44% of core workforce skills are expected to evolve in the coming years. AI is no longer just automating tasks; it is redefining roles, and traditional workforce planning models are falling out of sync with how work is actually performed.
At enterprise scale, hiring alone cannot close the capability gap. AI-native talent commands a steep market premium, so cost-effective transformation depends on baselining and uplifting the workforce you already have. The real question is not just how AI will change roles, but how organizations can measure readiness, redesign work, and build AI-native talent from within.
This webinar lays out a structured approach to that problem. It reframes AI readiness from an abstract concept into a measurable, actionable framework, grounded in task-level visibility into AI impact, role redesign aligned to evolving work, and a continuous, data-driven model that keeps workforce capability aligned with demand.
Key Topics Covered:
How AI impact can be assessed at the task level, beyond traditional job-based analysis
How to identify role overlap, consolidation, and emerging roles to design AI-augmented future-state work
How workforce readiness can be measured at a role-specific level for more precise capability decisions
How these elements come together as future-state role blueprints, productivity gains, and continuous workforce recalibration
A live demonstration of how this is operationalized through the AIQ (AI Quotient) platform
Your Speaker:
Tej Pratap
Product Lead, Prismforce
Who it's for:
Leaders driving workforce transformation in an AI-first setup, looking to move beyond traditional workforce planning into workforce execution, where strategy stays aligned with evolving work, skills, and human-AI collaboration.
