Document processing
18 min read
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Jul 29, 2025
Casimir Rajnerowicz
Content Creator
Procurement might sound like back-office busywork, but it drives everything from inventory levels on a retail shelf to whether an aircraft manufacturer has enough rivets on hand. Yet the workflows behind procurement are often archaic — spreadsheets circulate, approval emails languish in inboxes, and invoice matching becomes a detective game. The growing interest in procurement software reflects a broader shift in how organisations manage suppliers and spending. Corporate buyers are no longer content with paper trails and disjointed systems; they want speed, reliability and transparency.
At the same time, artificial intelligence (AI) has moved from hype to practical tools that can read contracts, classify spend, and even flag supplier risks before a disruption hits. Does that mean robots are coming for your procurement job? Hardly. It simply means the procurement function is evolving from tactical purchasing to strategic value creation.
This guide cuts through the jargon and wishful thinking. It explains what procurement software actually does, where AI fits in, and how to distinguish between predictive analytics and generative models. You’ll learn about:
The core types of procurement — direct vs. indirect, goods vs. services — and how they drive different requirements
The step-by-step procurement process and the modules included in modern procurement software
Current survey data on AI adoption in procurement and where AI delivers real value — spend analytics, sourcing, contract management, supplier risk — and where human judgment remains essential
A comparison of leading procurement software platforms
How a platform like V7 Go can be adapted for procurement tasks, even though it wasn’t designed as a traditional source-to-pay suite
By the end of this article you’ll have a clear understanding of what procurement software is, how AI can accelerate it, and whether the next step for your organisation involves a procurement suite, a custom automation, or both.
What is procurement software?
Procurement refers to the acquisition of goods and services. In practice, it encompasses everything from ordering laptop chargers for your colleagues to negotiating multi-year supply contracts. There are two broad categories:
Direct procurement involves sourcing goods and services that are directly incorporated into the company’s finished products. It includes raw materials, components and specialized services such as hiring research consultants for product development — a car maker buying steel or a pharmaceutical firm contracting R&D support are typical examples.
Indirect procurement covers goods and services that support day-to-day operations but do not become part of the final product. Examples include office supplies, maintenance services, marketing campaigns, IT subscriptions, consulting and other expenses that keep the business running.
The procurement mix can also be viewed through the lens of goods versus services. Goods procurement deals with tangible items — from office supplies and raw materials to software licenses — while services procurement covers intangibles like cleaning, consulting, contracting and other people-based services. Any purchase can fall under both direct/indirect and goods/services categories.
The procurement process
Though terminology varies, most procurement workflows follow a sequence:
Need identification: A department recognises a requirement, whether for materials, equipment or services.
Supplier sourcing and evaluation: The procurement team researches potential suppliers, requests quotes or proposals, and assesses them based on price, quality, delivery times and risk.
Negotiation and contracting: Terms are negotiated and codified in a contract, including price, delivery schedules and service-level agreements.
Ordering and fulfilment: Purchase orders are created and approved, goods or services are delivered, and receipts are logged.
Invoice verification and payment: Invoices are matched to purchase orders and receipts before payment.
Supplier performance and relationship management: Suppliers are evaluated regularly to assess quality, reliability and compliance, and relationships are managed over time.
Manual execution of these steps is labour-intensive and prone to errors. Paper invoices get lost, approvals stall in inboxes, and no one has a single source of truth for contracts. Procurement software brings structure and automation to this process. At minimum, it digitises purchase requests and orders; more advanced platforms integrate supplier portals, inventory management, contract repositories, budgeting modules and analytics.
Core modules in procurement software
Procurement software isn't monolithic. It usually comprises multiple modules that can be implemented separately or as a suite:
Requisitioning and approval workflows: Employees submit purchase requests that route automatically to the right approvers. Customisable spend thresholds, delegation rules and notifications reduce bottlenecks.
Purchase order creation and management: Once approved, requests generate POs. The system sends POs to suppliers, tracks order status and ensures goods are received.
Supplier and vendor management: A central repository stores supplier information, qualifications, certifications and performance data. Portals allow suppliers to submit invoices and update their profiles.
