1. Invoice processing and accounts payable

Accounts payable teams sometimes deal with hundreds or thousands of invoices a month, and the invoices are sent to them in a variety of formats. The range of invoice formats can lead to problems such as data entry errors, late payments and potentially fraudulent activity.

Automated invoice processing uses large language models (LLMs) to retrieve invoice data, compare it to purchase orders and delivery notes, then route it through approval pipelines. These processes can often be completed without the need for human intervention, though human employees should potentially analyze more unusual invoices and monitor invoice trends and patterns.

2. Spend analysis and category management

Inconsistent spend categorization across areas can lead to various issues. Automated spend analysis tools can categorize data across multiple systems, enabling managers to compare unusual expenses against company benchmarks.

CPOs should instruct category managers to avoid drawing any conclusions from the first automated spend analysis. The value of automating these processes will be in the trends that will eventually be revealed.

3. Supplier monitoring and risk scoring

Automation enables companies to carry out continuous monitoring of suppliers, which can help improve overall operations.

Also, AI research platforms can scan relevant information, then generate supplier risk scores so the company can decide whether or not to move forward with a particular vendor.

4. Demand forecasting and inventory alignment

Matching supply with demand has always been the procurement goal that is most difficult to achieve.

Automated forecasting systems can help companies succeed by processing data that earlier software tools could not evaluate. For example, inputs such as social media trends and consumer behavior patterns can be fed into models for predictions about demand increases or shortfalls. These models don’t possess the human insight of a skilled buyer but can carry out the processes quickly.

One application for automation in demand forecasting and inventory alignment is alignment of regional inventory. Analysis of historical buying patterns and new trends can ensure companies have stocked inventory at certain fulfillment centers before demand increases.

CSCOs in manufacturing, retail and distribution can determine the best candidates for automation by identifying which product categories result in the highest inventory costs because of poor visibility into trends and demand.

5. Compliance monitoring and audit trails

Procurement regulation is tightening in every region, and transparency is often seen as a weak point for AI.

However, tracing data lineage and the versions of AI models that were used to make a decision is possible, and in many cases, doing so is enough to show a fair degree of compliance. Manual procurement processes rarely produce documentation that is adequate to that standard.

Also, the same LLMs that extract contract terms can also check them continuously against regulatory requirements.

Donald Farmer is a data strategist with 30-plus years of experience, including as a product team leader at Microsoft and Qlik. He advises global clients on data, analytics, AI and innovation strategy, with expertise spanning from tech giants to startups. He lives in an experimental woodland home near Seattle.