Reskilling procurement teams for the age of agentic AI

Organisational incentives are a hidden obstacle to AI adoption The barriers to the adoption of AI in procurement and supply chain are not only technical. Data suggests that the most intractable challenge of all, in fact, is human. Executives dramatically overestimate how excited their workforces are about embracing the technology: three-quarters believe that their employees are enthusiastic about AI, but only 31% of workers themselves agree¹, thanks to a combination of poor user experience, a lack of clear governance guidelines around the usage of tools and an underlying mistrust of AI.² The gap matters because frontline acceptance—not algorithmic capability—is often the real constraint on implementation. Resistance does not necessarily decline with seniority, nor is it always rational. Middle managers, whose authority is often derived from the headcount or budget of the team they manage, understandably view automation with suspicion because it reduces both. Firms must redesign incentive structures alongside AI systems, rewarding managers and employees alike for outcomes rather than empire.

The entry-level gap: automation removes the training ground for tomorrow's talent Procurement teams traditionally develop future leaders by putting junior staff to work on the fundamentals: tracking purchase orders, processing invoices, categorising spend. But these are precisely the tasks that AI is now absorbing fastest and which are now substantially automated at the majority of firms.³ The move to autonomy risks removing the entry point through which human procurement capability is built. As one executive observed, if senior people spend their days interpreting AI outputs but no juniors ever learn the underlying logic, the talent pipeline will eventually run dry. Of course, firms must redesign the apprenticeship model for an era in which machines handle execution and ensure that their future leaders acquire the technical skills to succeed in this environment. But they must also ensure that new employees gain a thorough understanding of the domain they will work in. 

Beyond efficiency: AI as a discovery engine So far most firms use AI to execute familiar procurement tasks like chasing invoices faster. The most innovative ones, however, are using the technology to do things that were previously impossible: exploring alternative materials or stress-testing supply chains against scenarios that would take humans weeks to model, for example. Used expansively in this way, AI can reposition procurement from a cost saver to a contributor to product strategy and competitive resilience. The firms that limit AI to efficiency will capture incremental gains. Those that use it for discovery may reshape their industries.