Contract management: Contracts are stored centrally, with renewal reminders and version control. More advanced platforms extract clauses and link them to corresponding transactions.
Inventory and catalogue management: Maintaining catalogues of approved items prevents maverick spending and enables volume discounts.
Invoice processing and accounts payable: Systems automate invoice capture, match invoices with POs and receipts, and trigger payments once discrepancies are resolved.
Analytics and spend reporting: Dashboards provide real-time visibility into who is buying what, from whom and at what price.
Most vendors offer these modules through different deployment models. Some, such as procure-to-pay (P2P) or source-to-pay (S2P) suites, span the entire lifecycle from sourcing through invoicing. Others specialise in a particular area: e-procurement platforms focus on the requisition and ordering phase, while vendor management solutions provide a rich profile of supplier performance. The right choice depends on organisational size, complexity and integration requirements.
Why replace spreadsheets?
The argument for digitising procurement is straightforward. Modern platforms automate purchase order routing and invoice matching, shrinking cycles from days or weeks to hours or minutes. Industry research estimates that AI-enabled procurement can eliminate up to 30% of manual work and reduce overall costs by roughly 15–45% by improving spend analysis, contract management and supplier negotiations.
Some of the most recent advancements involve the use of AI agents to automate complex tasks and improve operational efficiency. This can be further enhanced with indexable knowledge hubs that use RAG (Retrieval-Augmented Generation) technology — a method where an AI model first retrieves relevant information from a large dataset or document repository and then uses that context to generate accurate, detailed answers. This allows you to query huge file and document repositories with AI.
Centralising data provides a single source of truth for spend and suppliers, and supplier portals enhance collaboration. Automated matching prevents duplicate or erroneous payments, and maintaining audit trails strengthens compliance. With these basics in place, teams can shift from firefighting to strategic decision making.
Software type | Focus | Typical features |
|---|---|---|
e-Procurement | Requisition and order management | Catalogues, approval workflows, purchase orders |
P2P (Procure-to-Pay) | Requisition through payment | e-Procurement features plus invoice matching and payment integration |
S2P (Source-to-Pay) | Strategic sourcing to payment | Supplier sourcing, contract management, spend analysis, P2P |
Vendor management | Supplier relationships | Qualification, performance tracking, risk scoring, collaboration portals |
This taxonomy isn’t rigid and many vendors blur the lines. What matters is how well the platform addresses your organisation’s pain points and integrates with your finance or enterprise resource planning (ERP) systems. Supply networks rely on many interconnected relationships. Procurement software helps map and manage these interactions.
AI in procurement: hype versus reality
Artificial intelligence has leapt from research papers into boardrooms. In procurement, early successes include machine-learning models that classify spend and predict demand, chat assistants that help employees submit purchase requests, and generative AI that drafts summary clauses. Adoption is rising quickly: Gartner’s 2025 Procurement Innovation Report found that 78 percent of global enterprises have implemented or are scaling AI-powered procurement tools. A separate survey noted that 90 percent of chief procurement officers (CPOs) have considered or already use AI agents, yet nearly 40 percent are looking to go beyond basic efficiency gains and leverage advanced analytics for strategic value. Despite this momentum, many organisations still struggle with data quality, change management and clear ROI. This gap between ambition and execution underscores why AI adoption remains uneven.
Before diving into use cases, it helps to clarify terminology. Not all AI is generative. Traditional machine-learning models are suitable for pattern recognition: they categorise spend, forecast demand and detect anomalies. These models are trained on numerical and categorical data and are used in predictive analytics and optimisation. In contrast, generative AI models, such as large language models, are trained on large volumes of text. They can summarise contracts, answer questions in natural language or draft negotiation clauses. They do not calculate optimal order quantities or forecast commodity prices. Additionally, different software can be used for processing, such as robotic process automation (RPA) that can automate rule-based tasks like routing invoices or generating purchase orders. Modern procurement software often combines these elements: machine-learning for predictions, generative AI for language, and RPA for workflows.
Use cases across the procurement lifecycle
AI can enhance nearly every step of the procurement process. Below are some of the most impactful applications, with examples drawn from research and industry practice.
