AI Procurement: Why it matters, Applications & Use cases 2024
The number of artificial intelligence and machine learning use cases in different industries expand daily. Procurement is no different. AI procurement applications like real-time monitoring of supplier’s performance and compliance data, identification of market-associated risk (e.g. tracking social media channels for signals about suppliers’ risk positions), and classification of spend and automation of repetitive tasks like invoice processing are bringing various benefits to companies.
What is procurement?
Procurement is the process of finding and agreeing to terms and acquiring goods, services, or works from an external source, often via a tendering or competitive bidding process. It involves making purchase decisions under conditions of scarcity.
Why do procurement teams need to leverage AI?
Data is crucial for procurement teams because, without the data, they cannot track the spending on goods and services and manage supplier and vendor relationships. The increasing number of data enables procurement teams to manage cost savings and supplier/vendor performance risk.
Procurement involves making purchase decisions under conditions of scarcity. Data-driven decision-making is required to ensure the buyer acquires goods and services at the best possible price when aspects such as quality, quantity, time, and location are compared. This makes procurement a good fit for AI because AI algorithms can provide insights and help companies make better decisions. According to Deloitte’s 2019 Global Chief Procurement Officer (CPO) Survey, 51% of CPOs indicated they are now using advanced analytics and 25 percent have, or are piloting, an AI/cognitive solution up from 19% in 2018.
What are AI applications in procurement?
Businesses can also leverage NLP to capture data on suppliers or specific markets via the internet so that it can predict market prices, identify and analyze new potential vendors, and help businesses evaluate the relationships with existing suppliers. Contract negotiations also become easier and more effective with the complete view of historical spending, vendor compliance and performance data, and other essential information available on demand.
Spend analytics helps organizations proactively identify savings opportunities, manage risks, and optimize their businesses’ buying power. Accurate spend data is foundational in the development of effective category, sourcing, and spend management strategies. Machine learning algorithms can be utilized to classify procurement spending into categories and sub-categories. AI-powered spending classification allows better analysis by enriching this data with external information from the web. In fact, according to a Deloitte report, projects that use AI spend classification have achieved around 97% accuracy in the classification of data.
Contract Management is the process of managing contracts from different parties (vendors, partners, and customers), covering the terms and conditions and deadlines, and supporting the processes that utilize the contract data, ensuring your vendor relationships are efficient and profitable. Natural Language Processing (NLP) enables companies to automatically scan and understand long and wordy legal documents for potential savings opportunities. Machine learning algorithm can also automate contract management via solutions like Sievo to make the auditing process faster and more efficient.
Artificial intelligence enables businesses to automatically detect anomalies such as fraud, compliance issues, or price changes across the supplier landscape.
Automation of manual tasks
Artificial intelligence can automate various time-consuming tasks like invoice processing where the procurement team spends most of their time receiving, reviewing, and paying the invoice. Invoice automation is a critical part of a company’s procure-to-pay (p2p) process where an average SME company takes about 25 days to process a single invoice when using a manual process. AI and automation reduce invoice processing times significantly and improve the overall efficiency of procurement teams.
Chatbots can provide support for employees & suppliers, for procurement queries via the text interface. The video below shows an example of a procurement chatbot UI designed for purchase order approvals. Yet queries like order status, shipment status, stock availability, stock price, supplier status, and contact details can be deployed in chatbots. A chatbot can alert the users for approvals of purchase orders and sales contracts to take appropriate action instantly.
If you want to learn more about AI applications from different industries and departments, feel free to check our research articles:
- 100+ AI Use Cases / Applications
- 12 AI Applications in Manufacturing
- 15 AI Applications/ Use Cases / Examples in Logistics
- 15+ AI Applications / Use Cases / Examples in Finance
You can also check out our list of AI tools and services:
And if you still have questions regarding AI procurement, don’t hesitate to contact us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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