As organisations prepare for 2026, the skills landscape is shifting. Business and technology are both evolving at rapid rates. The future is about how effectively humans, machines and systems interact to create business value.
Talent intelligence as a lead indicator
Predictive capability is central to staying ahead of skill crises. Roy emphasised the importance of tracking lead indicators such as attrition patterns, vacancy ageing and behavioural signals.
At CEAT, this translated into a six-month effort to build a predictive attrition model using AI. By combining static and dynamic data, analysing chatbot interactions, and integrating insights from internal engagement surveys, the organisation developed early-warning red flags.
Crucially, the AI initiative was anchored in a real business problem. This avoided the common trap of adopting platforms without a clear value thesis. Technology was piloted against live workforce challenges, ensuring both credibility and capability building within HR teams.
Key highlights from our conversation:
- AI is no longer a function. It is embedded across roles, requiring universal digital fluency.
- Skill strategies must shift from static taxonomies to work-led, outcome-driven capability building.
- Predictive talent intelligence should focus on lead indicators, not just lag outcomes.
- Low AI literacy within HR and trust deficits around AI remain major barriers.
- Platform adoption does not equal value creation. ROI depends on orchestrating technology with talent capability.
- HR maturity in 2026 will be defined by how quickly skills are converted into execution advantage.