Spend analytics and demand forecasting
Classifying spend by category is essential for understanding where your money goes. AI systems trained on past transactions automate this classification and reveal patterns that manual categorisation misses. Machine learning can also forecast demand based on historical usage, seasonality and external variables. Advanced analytics accelerate category management by enabling accurate spend categorisation and demand forecasting, while interactive AI interfaces allow procurement leaders to query market events or alternative suppliers. AI cannot guarantee perfect forecasts — black swan events will always disrupt supply chains — but it dramatically improves visibility and responsiveness.
Supplier sourcing and risk management
AI helps identify and evaluate suppliers by analysing structured and unstructured data, from financial statements and quality metrics to news articles and ESG disclosures. Reports highlight how AI monitors billions of data points to flag potential supply chain disruptions and combines supplier performance, market conditions and geopolitical information to provide near real-time risk visibility. Intelligent supplier assessment tools process delivery performance, quality scores and sustainability credentials to rank vendors. Leading procurement platforms tout their ability to analyse thousands of data points across financials, performance history and news mentions to flag risks early, improving supplier choices and reducing unpleasant surprises. Digital twin models go even further: they simulate supply chains, allowing scenario planning for events such as natural disasters or component shortages.
Sourcing and negotiation automation
AI simplifies the sourcing process by generating request-for-proposal (RFP) documents, identifying qualified suppliers and scoring responses. Industry reports describe “semi-automated sourcing” where AI engages users in conversations to define requirements and then analyses supplier proposals to score them. Generative models can also assist with negotiation scripts, suggesting counter-offers or concession points. While final negotiation decisions remain with humans, these tools accelerate preparation and reduce bias.
Procurement orchestration and intake
One of the most time-consuming steps in indirect procurement is simply capturing requests and routing them to the right approvers. AI can triage requests via chat interfaces, interpret natural-language descriptions and populate forms automatically. For example, a chatbot integrated into Slack or Teams can ask clarifying questions, suggest approved vendors and submit the requisition for approval. The same principle applies to procurement orchestration: AI coordinates different systems to ensure that purchase orders, contract approvals and invoice matching happen in the correct sequence.
Contract management
Once a contract is signed, it rarely surfaces again until something goes wrong. AI changes that. Natural-language processing can extract key clauses, obligations and renewal dates from contracts, compare them with company templates, and flag deviations. Reports point out that automated contract management platforms now go beyond storage, extracting key terms, alerting teams to renewal dates and identifying consolidation or renegotiation opportunities. Reports note that AI shortens review cycles by extracting clauses, flagging inconsistencies and comparing new contracts to approved templates. Generative AI can even redline documents by suggesting edits or summarising differences between versions, speeding legal review.
Invoice processing and touchless procurement
Processing invoices manually is resource-intensive and error-prone. Machine-learning models can capture invoice data, match it against purchase orders and receipts, and route discrepancies for resolution. Procurement software vendors report achieving up to 90 percent straight-through invoice processing. AI also detects duplicate payments and identifies opportunities for early payment discounts.
Spend optimisation and dynamic pricing
AI doesn’t just record past spend; it recommends ways to optimise it. McKinsey notes that combining procurement data with external commodity prices and should-cost modelling helps teams negotiate better terms and anticipate market trends. Machine-learning models can recommend order quantities and timing to balance inventory holding costs against stockout risks.
Supplier relationship management and collaboration
Beyond scoring suppliers, AI supports collaborative supplier relationships. Reports highlight how AI provides deeper insights into supplier capabilities, enabling innovation and strategic partnerships. Reports note that AI helps monitor compliance automatically, ensuring procurement policies are followed and flagging issues before they become costly. For organisations pursuing sustainability goals, AI can integrate sustainability metrics and emissions data to inform supplier selection.
Strategic decision support
Procurement leaders need actionable insights rather than raw data. AI-driven dashboards provide predictive and prescriptive recommendations on categories, suppliers and contract terms. Strategic decision support is a growing use case for AI, with data-driven dashboards helping teams design better sourcing strategies and detect outliers. These systems allow executives to ask natural-language questions about spend or risk and receive contextualised answers, making analysis more accessible.
