Artificial intelligence technologies have been used in procurement processes for quite some time. From demand forecasting to spend analysis, machine learning, natural language processing, and generative AI applications are widely adopted across various areas. However, most of these technologies are positioned as solutions that support a specific task or rely heavily on user input.
More recently, agentic AI has introduced a different perspective to procurement processes. These systems operate based on predefined rules and objectives, going beyond isolated analyses to take ownership of the entire process. In this article, we briefly review the types of AI used in procurement and examine where and how agentic AI is applied in procurement processes through practical examples.
What Is Agentic AI?
Agentic AI refers to artificial intelligence systems that can take ownership of a task from start to finish and execute it independently. While traditional AI applications require continuous user guidance, an AI agent interprets the current situation, identifies needs, and plans appropriate actions on its own.
An agentic AI system typically has the following core characteristics:
- Context awareness: It can gather data from sources such as the internet, ERP systems, or enterprise business applications.
- Planning capability: It breaks down complex problems into manageable steps.
- Autonomous action: It can interact with different systems to complete tasks end to end.
- Continuous learning: It uses each outcome to inform future decisions without requiring constant human intervention.
Types of Artificial Intelligence Used in Procurement
AI solutions used in procurement are not uniform. Each technology addresses a different need and plays a distinct role within the process. Some approaches focus on data-driven prediction and classification, others on understanding or generating text, while some are designed to manage more complex, end-to-end tasks.
1.Machine Learning
Machine learning algorithms are used to identify recurring patterns within large datasets and support decision-making processes. By operating beyond the limits of human analysis, these systems can detect relationships and trends that are meaningful for business decisions.
In procurement, machine learning models can evaluate historical purchasing data, supplier performance metrics, market movements, and many other data sources together. These measurable data points help decisions become more data-driven and enable more accurate demand forecasting. One of the most common applications of machine learning is payment process automation.
2.Deep Learning
Deep learning, a more advanced approach within machine learning, processes data through multi-layered neural networks. This structure enables the identification of complex relationships within large and unstructured datasets that are difficult to interpret using rule-based methods.
In procurement processes, deep learning is used to analyze unstructured content such as contract documents, bid files, invoices, and supporting attachments. Evaluating these data sources together reduces the need for manual review and improves process consistency.
3.Natural Language Processing (NLP)
Natural language processing (NLP) algorithms are designed to interpret, transform, and generate human language. They work with written and spoken expressions, analyze text, and extract meaningful information.
In procurement, NLP models are used in communications conducted through chatbots and virtual assistants. They automatically classify information contained in customer feedback, requests for quotation, and similar text-based sources, making this data usable within procurement processes.
4.Generative AI
Generative AI refers to models that learn from large datasets to produce new text and structured outputs. In procurement processes, these models are used for tasks such as comparing supplier data, creating pricing scenarios, and preparing pre-negotiation evaluations.
In contract management, generative AI is applied to drafting contract templates, identifying risky clauses, and monitoring compliance. Generative AI models can also be used for supplier risk assessment and supply chain planning by analyzing financial data, market movements, and historical performance records.
5.Agentic AI
Agentic AI refers to artificial intelligence systems that operate based on defined objectives and can independently advance multi-step tasks within procurement processes. These systems go beyond producing analyses; they assess context, evaluate decision points, and initiate the next step in the process. When a purchase request arises, supplier options are evaluated, order-related steps are shaped, and the process is monitored within this structure. Similarly, risk and compliance indicators are tracked based on contract terms and supplier data.
Use Cases of Agentic AI in Procurement Processes
Autonomous / Touchless Procurement and Order Management
In procurement processes, agentic AI operates in scenarios defined by rule sets and threshold values, handling steps that do not require human intervention. For example, when a demand arises, supplier data, price history, and delivery conditions are evaluated together to determine suitable ordering options. Based on this evaluation, an order draft can be created and forwarded to the relevant approval process.
Such applications are commonly referred to in procurement literature as touchless procurement or touchless procure-to-pay (P2P) processes. The distinguishing factor is not merely the automated progression of workflows, but the evaluation of decisions under specific conditions and the system’s ability to initiate the next step.
Proactive Risk Management
Agentic AI is used in scenarios where supplier and operational risks can be addressed at an early stage. Financial indicators, historical performance records, delivery deviations, and external signals are evaluated together to update risk profiles. When defined thresholds are exceeded, actions such as halting the process, introducing alternative suppliers, or triggering additional approval steps are initiated.
Contract Management and Compliance
In procurement processes, agentic AI is applied at specific stages of the contract lifecycle. Contract texts are reviewed against defined rules and reference conditions to identify risky clauses and compliance issues. As a result of these reviews, steps such as submitting the contract for approval, requesting revisions, or routing it to relevant teams can be automatically sustained.
Intelligent Procurement and Payment Automation
In procurement and payment processes, agentic AI is used in scenarios where invoice, order, and payment information are evaluated together. By comparing these data points, inconsistencies, mismatches, or unusual situations are detected at an early stage. Based on these findings, actions such as proceeding with payment, stopping the process, or initiating an additional review are determined.
A Comprehensive SRM Solution for AI-Driven Supply Chain Management: JetSRM
As the use of artificial intelligence expands across business functions, the way data is handled in supply chain management has also evolved. JetSRM began addressing this transformation in 2024 with its first AI solution a chatbot. Over time, this structure was expanded, and today JetSRM has become a platform that actively uses supply chain data across different processes through AI-powered modules, rather than merely recording it.
The AI modules used within JetSRM and their core functions include:
- JetNegotiation: Defines and automatically manages negotiation processes within the system.
- JetVerify: Performs accuracy and compliance checks on documents.
- JetInsight: Scans, classifies, and uploads documents into the system.
- JetAssistant: Accesses system information and answers user questions based on existing data.
Today, JetSRM places intelligent automation at the center of its approach, aiming to ensure that procurement processes progress without interruption and with minimal error. The Zero-Touch operating model, where manual intervention is removed from the process, is a natural outcome of this approach. JetSRM acts as a technology partner that helps organizations carry their supply chain structures from today into the future.
To manage your procurement processes in a smarter and more systematic way with JetSRM, contact us.
