AI is everywhere—or so a casual perusal of business headlines would make you think. But why is it still underrepresented in the procurement function?
We covered some of the reasons why we view this area as ripe to benefit from the transformative nature of AI and machine learning in the first article in our series. Now, let's take a closer look at some high-potential use cases with the power to transform procurement.
Putting AI to work to tame uncertainty and replace manual processes
AI can unlock tremendous value in areas where high uncertainty or significant manual processes exist. Supplier Relationship Management (SRM) and Source-to-Contract (S2C) are two areas where these conditions exist. In SRM, for example, uncertainty comes from having to identify and research alternative suppliers and research factor market development along with its potential impact on the firm's P&L statement. Examples of high manual effort processes include monitoring relevant contracts and terms and conditions (T&Cs) for multiple suppliers over many instances within the company, as well as structured, systematic bid evaluation.
We've observed cases where contracts and amendments are sometimes contradictory within the same supplier (or supplier conglomerate), often at the expense of the buyer.In other cases, favorable situations for new negotiations are missed or overlooked because of special contract terms unknown to the procurement team. Companies may avoid issuing broad RFQs for medium-sized commodity categories since they are often linked to a high degree of manual effort to check bids for consistency and missing information, as well as interfaces between the bids (indicating potential price fixing). This leads to RFQs with a limited number of suppliers (often already known or incumbent), analyzed only at a macro level.
Three AI solutions for common pain points
Here are three simple ways to implement AI-enabled solutions to address these procurement functions with high uncertainty and manual processes.
1. Supplier research and best fit assessment
Most organizations lack structured processes to identify and evaluate alternative suppliers in comparison to incumbents. There may be insufficient time to conduct a thorough analysis, from researching and identifying potential suppliers to assessing their capabilities, capacities, and overall health (from outside in). Two key challenges exist: 1) gathering relevant information for identification and research, and 2) effectively assessing the insights gained. Understanding the viable options in the market is crucial for presenting an alternative to the current supplier. However, it's important to ensure that the information you have is relevant and thoroughly researched.
AI solution: AI excels at thoroughly analyzing the supplier landscape. Models can be trained to focus on key factors such as capabilities, footprint requirements, and more, helping to narrow the list of potential suppliers for deeper analysis. The buying organization can avoid starting from scratch and instead evaluate a select group of promising candidates.
Once chosen, an AI-driven bid or RFI process can automatically analyze commercial and technical aspects, identify missing information, assess risks, and highlight promising candidates – tasks that were previously done manually. The process is even more efficient if the AI tool is integrated with the supplier portal, where information is submitted in a semi-structured format.
The AI agent can then automatically notify suppliers about missing or unclear data. Ideally, the buyer can step in when the information is complete, allowing them to review bids, decide on the next round of evaluations, or move into negotiations. An AI solution could not only save days of manually comparing bids but also increase effectiveness in ensuring compliance with RFI rules and broader procurement policies. AI agents are already handling limited scope commercial negotiations for some commodities today.
2. Spend forecast based on factor market development
Procurement data has two main issues: one is overall data quality, and the other is correctly linking commodities or parts to their respective underlying factor markets.
AI Solution: The benefits of AI in improving data quality – by structuring, cleaning, and enriching data – are well-known and have been widely discussed. However, AI can also help link the correct factor market index to a specific category. The AI model would then map the work package to a certain index given a defined taxonomy. Understanding the taxonomy and the wider context of the exercise, the AI model would then not only return exact matches, but a reliable base of indices suitable to effectively describe the factor market nature.
With forecasting capabilities to identify patterns (such as seasonality, events, or disruptions), AI can enable buyers to stay ahead of market trends, achieve better negotiation outcomes, or at least enter negotiations fully prepared. To make the most of this, buyers should understand how changes in the factor market directly impact their category. While this is not necessarily an AI-driven solution, it's an essential part of the process.
3. Ensuring contract compliance and tracking usage
Once a supplier is established, you'll eventually need to retrieve the most current applicable contract clauses. If you're not careful, you might be sourcing under incorrect terms, or the supplier could be operating under different conditions for different BUs or plants, rather than within the framework agreement. Manually comparing documents over time or across work packages can easily become exhausting.
AI solution: A Natural Language Processing (NLP)-based AI tool can streamline this process by autonomously comparing hundreds of documents, extracting and structuring relevant data. This ensures contract compliance, highlights discrepancies, and provides leverage for negotiations. Additionally, combining this data with advanced analytics allows for automated actions, like triggering contract renewals or initiating new negotiations when specific conditions are met (e.g., volume thresholds).
Proper training of the tool does not require an exact fit of a specific term or condition, as the AI model understands the broader context and returns the most probable answer. A typical example is the return of any state tax or agreements. Even if the specific locality is not explicitly stated, the tool will return the right answer. Language standardization is no longer an issue. You can easily upload your contracts in local languages, and the AI tool will return the answer in the preferred language. For smaller document sets, Microsoft Copilot already offers a solution to compare documents efficiently.
Make vs. buy decisions
When considering AI in procurement, the make-or-buy decision hinges on scope and speed. Built-in tools like Microsoft Copilot already offer quick wins, automating tasks such as document comparison, supplier communication, and spend analysis—often with little upfront investment.
Larger-scale or customized solutions, whether developed in-house or sourced from partners, require a clear business case and alignment with your IT and data strategy. In-house builds are typically slower and more costly, while external providers offer speed but must fit within your ecosystem.
There's no universal answer, but starting with simple, embedded tools is low-risk. For advanced use cases, ensure objectives are clear—unclear goals lead to expensive pilots and frustrated stakeholders.
Practical use casesare the key
Identifying practical use cases such as those outlined above can help procurement decision-makers roll out AI to improve their operations and control uncertainty. We have advised clients who are looking for high-impact use cases and helped them select potential external solution providers.
Next up in our series, we'll examine the role of procurement professionals in balancing innovation with cost management, ensuring that their organizations reap the benefits of AI while optimizing costs for their business partners.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
