Prediction #3: Automated metadata generation will emerge as a strategic capability—and potentially a standalone business
As interoperable learning platforms scale, metadata becomes a bottleneck. In 2026, AI-generated metadata will emerge as core learning infrastructure, accelerating discoverability and personalization while increasing demand for validation, standards alignment, and trustworthy “Content Metadata as a Service.”
Prediction #2: Data quality tooling for xAPI will become a priority as learning technologies increasingly share data
As more tools and organizations share their xAPI data around, the question of data quality becomes (even more) urgent. A malformed statement, a non-conformant xAPI Profile implementation, or low-fidelity activity data no longer “just” create local problems; now flawed data can propagate through the network, degrading analytics and undermining trust across the digital landscape.