This podcast draws on GEP's whitepaper, Leveraging AI to Transform Spend Analytics and it tackles a question procurement teams have been wrestling with for years: how do you turn stagnant data into decisions that actually move the needle?
The conversation traces a shift that's already underway, from reactive dashboards that tell you what happened, to agentic AI systems that don't just analyse data; they act on it. They trigger sourcing activities, surface risks before they become problems, and keep procurement running without waiting for a human to connect the dots. The central idea is this: insight and workflow need to converge. Without that, analytics stays a side project instead of becoming a core business function.
Here's what the numbers say: workflow-embedded analytics accounts for 42% of total benefits available to organisations. That's a significant slice, and it's being left on the table by teams still relying on manual spreadsheet cleanups and backward-looking reports. The shift toward predictive analytics and autonomous automation changes that equation entirely; it moves procurement from "small data" habits to "big data" patterns that directly impact profitability and shareholder value.
And yet, only 4% of procurement decisions currently rely on data and analytics. That gap is jarring. The barriers are real: poor data quality; legacy systems that don't talk to each other; a shortage of domain talent; and cultural resistance that no software purchase can fix on its own. Notably, technology alone accounts for just 9% of captured value. The rest comes from people, process, and how well analytics gets embedded into day-to-day work.
That's the core argument of this podcast: integration isn't a technical problem; it's an organisational one. And the only way to cut through the noise of unstructured data is to make analytics inseparable from operations.
For procurement leaders, this resource offers a practical roadmap: how to clear integration hurdles; how to redesign processes for an AI-driven future; and how to shift your team's role from doing the work to managing how autonomous systems deliver results.
What's Inside:
- Transitioning from reactive dashboards to proactive, natural language queries
- How agentic AI functions as a procurement taskforce: automating sourcing end to end
- Strategies for embedding analytics into daily workflows, so value is captured consistently, not just occasionally
Drive actionable value through AI. Listen to the podcast now.
Frequently asked questions
Traditional analytics tools give you information; agentic AI acts on it. Where a conventional dashboard requires a human to translate findings into next steps, agentic AI can analyse cost drivers and autonomously trigger sourcing pipelines, with no manual handoff required. Multiple AI agents can operate together as a "procurement taskforce": handling cost forecasts; benchmarking internal rates against the market; and identifying sourcing options that would take a human team days to surface. The productivity gains are significant.
The obstacles tend to cluster around three areas: data, systems, and people. Poor data quality and availability is the most common starting point; 57% of professionals cite difficulties integrating various systems as a primary barrier to maintaining the data quality AI needs to function well. Beyond the technical side, there are real challenges around domain talent, governance, and, perhaps most underestimated, cultural resistance to change. These aren't solved by buying better software; they require deliberate change management.
The short answer: AI doesn't replace procurement professionals; it repositions them. The shift is from doing the work manually to managing how autonomous systems do it. That means new skills become essential: reviewing AI-generated actions; setting escalation thresholds; ensuring AI behaviour stays aligned with business priorities and acceptable risk levels. And because talent and workflow integration account for the vast majority of business value, not the technology itself, human domain expertise remains the essential foundation. AI needs direction; procurement professionals provide it.