Beyond Productivity: Using Procurement AI toMake Better Commercial Decisions

Most procurement AI initiatives have focused on doing existing work faster, reducing cycle times, automating repetitive tasks and improving team productivity. But the bigger opportunity is using AI to help procurement make better decisions across cost, supplier performance and risk.

This webinar explores how procurement can move beyond efficiency gains and use specialist AI to connect fragmented internal and external data, uncover opportunities that may otherwise be missed, and turn information into actionable commercial decisions. Through real-world case studies, we’ll examine how AI can help teams optimise supplier bases, strengthen negotiations, identify emerging supplier risks and give procurement leaders a clearer view of where attention and action are needed.

The discussion will also tackle the practical questions procurement leaders are facing as AI scales: Can you trust the underlying data? How do you move from alerts and dashboards to action? Where should human judgement remain? And how do you demonstrate that AI is creating measurable procurement value rather than simply saving time?

Key Takeaways

• Move beyond the productivity trap: Understand where AI can create commercial value rather than simply automate existing procurement activity.
• Turn fragmented data into decisions: See how structured and unstructured supplier, sourcing, performance and market data can be connected to identify opportunities and risks.
• Optimise supplier decisions: Explore how AI can support supplier selection, supplier-base optimisation and negotiations by considering cost, performance and risk together.
• Move from risk monitoring to action: Learn how external risk signals can be combined with internal supplier data and audit activity to highlight where procurement intervention is required.
• Give leaders a clearer view of the procurement landscape: Explore how AI can help leaders interrogate procurement data across suppliers, categories, contracts and performance to identify where teams should focus.
• Prove the value of AI: Consider the measures that matter beyond hours saved — including savings, risk avoided, supplier performance, negotiation outcomes and improved decision-making.