Agentic AI in Procurement: Leveraging data, AI, and automation to drive process efficiency and unlock resources

Procurement is at the heart of modern business operations, directly impacting costs, efficiency, and competitiveness. With the rise of agentic AI, organizations have an unprecedented opportunity to optimize their procurement processes through intelligent, autonomous decision-making systems. According to Gartner, 33% of software applications will include agentic AI by 2028–a significant increase from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomously.  

In this blog, we’ll explore the transformative role of agentic AI in procurement, highlight practical use cases across key procurement areas, and provide actionable insights for businesses looking to harness the power of AI to drive efficiency and innovation.

‍

What are AI agents?

Agentic AI refers to advanced artificial intelligence systems that operate autonomously, learn, and adapt. Unlike traditional AI, which often relies on predefined rules, agentic AI dynamically adapts to real-time inputs and scenarios. They use techniques like machine learning, natural language processing, and advanced reasoning models to make decisions and execute tasks.  

‍

In short, AI agents are defined by three key characteristics:  

‍

• Memory: They remember inputs and outputs across tasks and changing conditions.  

• AI models: They dismantle problems into their smallest parts and define and execute actions against those.  

• Systems: They access external systems to retrieve or write information.  

‍

Different types of AI Agents

While no formal definition exists, we have organized AI agents into three categories, acknowledging that the lines can be blurry:  

‍

• Autonomous agents: Operate independently within predefined boundaries, executing tasks and interacting with external parties without human intervention.  

• Collaborative agents: Support and augment humans in their work by retrieving, organizing, and presenting relevant data and insights to improve efficiency and accuracy in decision-making.  

• Ambient agents: Operate in the background, monitoring their environment, offering proactive and context-aware support to enhance data accuracy, decision-making, and risk management.    

‍

Agentic AI in Procurement  

Procurement teams are facing ever-increasing requirements paired with a highly volatile business environment. Combined with the ongoing pressure on resources, this means procurement is expected to do more with less while being held back by manual processes, disconnected systems, and fragmented data.  

‍

AI agents can help procurement teams simplify, optimize, and automate complex processes and tackle challenges around data management, process compliance, and resource constraints.

‍

The key features that make agentic AI valuable to procurement include:

‍

• Autonomy: AI agents make independent decisions within defined guardrails, reducing the need for human intervention.

• