AI is revolutionizing procurement and supply chain
What is generative AI?
Artificial intelligence (AI), specifically generative AI (GenAI), is revolutionizing business as we know it—and procurement and supply chains are no exception. Generative artificial intelligence is a type of artificial intelligence technology that uses data to generate new forms of content including text, imagery, and audio. Recent innovations in generative artificial intelligence, such as ChatGPT, are transforming and simplifying the way people create high-quality content for many different applications, including procurement and supply chain.
Today in procurement, basic artificial intelligence technologies are being used for contract analysis, spend classification, supplier discovery, and demand and supply planning. Yet with the rise of GenAI, more sophisticated use cases are emerging that can help teams become more efficient and maximize value. With so much data available, GenAI can help procurement and supply-chain teams process large data sets and identify patterns, opportunities, and competitive advantages.
Use cases and examples for AI in procurement and supply chain
According to CB Insights research, 2022 was a record year for investment in generative AI start-ups, with equity funding hitting $2.6 billion. Goldman Sachs predicts that generative AI could expose roughly 300 million jobs to automation and increase global GDP by 7% in 10 years. GenAI can help procurement and supply-chain teams specifically by optimizing efficiency, mitigating risk, and managing spend. Below are some of the use cases and examples for artificial intelligence in procurement and supply chain.
Demand intake
Understanding the demand for parts and services at most organizations is a manual process for buyers. Between disparate systems like spreadsheets, emails, and messaging platforms, business stakeholders and procurement and supply-chain teams have no easy way to collaborate on requests and source accordingly. This lack of collaboration means competitively sourcing at scale is challenging.
AI could be a breakthrough solution for these use cases. Conversational platforms, chatbots, and virtual assistants can self-serve and guide business users through the process of articulating what they need from procurement. As a result, AI tools can free up time for procurement to spend on more strategic projects, not on back-and-forth communications, while also mitigating rogue spend.
Autonomous sourcing
Procurement teams are focused on strategic sourcing and often leave the smaller, more frequent purchases to business stakeholders—otherwise, they simply wouldn’t have time for anything else.
Autonomous sourcing uses artificial intelligence capabilities to identify predictable purchases, create an RFx, compare bids, and even award them based on preset criteria like price, lead time, and more. By reducing the need for human intervention yet maintaining control over risk exposure and cost-savings, these tools enable procurement teams to automate the entire source-to-pay process and remain hands-off with purchases like tail spend.
PO follow-ups & expediting
Understanding when materials will be delivered and gaining better visibility into issues causing bottlenecks in the supply chain is another massive challenge for procurement and supply-chain leaders. With the help of generative AI, you can now get updates on delivery dates for every purchase, and parse supplier responses for exceptions like quality problems, so you can accurately forecast incoming deliveries and understand the impact of delivery schedule changes on production.
These AI solutions help proactively mitigate order delay risks by sending exception notifications, tracking historical supplier performance, and updating delivery projections. This visibility empowers you to act quickly if crucial inventory is not going to arrive on time.
AI also helps to automate outreach to suppliers to get timely updates. Outreach sequences are designed to collect pertinent information from your suppliers at the right times so you can free up your team’s time to focus on more strategic initiatives.
Lastly, you can optimize your supplier base. Procurement and supply chain teams often struggle to get high-quality supplier performance data in one place so it can be analyzed for insights. Typically this data exists but in disparate locations like email inboxes. With generative AI, myriad unstructured data sources can now be parsed creating a rich dataset on supplier performance. With this data, you’ll learn which suppliers are providing on-time deliveries, and those that are consistently delayed, and have the data to communicate your suppliers’ performance to all key stakeholders. Teams can grow their supplier base (i.e. dual sourcing, adding localization) without having to double or triple the size of their teams. It also enables the team to spend more time on strategic goals like relationship development, forecast accuracy, and more.
Textual data analysis
One case for AI in procurement and supply chains is the ability to parse unstructured data into structured data through textual data analysis. For example, with Factor’s AI solution, users can automatically get the data sitting in their email and messages parsed and pushed back into the ERP to be updated accordingly. When a supplier reaches out to communicate a delivery delay or provide an advance shipping notice, this data can be ingested and automatically updated in the systems you need. Not only can AI solutions help read and parse emails, but also attachments. This could be a PO confirmation PDF, a failed inspection report in Excel, and more.
These AI solutions will allow supply-chain and procurement teams to grow their supplier base (i.e. dual sourcing, adding localization, and supplier diversity) without having to double or triple the size of their teams. It also enables the team to spend more time on strategic goals like relationship development, forecast accuracy, and more.
Strategy planning and risk management
GenAI can also help analyze more macro-level data sets, both structured and unstructured, to assist with finding, evaluating, and identifying the best suppliers. Additionally, these suppliers can be evaluated based on capabilities, performance, and associated risks to understand the downstream impact.
An example of this would be mining social media and local news to look for information on earthquakes, fires, and other natural disasters or geo-political events. This macro-level data can help manufacturing teams to more accurately forecast and build their plans. Knowing which of your suppliers are affected by one of these events would be incredibly useful, as well as where they are located or shipping from. By incorporating these third-party data sets, teams can figure out what demand could look like in 3, 6, or 12 months to make the forecasts much more accurate.
Contextual recommendations
When a request for parts or services has been sent to procurement, the buyers will first look to their existing supplier catalogs and agreements. Typically, this is a very manual process and involves reviewing multiple databases in disparate systems, all while considering pricing, availability, lead time, ESG, diversity, and more. If a buyer isn’t able to find a match based on historical purchase information, they then turn to the approved supplier database.
AI can help improve this time-consuming process using contextual recommendations. These recommendations will crawl massive databases across systems to suggest the next best step
Basic contextual recommendations AI can match a request to a category, while advanced use cases involve supplier recommendations, goods and services, and even pricing.
Contract analysis and compliance tracking
Even with large teams and lots of bandwidth, reviewing contracts and negotiations can be a very manual, time-consuming process for procurement and legal teams. Existing supplier contracts have a ton of information including service levels, terms, and discounts, while new contracts require negotiating.
With the help of artificial intelligence solutions known as intelligent contract analytics, procurement teams can upload contracts, extract the necessary information easily, and get recommended next steps from existing contracts to assist with sourcing new parts and services. It can also help teams to understand the most effective methods for negotiations by simulating complex negotiation scenarios and predicting outcomes.
For example, these solutions could alert the buying team of any renewals that may impact an in-flight sourcing event, or provide a snapshot of service level compliance that can be used during negotiations.
Similarly, AI can help review the contract, invoice, or PO data to flag any that are non-compliant, mitigating supply-chain risk.
Payments and invoice automation
Maximizing cash flow is critical to the business, while late payments can damage relationships with key suppliers. However, making payments, invoices, and matching POs is a very cumbersome, manual process that is prone to human error.
Artificial intelligence solutions are helping procurement and supply-chain teams and buyers reduce errors, accelerate payment times, and receive early pay discounts by eliminating the manual efforts necessary. Using natural language, existing contracts, and historical invoice and payment activity, these invoice automation solutions help to match invoices to POs to the appropriate invoices and payments. GenAI can also assist with identifying opportunities for cost savings.
Ready to leverage the power of AI in your supply chain? Click here to learn more or request a demo today to see how Factor can transform your operations and help you get better data from your suppliers to save money and time. Our supply chain experts are ready to provide a tailored walkthrough focused on your specific challenges and goals.