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 amount of data enables procurement teams to manage cost savings and supplier/vendor performance risk. 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. Which of the following is an example of using AI to analyze spend analytics? Artificial intelligence can automate various time-consuming tasks like invoice processing where the procurement team spends most of their time on receiving, reviewing, and paying the invoice. Machine-learning algorithms can be utilized to classify procurement spend into categories and sub-categories. AI-powered spend classification allows better analysis by enriching this data with external information from the web. AI can be used in 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. Chatbots