Procurement in the Age of AI

Procurement professionals face challenges more daunting than ever. Recent years’ supply chain disruptions and rising costs, deeply familiar to consumers, have had an outsize impact on business buying. At the same time, procurement teams are under increasing pressure to supply their businesses while also contributing to business growth and profitability.

Deloitte’s 2023 Global Chief Procurement Officer Survey reveals that procurement teams are now being called upon to address a broader range of enterprise priorities. These range from driving operational efficiency (74% of respondents) and enhancing corporate social responsibility (72%) to improving margins via cost reduction (71%).

To meet these rising expectations, many procurement teams are turning to advanced analytics, AI, and machine learning (ML) to transform the way they make smart business buying decisions and create value for the organization.

New procurement capabilities unlocked by AI

AI and ML tools have long helped procurement teams automate mundane and manual procurement processes, allowing them to focus on more strategic initiatives. But recent advances in natural language processing (NLP), pattern recognition, cognitive analytics, and large language models (LLMs) are “opening up opportunities to make procurement more efficient and effective,” says Julie Scully, director of software development at Amazon Business.

The good news is procurement teams are already well-positioned to capitalize on these technological advances. Their access to rich data sources, ranging from contracts to invoices, enables AI/ML solutions that can illuminate the insights contained within this data. Acting on these insights unlocks new capabilities that can enhance decision-making and improve spending patterns across the organization.

Predicting supply chain disruptions. In an era of constant supply chain disruptions, procurement teams are often faced with inconsistent item availability, which can negatively impact employee and customer experience. Indeed, the Deloitte 2023 Global Chief Procurement Officer survey finds that only 25% of firms are able to identify supply disruptions promptly “to a large extent.”

AI tools can help address this issue by recognizing patterns that indicate an emerging supply shortage and automatically recommending two or three product alternatives to business buyers, thereby preventing supply disruptions. These predictive capabilities also empower procurement teams to establish buying policies that proactively account for items that are more likely to go out of stock.

Answering pressing questions quickly. Sifting through data to understand the cause of a supply chain disruption, product defect, or other risk is time-consuming for a procurement professional. LLM-powered chatbots can streamline these processes by understanding complex queries about orders and “putting together a nuanced answer,” says Scully. “AI can query a wide variety of sources to fully answer a question quickly and in a way that feels natural and understandable.” In addition to providing fast and accurate answers to pressing questions, AI promises to reduce the need to explain procurement issues eventually. Instead, it will proactively analyze orders, buying patterns, and the current situation to provide instant support.

Offering customized recommendations. As business buyers increasingly demand personalized experiences, procurement officers seek ways to customize their interactions with business procurement systems. Scully provides the example of an employee tasked with hosting a holiday party for 150 employees who needs help deciding what to order. An AI-based procurement tool posed that scenario, she says, could generate a proposed shopping cart, sifting through “millions and billions of data points to recommend and suggest items that the employee may not have even thought of.”

Better yet, she adds, “as we get into really large language models, AI/ML can help answer questions or help buy items you didn’t even know you needed by understanding your particular situation in a much more detailed way.”

Influencing compliance spend. Procurement professionals aim to balance employees’ freedom to purchase the items they need with minimal intervention. However, self-sufficiency should not come at the cost of proper spend management, productivity, and policy compliance. “There’s always a healthy tension between how a company ensures they have the right controls and oversight but also enables a federated spend model,” says Scully. Fortunately, she says, “AI can offer huge value” in alerting procurement teams to any “outliers” before any damage is done.

AI can also help ensure compliance by enforcing spending policies and expectations so that employees “can still confidently buy the right items,” says Scully. This capability can minimize the risk of overspending and also help with companies’ contractual obligations, such as fulfilling a spending commitment to a particular supplier. In the future, an AI-powered anomaly detection trigger might even be used to examine large datasets to identify non-compliant purchases.

Increasing spending visibility. AI and analytics tools can provide greater transparency into overall procurement spending by automatically analyzing data and unlocking timely analysis. These data-driven insights provide procurement officers a comprehensive view of where they’re allocating budget and areas where they might be able to cut costs.

But greater transparency into procurement spend can also empower organizations to respond to emerging business priorities, such as adopting more socially responsible purchasing practices. “Companies want to prioritize locally owned businesses or businesses that prioritize a lower carbon footprint,” says Scully. With greater visibility into their procurement patterns, organizations can direct business buyers to climate-friendly products or suppliers that help meet  their environmental, social, and governance goals.

Driving procurement productivity. Monitoring supplier performance, ensuring spend compliance, and identifying supply chain disruptions—these are all time-consuming activities that distract procurement professionals from more business-critical objectives. “If the procurement team is bogged down in day-to-day processes, they can’t be thinking about their overall strategic goals for the company, if they’re able to deliver them, and where they might want to provide optimizations,” says Scully. By automating labor-intensive processes such as spend analysis, product selection, and tracking down orders, advanced procurement tools can free procurement teams to focus on value-added activities.

Best practices for AI-powered procurement

For all the advantages of advanced analytics and AI/ML solutions, procurement teams must take steps to ensure the best use of these innovative tools. AI models are only as relevant as the training data they ingest. For this reason, Scully says, organizations need “to be aware that a model may sometimes have blind spots or not immediately recognize if the business is beginning a change in strategic focus.” As an organization’s priorities evolve, the model training data must keep pace to reflect new business goals and circumstances.

To get the most from its advanced technology tools, procurement teams should ensure that they support the company’s overall procurement goals and business strategy. These goals may range from working with a more diverse supplier base to purchasing more sustainable goods. Whatever the desired end, the procurement function must link its use of new AI-powered tools to achieving its business goals and regularly evaluate the results.

The new procurement capabilities unlocked by advanced analytics and AI/ML can help businesses rethink how procurement gets done. As generative AI and related technologies advance, sophisticated procurement use cases are likely to multiply, offering substantial financial and operational gains to procurement teams.

Originally published on MIT Technology Review.