How AI-powered learning platforms are changing the role of L&D teams

Rapidly changing workplace skills are increasing pressure on learning and development (L&D) teams. LinkedIn's 2025 Workplace Learning Report found that 49% of learning and talent development professionals said their executives were concerned that employees lacked the skills needed to execute business strategy. AI-powered learning platforms may reduce some operational work, giving teams more time to focus on learning quality and skills planning.

From course production to personalised pathways

Depending on its capabilities, an AI-enabled learning management system can use existing material to suggest course structures, learning objectives, quizzes, assessments, and skills mappings. It may also recommend more relevant resources or pathways based on a learner's role, skills, and activity. A new employee could receive foundational material, for example, while an experienced colleague is directed to more advanced practice.

Assessment results can also be connected to the next stage of learning: strong performance may lead to advanced material, while gaps can prompt additional practice. The quality of this personalisation depends on the available data and system design, however, so it should not be treated as a guaranteed outcome.

Less repetitive administration, better-informed decisions

Updating content, building question banks, translating material, assigning courses, and tracking completion can consume substantial time at scale. Selective automation may free capacity for analysing skills gaps and working with business leaders. Participation, assessment, and skills data can help identify areas requiring support, although interpreting those signals still requires organisational context.

LinkedIn reported that 71% of L&D professionals surveyed in 2025 were exploring, experimenting with, or integrating these technologies into their work. That indicates broad interest rather than proving that every implementation succeeds. Strategic questions—what skills the organisation will need and how learning should connect with recruitment, internal mobility, and leadership development—continue to depend on human judgment.

Human oversight remains essential

AI-generated material can contain inaccuracies, miss organisational context, or be unsuitable for its audience. Courses, assessments, recommendations, and uses of sensitive information therefore need clear review processes. A practical approach is to apply AI to selected repetitive tasks while keeping specialists responsible for important decisions, policy alignment, and the final quality of learning.