Benefits and challenges
The rationale for AI in procurement is compelling: efficiency gains, cost reduction, risk mitigation and better governance. Automation reduces manual processing time and frees teams to focus on higher-value tasks. AI identifies savings opportunities, lowers processing costs and reduces errors. Continuous supplier monitoring alerts teams to disruptions and helps prevent fraud.
Yet obstacles remain. McKinsey notes that many digital procurement initiatives stumble due to poor data quality, unclear business cases and difficulties scaling adoption. Industry reports underline the challenge of turning optimism into reality. Without clean, centralised data, AI will amplify existing errors rather than eliminate them. Change management is equally vital: procurement professionals need training to interpret AI outputs and to shift from transactional to strategic roles.
Guidelines for implementing AI procurement
Implementing AI successfully requires a deliberate roadmap. Experts recommend starting with a single high-impact use case, such as invoice matching or supplier risk scoring, to demonstrate quick wins and build confidence. Clean and standardise your data before deploying AI — messy supplier master data or mismatched contract terms will undermine results. Choose software that integrates well with your existing ERP and offers robust security and compliance controls. Provide training and change management support to help procurement teams adapt to new workflows. Finally, monitor and measure outcomes, adjusting models and processes as you scale.
Leading procurement software platforms
The procurement software landscape is diverse. Some vendors offer broad S2P suites with built-in AI, while others specialise in particular steps. Here is an overview of notable tools. This list is not exhaustive and does not constitute endorsements, but it illustrates the range of options available:
Tipalti. Tipalti focuses on supplier management, procurement, invoice management, payment remittance and tax compliance. It offers accounts payable automation and integrates with ERPs like NetSuite, QuickBooks and Sage. Case studies show that clients cut procurement and accounts payable workload by 80 percent and close their monthly accounts 25 percent faster.
Precoro. Precoro covers purchase requests, purchase orders, approval workflows, reporting, budgeting, supplier management, inventory management and expense management. It integrates with ERPs and is priced on a per-user basis.
Procurify. This platform emphasizes spend control and real-time visibility. It allows businesses to manage purchase requests, approvals and budgets from desktop or mobile devices. Procurify integrates with accounting software and provides dashboards to track spending across departments.
Teampay. Geared toward high-growth companies, Teampay embeds procurement workflows into collaboration tools such as Slack and Microsoft Teams. It simplifies requisitions, enforces approval policies and issues virtual cards.
Coupa. Coupa is a comprehensive spend-management platform covering procurement, expenses, procure-to-pay, supplier management and contract management. Its AI-powered analytics and community-sourced benchmarks help companies optimise spend.
Airbase. Airbase combines accounts payable, expense management, corporate cards, procurement, budgeting and reconciliation in one platform. It offers real-time spend visibility and automates accounting entries.
SAP Concur. Originally designed for travel and expense management, SAP Concur now includes modules for procurement, invoicing and compliance. It integrates with SAP ERP and third-party systems.
PayEm. A global procure-to-pay platform, PayEm manages procurement, payments, budgeting and invoice processing with integrations across finance systems. It offers flexible approval workflows and supports multicurrency transactions.
Vroozi. Vroozi provides procure-to-pay and marketplace capabilities targeted at mid-market companies. It emphasises user-friendly requisitioning and catalogue management and offers subscription-based pricing.
These tools address common procurement pain points, but AI capabilities vary widely. When evaluating vendors, focus on whether their AI features tackle your specific challenges — for example, automated classification of tail spend or predictive supplier risk scoring — rather than being swayed by marketing hype.
The V7 Go approach: agentic AI for procurement
V7 Go isn’t marketed as a procurement suite but can be used for automating the process in a centralized way. It is a platform for building and orchestrating AI agents that handle knowledge-heavy processes. Because procurement touches contracts, invoices, specifications and regulations, it can benefit from the same underlying capabilities that legal or finance teams use on V7 Go. In essence, you assemble an agentic workflow tailored to procurement rather than buying a pre-configured solution.
