path and content that upskills people on exactly where they are deficient," said Miller.
Skills Data as Part of Workforce Intelligence
Skills data also plays a part in wider business decision-making. Graham cited the example of a company operating a new division in a country and wanting to know how it should be staffed. “Most companies are not evaluating decisions like that from a skills and capability perspective, because it has been too difficult to gain a comprehensive view of that data,” she said.
Skills data assumes more value and supports areas such as workforce planning combined with other data sets. Cornerstone already uses external market data to produce insights but integrates with data from internal enterprise platforms, too — not just other HR systems, but systems of work to build a complete picture.
“If you want to truly understand what your workforce is doing and the skills they've got, then you need to be able to combine and analyze the data from all those different systems,” Graham said. Learning that someone finished a course, combined with other data, provides insights into whether employees are ready to apply their learning to their work — and whether learning affects their performance on the job.
Cornerstone is focusing on this area, planning to launch workforce intelligence features to support strategic decision-making. That will provide a real-time view of what people can do, driven by continuous signals from what they're learning, what they're working on and what they're ready for, Graham said.
New Opportunities for Analytics
“With the amount of data being generated, there are clearly new ways to capture and capitalize on the analytics,” said Thompson. “The opportunity to bridge gaps between systems is going to be very tempting to employers.”
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Zensai is another learning provider using AI to synthesize data from other sources to both improve learning and create new ways to report on success. A client call could be recorded and transcribed, and a learner could now get coaching insights based on how they spoke on that call and interacted with their customer, Roberts said.
Zensai has also combined learning, engagement and performance data to create one metric for HR and learning leaders to use for the CEO to support people-related decision-making. “We now have a measure which is behavioral, which gives CHROs a seat at the table,” said Roberts.
Gaps That Learning Vendors Still Need to Address
Despite all the excitement in the learning space, fundamental issues remain and learners still have unmet needs.
“It is exciting to see a course being spun up in front of you,” said Thompson. “But it worries me that the cost of getting things wrong is greater than ever.” Not enough attention was being paid to understand users, manage content or measure whether training works.
"Generally, LMSs are very good for knowledge-based workers but not as good for frontline workers,” said Conneally, adding that deskless workers are largely underserved when it comes to receiving necessary operational knowledge and appropriate training for their environment, context and reality.
Overall, the impression from Learning Technologies 2026 is the space is still very much in transition. AI’s influence is unmistakable, with vendors increasingly delivering intelligent solutions that offer greater value through capabilities such as adaptive learning, workforce intelligence and support for skills-based organizations. At the same time, new competitive threats from major AI companies may emerge and foundational requirements such as robust compliance support remain critical. Meanwhile, long-standing challenges around content management and frontline workforce support have yet to be addressed.
Editor's Note: How else is learning and development evolving?
- L&D Needs a Mission and a Vision Statement. Here's How to Build One — Organizational mission and vision statements create alignment and focus across a company. L&D teams can reap the same benefits when they draft their own.
- Learning and Development Needs a Reset — We need to evolve L&D from telling and teaching, to activating new skills, capabilities, habits and behaviors.
- Workers Need More Than Technical Training to Succeed With AI — Unlocking the power of AI requires more than tech knowledge, and companies that invest in L&D for AI may be one step ahead of the rest.