Procure-to-pay (P2P) operations are undergoing a radical evolution. The rise of AI agents and automation promises to overhaul how procurement and finance teams work. But for many organisations, the transformation feels out of reach.
Despite the hype, full-scale automation and intelligent procure-to-pay (P2P) remain elusive. Why? The answer lies in the foundations: poor data quality, fragmented systems, and a lack of orchestration across the P2P lifecycle.
It starts with the basics. Many companies struggle with incomplete, obsolete, or inconsistent supplier and transaction data. Inconsistent versions of supplier records exist across ERPs, procurement suites, and payment systems. Metadata is missing or mismatched. Invoice terms are unclear or misclassified.
Poor data quality means missed early payment discounts, duplicate payments, compliance issues, and friction in supplier relationships. More critically, it limits the effectiveness of AI agents. Without clean, harmonised data, even the most advanced AI struggles to deliver intelligent recommendations.
As a recent McKinsey study notes, “CPOs expect data, analytics, and gen AI to play a core role in every business decision by 2030, but respondents to our survey admit that their data infrastructure is not ready to support this ambition. Twenty-one per cent say their data infrastructure maturity is low, with less than 70 per cent of spend data stored in one place. An additional 30 per cent think they have average levels of data maturity, and even those who have implemented systems to give them a single source of truth for all spend data admit that this data is not cleaned and categorised. These systems may also lack important information from outside the procurement function, such as quality or specification data, or external data from suppliers, customers, and the wider market.” McKinsey, 2024.
Without a strong data foundation, AI efforts will underperform or fail outright.
Most procurement organisations rely on a patchwork of tools. One system manages sourcing, another handles approvals, a third processes invoices, and yet another instructs payments. However, these platforms were rarely designed to communicate with each other.
This fragmentation interrupts the continuity of the P2P journey. Teams must manually reconcile data across multiple systems, often serving the same purpose but acquired through mergers and acquisitions. Critical insights about supplier risk, payment performance, or contract compliance are buried in silos. As a result, decision-making becomes reactive and disconnected.
GEP lists it as the number one challenge in Procure to Pay transformation: “Different business functions in large organisations often work with different processes and tools and maintain their own data. When procurement and accounts payable work in silos, processes are fragmented and there isn’t clarity about which data is accurate. In other words, there isn’t an enterprise-wide single source of truth for all teams. This creates confusion and leads to process inefficiencies and errors.” GEP, 2023.
Without this centralised, single source of the truth, meaningful efforts to adopt automation and intelligence across the P2P journey hit a dead end.
In response, vendors are launching AI agents that solve specific workflow problems, such as automating invoice classification, suggesting payment terms, or flagging anomalies. These are powerful innovations, but their impact is limited when deployed in isolation.
An invoice AI agent may be able to classify documents efficiently. However, if it can’t contextualise against diverse supplier entities, and billing centres or interpret credit terms from contracts, its usefulness is limited. Procurement teams need orchestration and coordination, not isolated automation.
Previse tackles these challenges head-on. The foundations of our technology serve as an operating system for the entire P2P lifecycle from data ingestion to actionable insights, rather than automating individual steps.
The result is end-to-end visibility and control. Procurement and finance teams can finally operate from a single, intelligent source of truth, with confidence in the data and the decisions it drives.
Organisations that deploy Previse’s orchestration layer experience:
In short, they stop “doing automation” and start leveraging the value embedded in their data.
AI in procurement already has huge potential, and the breakneck speed of evolution is expanding that potential exponentially. But it must be built on the right foundations. Point solutions alone won’t fix fragmented systems or broken data and can encourage hallucinations. What’s needed is a coordinated approach: a central intelligence layer that ensures data quality, connects systems, and activates the right AI agents at the right time.
McKinsey highlights that digital enablement has moved from a niche to a “core priority” for 24% of procurement leaders—up from just 2% the year prior McKinsey, 2024. In this new era, orchestration isn’t optional—it’s essential.
Previse delivers exactly that.
It’s time to move beyond silos. It’s time to orchestrate the full P2P lifecycle.
Want to learn more about orchestrating intelligent P2P solutions? Let’s talk.
