Research Digested: L&D in the Workforce Transformation Age: What Learning Leaders Need to Know, Obrizum

About this research

Obrizum surveyed 302 senior L&D decision-makers (152 in the UK and 150 in the US) (p.3) in large enterprises (5,000+ employees; $1bn+ revenue).

Key findings

  • 93% say workforce transformation is a top three priority and 55% rank it as their top priority
  • 67% are not “very confident” their learning data can identify capability and knowledge gaps
  • 80% agree AI is accelerating role change and skills demand
  • 75% say they struggle to evidence the ROI of learning in business terms
  • Learning is expected to deliver across multiple business outcomes – productivity (45%), customer outcomes (46%) and AI readiness (43%). The research suggests learning is being stretched across competing priorities, with no single dominant objective
  • 78% say the pace of transformation is creating noticeable change fatigue
  • 85% (US) and 68% (UK) say linear course-based approaches are too slow
  • Only 44% are “very confident” their workforce has the capability to deliver transformation priorities
  • 70% say it takes three or more months to deploy a capability programme at scale and only 30% can do so in one to two months
  • Barriers include data/privacy (35%), time to build training (34%), prioritisation (34%), ROI proof (33%)
  • 8 in 10 expect to invest more in organisation-specific learning
  • 66% are not “very satisfied” with their ability to personalise learning while maintaining standards
  • Only around one-third are “very satisfied” with capability measurement overall.

What to act on

Organisations need to shift learning from content delivery to capability measurement. With 67% lacking confidence in their learning data and only 44% confident in workforce capability, the priority is to build systems that show whether people can perform – not just complete training. This means defining clear capability standards for critical roles and measuring against them consistently.

With 70% taking more than three months to deploy programmes while AI accelerates role change, current delivery models are structurally too slow. Organisations should prioritise smaller, faster pilots focused on high-risk or high-impact roles, enabling quicker iteration and evidence generation before scaling.

The research also shows the need to develop organisation specific content including capturing and operationalising their own expertise. This is particularly important in regulated environments where context-specific knowledge and auditability matter.

Finally, organisations must address structural fragmentation in L&D. Barriers are distributed across data, governance, prioritisation, and resources, meaning isolated fixes will fail. A coordinated approach is required – aligning data, delivery models, and measurement – to reduce friction and enable learning to keep pace with transformation demands.

Read the report https://obrizum.com/resources/ld-in-the-workforce-transformation-age/