As AI reshapes how work is created and delivered, learning teams have an opportunity to rethink their structure, not just their programs. This session shares an approach that blends learning expertise with embedded subject-matter experts, bringing learning closer to the product.

By hiring people who understand the business at its core, learning teams can build credibility, contribute to cross-functional strategy, and shift from support function to strategic partner. This way, relevance is not claimed. It is intentionally designed.

The measurement debate in L&D never ends, but often because we’re measuring the wrong things. Instead of focusing on learning outputs, we should measure behavioral change, workflow adoption, accountability, revenue influence, and performance acceleration.

In this session, Judith will share practical ways to connect enablement initiatives to business KPIs, partner with Product, Sales, and Leadership, and build credible attribution models that resonate at the board level and show the transition she has led in two companies so far.

No one wants to learn. Accepting this, is your first step towards enablement. It’s no secret that our cousins in Sales Enablement get the budget, ROI is much easier to measure, but L&D can learn a lot from how they approach workforce performance.

In this session, James will be looking at practical steps you can take to move your teams towards Enablement, the impact that will have on the business and the challenges along the way.

Without technology, the three major ways of learning were observing,  experiencing, and human exchange. When computers became more developed, they allowed us to scale learning. But we had to adjust to technology, which led to static learning: few people (learning teams) built content, and many had to consume it.
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With AI and natural language, we have the chance to enable natural learning at scale. In this session, Aki explores how the future of learning will look like and how we, as L&D teams, need to prepare.