Reinventing Career Development

This may be the most underappreciated issue in talent management. Historically, careers have been relatively predictable:

Entry-level role → increasing responsibility → management → leadership.

But what happens when AI automates many of the tasks that employees traditionally performed to learn their profession? How does a young financial analyst develop judgment if AI performs much of the initial analysis? How does a consultant learn problem-solving if AI produces the first draft? How does a manager learn to manage if organizations eliminate layers of management?

This creates what I would call a potential experience-development crisis. Organizations will have to deliberately create new developmental pathways through:

• Internal gigs
• Project-based assignments
• Rotational experiences
• Human mentoring
• Simulations
• AI-assisted practice
• Cross-functional work
• Deliberately designed stretch experiences

LinkedIn's workplace learning research already points toward the convergence of learning, leadership development, career development, internal mobility, and AI adoption. Organizations with stronger career-development practices appear better positioned for AI transformation, while AI upskilling increasingly varies by role rather than following a one-size-fits-all model. Those of us with backgrounds in learning see this as a major opportunity: Move beyond “Head of Learning” toward “Architect of Talent Capability and Career Systems.”