Skilling gap in AI adoption
While India has a vast talent pool eager to learn, Alpana highlighted a key challenge: the specialized skills required for advanced AI applications remain scarce. According to our latest GenAI report, "How much productivity can GenAI unlock in India?" only 36% of Indian enterprises have allocated budgets for GenAI, with another 24% still in the experimental phase. In contrast, organizations in the US and UK are not only upskilling their existing workforce but also creating entirely new roles to integrate AI into business operations. Meanwhile, Japan is taking a government-backed, steady approach to AI readiness, though a shortage of AI talent remains a significant hurdle.
Cultural factors also play a role in AI adoption. Organizations must navigate the challenge of integrating new technologies into traditional business environments. More importantly, AI skilling is not just an HR or IT concern—it is a company-wide priority that demands a holistic approach.
From experimentation to implementation
Thirukkumaran Nagarajan emphasized that organizations are shifting from AI experimentation to real deployment. Business leaders now demand tangible results, moving beyond pilots to scaled AI solutions. As AI integration accelerates, workforce transformation becomes a necessity.
A major challenge is the readiness of employees to adapt to AI-driven workflows. Thirukkumaran Nagarajan noted that AI literacy is critical, with organizations aiming for comprehensive AI education by 2026. Without a structured change management program, the true potential of AI remains untapped. IBM, for instance, has implemented mandatory AI training across all functions—from legal and procurement to HR and development—ensuring employees at all levels understand AI fundamentals.
The future of work in an AI-driven world
The impact of AI extends beyond workforce upskilling; it transforms business models and operational efficiencies. With AI-driven digital labor executing tasks at scale and near-perfect accuracy, organizations must rethink job roles and processes. Thirukkumaran Nagarajan reiterated that successful AI adoption depends more on people than technology.
The path forward requires a collective effort across business functions, leadership, and employees. By embracing a structured approach to AI skilling, organizations can future-proof their workforce and unlock AI’s full potential.
Closing thoughts
The discussion at EY Convene reinforced that AI skilling is not an option but a necessity. Organizations that invest in upskilling and change management today will be the ones leading the AI-driven transformation of tomorrow.