AI Utilization in Procurement and Sourcing

As AI gains increasing prominence in industries around the world, its functionalities and supply chain use cases continue to be uncovered and refined. Procurement is at the core of a well-functioning supply chain, with effective and efficient materials sourcing being an absolute necessity for businesses. In a truly global marketplace, two things become true. First, myriad options await businesses searching for suppliers, offering new opportunities every day to make better connections and expand and improve relationships. Second, this abundance of choice can be limiting, in the sense that too many options exist for any procurement team to possibly scour through on their own. Here, automation comes into play, as a resource to find resources, and optimize the work of procurement teams, helping them to find and foster the best supplier connections available.

“Bigger” Data

When analyzing the components of a company’s procurement process, from supplier selection, to PO quantities, budgets, market trends, and more, there is only so much that traditional algorithmic models can handle. Larger and more detailed datasets can be analyzed with AI implementation, allowing for companies to make better use of their time and resources. A key difference between the models many companies already use and those that utilize AI comes in enhanced predictive capabilities. When analyzing market trends, the reliability of forecasts can vary greatly, which can significantly impact the sourcing decisions companies make with pricing and availability in mind. AI programs are able to learn much more quickly and effectively than traditional models, allowing for more accurate and reliable forecasts. Of course, this process still takes time, but by functioning with both greater efficiency and accuracy, companies can make more effective sourcing decisions and stay on top of trends. Ultimately, experienced procurement professionals will be making the calls, but their decision-making can be better-informed with more reliable data interpretations made available to them. This pairing of employee expertise with access to data insights that were once unavailable, given the insurmountable size of the datasets, will help companies tremendously as they seek to gain an edge over competitors in their sector. Here, AI helps people do their jobs more effectively, rather than automating away a process still very much reliant on experience and expertise.

Ethical Sourcing and Sustainability

More complex and thorough, not to mention vastly larger, datasets provide valuable information not only for pricing and market trends, but also matters of environmental impact and labor practices. AI sourcing programs offer a level of customizability and specialization that allow companies to align their search processes with their principles highly effectively. Sustainability-specific software is being developed for a variety of use cases, and its potential in sourcing could prove to be particularly impactful. Procurement teams can select filters and set benchmarks to establish the parameters of their search, aiding efforts to work with producers of raw materials that carry out sustainable practices. Large databases can introduce procurement teams to new sourcing partners they were previously unaware of that can offer better partnerships built on a mutual dedication to sustainability. And by keeping digital records, ethics violations are easier to find, helping companies determine which sourcing partners are consistently reliable in their commitment to fair labor practices, rather than just seeking to profit off recent trends. The archival and identification abilities of AI programs will help ensure the accuracy of these records, and facilitate internal company recordkeeping of best practices and partners. Sustainability-wise, we’ve yet to even mention the role AI can play in helping to identify more local sourcing opportunities, as well as optimized shipping routes, which we explore further in our article here.

Risk Management

AI programs offer a key safeguard in addition to identifying suppliers who meet a company’s economic, environmental, and ethical standards. Risk forecasting, in a capacity similar to the market forecasting aspect of these models, is a notable benefit, helping procurement teams create more well-rounded plans that take into account the potential pitfalls underlying any sourcing agreement. AI programs can analyze not only the reliability of sourcing partners to deliver the materials expected, but the likelihood of them being impacted by outside environmental, economic, or myriad other factors. They can then recommend diversification options so that companies aren’t left in the lurch when one supplier is rendered temporarily unavailable. A crucial supply chain takeaway from the COVID-19 pandemic was the necessity of having multiple reliable sourcing options, so as to create more resilient supply chains capable of withstanding unforeseen fluctuations. With the increased prevalence and frequency of disruptive climate events, as well as volatility in global markets and materials costs, having adaptable forecasts and reliable options is a necessity for the procurement professionals of both today and tomorrow.

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