For example, a procurement team could build an AI agent that reads incoming contracts, extracts delivery terms, payment conditions and penalty clauses and stores them in a structured repository. Using retrieval-augmented generation, the agent can answer natural-language questions like “What are the payment terms for Supplier A?” or “Show me all contracts with penalty clauses above €50,000.” It can cross-reference these answers with source documents, ensuring that humans can verify every extracted value.
Another agent might process invoices. V7 Go’s intelligent document processing pipelines automatically capture invoice data, compare it with purchase orders and goods receipts, and flag discrepancies. A case management module then assigns exceptions to an analyst. Because V7 Go supports bringing your own API keys to popular language models, users can choose between different large language models for summarisation while keeping proprietary data secure. These automations don’t replace predictive forecasting tools; they augment them by digitising and structuring input data so predictive models can operate on clean information.
Procurement also involves unstructured communication with suppliers. V7 Go’s AI concierge — described in our overview of AI workflow automation — allows non-technical users to ask open-ended questions and trigger workflows across documents. For instance, a category manager might ask, “Compare the sustainability certifications of our top five suppliers in the electronics category,” and the concierge would compile a report using the data extracted earlier. Another workflow might automate the creation of sourcing dashboards by combining spend data, supplier risk scores and market intelligence. Because V7 Go treats each step as a modular agent, procurement teams can adapt workflows without writing code, whether they work in healthcare, manufacturing or retail.
The point isn’t that V7 Go replaces traditional procurement suites. Instead, it complements them. Where a P2P system focuses on transaction processing, V7 Go excels at extracting insights from unstructured documents, orchestrating multi-step tasks and providing verifiable answers. Organisations might use a P2P suite to handle catalogues and payments while relying on V7 Go to automate contract analysis, supplier due diligence and RFP triage. This hybrid approach leverages the strengths of both worlds: stable transaction processing and flexible AI-driven intelligence.
Looking ahead
AI adoption in procurement is at a tipping point. Gartner reports that 78 percent of global enterprises have implemented or are scaling AI-powered procurement tools, yet the implementation gap identified by other surveys remains. The future will likely involve autonomous sourcing agents, real-time ESG scoring and embedded AI alerts within ERPs. To prepare, procurement teams should invest in data quality, experiment with AI in targeted areas and develop the analytical skills required to interpret machine-generated recommendations. As the technology matures, AI won’t replace procurement professionals; it will free them to focus on strategy, supplier innovation and risk management.
Hype versus reality: practitioner perspectives
Despite the optimistic forecasts in industry reports, procurement teams on the ground often paint a more nuanced picture. In public forums frequented by buyers and contract managers, people describe AI tools as powerful yet limited assistants rather than all-seeing masterminds. Many practitioners who evaluated several AI-enabled procurement suites and shared their insights on Reddit said that most vendors overpromise on end-to-end automation. Others echoed that sentiment: current AI is excellent at discrete tasks like optical character recognition and invoice matching but still struggles to handle complex negotiations or supplier relationships on its own.
Some buyers caution against jumping straight into advanced AI without fixing the basics. As one experienced procurement engineer put it, building sophisticated models on top of spreadsheet chaos and email management is like erecting a skyscraper on quicksand. They recommend first digitising vendor onboarding by creating online forms and using simple automations to capture vendor data, send acknowledgements and store contracts. A lightweight AI email assistant powered by a large-language model can help craft professional replies to supplier questions, saving hours of manual typing. Only once core data flows are automated does it make sense to layer in AI-driven document intelligence and follow-up workflows.
Others stress the need for human expertise alongside AI. A ten-year veteran of procurement recounted how their contract analysis tool initially missed an important liability cap. When prompted, the model eventually located the relevant clause — but only because they knew what to ask. For them, AI is macros on steroids that augments rather than replaces judgement. A security-conscious commenter also highlighted the importance of data governance: using consumer chatbots to process vendor data can run afoul of privacy rules, so organisations should ensure their automations meet enterprise security standards. Taken together, these accounts reveal an emerging consensus: AI accelerates rote work and surfaces insights, but success depends on clean data, incremental automation and procurement professionals who retain the final say.
