Generative AI is the new iteration of artificial intelligence, and will eventually change how suppliers are identified, evaluated, onboarded, and managed. This powerful technology may also increase supplier diversity across organizations through objective supplier discovery and evaluation. -BY Shaniqua Thomas

While generative artificial intelligence (AI) has only begun to demonstrate its power to change how business is conducted, it is already making a huge impact. As sourcing, procurement, and supply chain management seem unendingly complex, generative AI may become a critical technology for automating sourcing activities. It can potentially automate many supply chain processes, including finding and analyzing suppliers based on a combination of AI-collected data and human input data. It also has the potential to assist with supplier negotiations by quickly presenting multiple contract scenarios for consideration, minimizing bias in supplier selection, and supporting supply chain management in multiple ways.

A Brief AI Background

Generative AI is a deep-learning model that uses raw data to generate statistically probable outputs. The technology “learns” with each iteration as it collects more data. The type of data it can now utilize includes numerical data and data from speech, images, and other sources.

As a result of these innovations, AI can now do remarkable feats like adapting to multiple tasks at once by using unlabeled data to create a representation that can be applied to many tasks. It can also process instructions paired with various responses to generate statistically probable text and answer humanlike questions. For businesses that introduce structured and well-engineered prompts, AI can now be customized to do a wide range of tasks just by asking it to do so.

Interacting with AI

Getting useful results requires human technology wizards who can manage generative AI behavior so that it does not produce unwanted results. One example of this is bias, because systemic bias is embedded in many raw data sources, and firms need to use smart guidance to ensure historically biased data sets being used to train an AI system do not pass on their skewed outlook. However, knowing the risks, companies can still see how AI’s processing power can be leveraged to become an important element of sourcing strategies.

In Deloitte’s 2023 Global Chief Procurement Officer Survey, responses indicate procurement risks and supply chain disruptions continued to increase over the last year, including in areas like compliance, fraud, supplier performance, and cost fluctuations. A major challenge is selecting the best suppliers to meet organizational needs, which has also become incredibly complex. Generative AI can assist with supplier selection by quickly evaluating supplier capabilities, product specifications, performance risks, costs, and potential cost savings. Firms can also use generative AI to simulate negotiations with suppliers and predict outcomes. The various scenarios and outcomes can then support a firm’s development of sourcing strategies. Deloitte gives an example of a generative AI use case as an RFP response evaluation. An organization creates an RFP and vendors respond. Rather than manually reviewing initial submissions, AI is put to work. Cognitive services are used to identify significant information in the responses and identify context. The content is summarized, complex words are identified, and a scoring framework is generated from pre-defined evaluation criteria. The vendor responses are scored, and a prioritized list of vendors is generated based on quantitative and qualitative factors in a fraction of the time it might take a purely human team.

There are many other use cases and variations. In the future, buyers and sellers may interact in multiple ways, such as AI to AI, human to AI, AI to human, and human to human. The possibilities are limited only by available data and the comfort levels of human operators with the tools.

Generative AI learns from huge amounts of data. To be effective for sourcing, it needs up to date data sets covering logistics, inventory, materials requirements, sales, labor costs, scalability, demand, and more. As companies feed and train their AI platforms, these platforms will be able to analyze a broader set of inputs and variables than humanly possible within a reasonable amount of time. This will also allow for efficient modeling of contracts, data-driven recommendations on supplier relationships, and more structure in complex processes.

Increasing Supplier Diversity

For sourcing, the potential of generative AI to analyze more suppliers based on capabilities, performance, and risks could lead to more supplier diversity. In fact, TealBook’s Chief Technology Officer, Arnold Liwanag, feels AI is critical to the search for diverse suppliers. By using functionalities like searching the web at scale and using relevant data to produce more accurate supplier profiles, AI can uncover new suppliers based on sourcing and procurement criteria. These fresh suppliers are likely to include minority-owned enterprises, women-owned businesses, and small business enterprises that might have been previously overlooked by purely human teams.

Liwanag also notes AI can increase business agility with more accurate data, increased efficiencies, and more diverse supplier pools. Sourcing and procurement can more easily add new suppliers to take advantage of business opportunities by speeding up any process that can be automated. Since one of the barriers to increasing supplier diversity is organizational managers who prefer “business as usual” with their favorite suppliers, these changes can drive results.

Sure to Play a Bigger Role in Sourcing Strategies

Generative AI is transforming sourcing and procurement. It can automate rote functions, produce predictive analytics, optimize supply chain logistics, access a broader supplier database, perform deeper supplier analysis based on input criteria, and increase identification of diverse suppliers. It will become a negotiating and strategy development tool and has tremendous potential to significantly reduce stubbornly embedded biases in sourcing and procurement.

In a collaborative study by Wharton School and GBK Collective on the adoption and impact of generative AI, a poll of U.S. businesses found that 71% of those surveyed believe generative AI will be used for managing supply chains, increasing efficiency and effectiveness in the future. Thus, while generative AI in sourcing is still in the early stages, there is no doubt it will become a critical tool in any organization that wants to remain competitive.