e.learning age

With every week bringing a new AI tool or feature to the market, leaders are increasingly looking at their AI adoption and return on investment. Nobody can disagree with the potential of AI, after all, the market is projected to grow from $347 billion USD in 2026 to $1.68 trillion USD by 2031. Yet 93% of global AI and data leaders identify human factors as the primary barrier to AI adoption in their organisations.

Every week there's a new AI model, a new AI capability, and ten more LinkedIn posts about 'AI transformation'. Meanwhile, learning leaders are stuck between executive pressure to "do something with AI" and the very real fear of wasting time and budget on the wrong thing. So, we went straight to the people who are building this future right now.

Learning and Development is entering 2026 with no shortage of ideas, tools, or opinions. AI is advancing at speed. Talks of skills frameworks are everywhere. Collaboration is widely championed. And yet, many L&D teams still feel a familiar tension: more need and more potential than ever, but more pressure too. The challenge isn’t knowing what’s possible. It’s knowing what actually matters now. In 2026, success in L&D won’t come from chasing the latest trend.

In the world of learning technology, innovation is often associated with feature-heavy platforms and flashy interactivity. But throughout my career, I have seen firsthand how unnecessary complexity creates barriers to learning. Platforms that try to do everything often struggle to do anything well. Our team decided that we would clear a different path. We created Build Capable XCL, a patent-pending tool that simplifies the way learning is delivered, tracked, and analyzed.

Employee development, continuous learning, and career ownership are poised to be the #1 priority for HR teams in 2026. Employees are hungry for learning and development, with 75% of workers saying they’d stay longer at their current jobs if offered development opportunities. Yet, organizational hierarchies are flattening and the road to promotions and title changes has never been muddier… The future of work can no longer be defined by job titles, fixed career ladders, or static skill sets.

AI image-generation tools can create impressive learning visuals in seconds. But without thoughtful prompting, they tend to replicate and even amplify the same narrow visual defaults we’ve been trying to move past – white, male, young, slim, and able-bodied. That’s not just a technical limitation. It’s a problem of representation – and it has real implications for how people connect with your training content.

In this episode of Totara talks Talent, Totara explores how organisations can create digital learning experiences that are accessible, inclusive, and designed for every learner. “Accessibility is a people problem, not a technology problem.” Totara’s accessibility experts discuss practical steps for building learning that meets diverse user needs, the importance of universal design principles, and how small improvements can make a big impact.

The pace of change across workplace learning has shifted from steady evolution to rapid transformation. Learning professionals are no longer preparing for a distant future – they’re operating in the middle of it. New technology, rising employee expectations, and increasing pressure on organisations to demonstrate measurable impact are all accelerating a reinvention of how learning is designed, delivered, and valued.

Key takeaways: AI use is widespread but unstructured – 8 in 10 employees use AI regularly, yet most don’t share that use with peers or managers due to unclear policies and guidance. Culture and training are not keeping up – Despite growing top-down encouragement, most organisations lack defined expectations, role-based learning, and manager support.

New research from Cornerstone highlights an AI income gap with higher earners far more likely to receive structured training compared to lower income earners. 80% of UK employees have used AI; 63% using it weekly or more.1 81% of employees that use AI to support their work say they don’t always disclose their use to managers or colleagues.2 Only 33% of employees say they are often or always encouraged to use AI at work.