AI report says L&D must move beyond content creation
Based on interviews with senior L&D leaders, Eglė Vinauskaitė and Donald H Taylor outline three new operating models for workplace learning and argue AI is accelerating the decline of content-led L&D functions.
A new report from Eglė Vinauskaitė and Donald H Taylor argues that AI is pushing workplace learning teams to rethink their purpose, moving beyond content production towards organisational performance and capability strategy.
‘The Transformation Triangle’, the latest in the AI in L&D research series, is based on interviews with senior L&D leaders from around 20 organisations across sectors including professional services, technology and consumer goods. The report says AI has accelerated a shift already underway: the decline of content creation as L&D’s defining value proposition.
The authors argue that AI tools can now generate learning content quickly, cheaply and at ‘good enough’ quality, while business units increasingly create and share their own resources without relying on central learning teams. That weakens the traditional model of L&D built around producing and distributing content.
Instead, the report sets out three operating models for modern L&D teams, described as the ‘Transformation Triangle’: Skills Authority, Enablement Partner and Adaptation Engine.
- Skills Authority positions L&D around workforce capability data, identifying gaps and linking development to business outcomes and career progression.
- Enablement Partner focuses on making expertise inside the organisation more visible and easier to share, helping knowledge move between teams and surfacing practical know-how from employees closest to the work.
- Adaptation Engine treats performance as a systems issue. In this model, L&D diagnoses operational barriers to performance and works across workflows, incentives and organisational structures, rather than defaulting to training interventions.
The report says all three models move L&D away from reactive training delivery towards what the authors describe as ‘anticipatory signal reading’, where functions identify capability, expertise or performance gaps before business units formally raise them.
The research also found that learning becomes more effective when development carries visible consequences for employees, such as progression opportunities, performance expectations or professional standing. In those environments, employees are more likely to seek out development without prompting from L&D.
The report identifies three barriers to transformation: structural drag, cultural drag and capability drag. These include organisations continuing to see L&D primarily as a training provider, teams organised around content production and capability gaps within L&D itself.
Vinauskaitė and Taylor conclude that the future of L&D depends less on producing content and more on helping organisations improve performance, adapt to change and make expertise visible across the business.