NOMINATION HIGHLIGHTS

Sunkanmi “Sukky” Agbomeji is being nominated for his pioneering contributions to AI‑enabled learning and skill development, grounded in real‑world enterprise leadership and a deep understanding of how work, skills, and relevance are changing in the age of AI.

Sukky is a Senior Director at EY‑Parthenon, where he leads teams across AI, advanced analytics, and M&A strategy for healthcare and life sciences organizations. In this role, he advises C‑suite leaders on high‑stakes, AI‑enabled decisions that frequently involve workforce transformation, capability redesign, and post‑merger integration, often in environments where roles are being automated and traditional skill sets are rapidly aging. This front‑line exposure gives him a rare, practical view into how learning and reskilling succeed or fail at scale.

Beyond enterprise leadership, Sukky is the award‑winning author of Uncomfortably Pivot, a book that reframes career stability not as permanence, but as continuous adaptation. Drawing from his journey from clinician to entrepreneur to global analytics leader, the book outlines practical principles for navigating disruption and building relevance in an AI‑shaped economy. His work challenges the common notion that more knowledge alone is the answer, instead emphasizing judgment, adaptability, and the ability to unlearn.

As part of this broader mission, Sukky founded Caippy, an AI career‑readiness platform that operationalizes his learning philosophy. Caippy helps professionals assess displacement risk, identify which skills matter now, and translate learning into credible market signals. While Caippy is not the subject of this nomination, it represents one applied extension of Sukky’s larger contribution to learning and skill development in the AI era.

What distinguishes Sukky’s impact is not just technological innovation, but behavioral change. His work moves individuals from reactive upskilling to intentional, forward‑looking learning strategy, equipping them to continuously reassess, update, and future‑proof their capabilities. In a time of accelerating AI adoption and workforce volatility, his approach offers a human‑centered, scalable blueprint for learning that directly meets the moment.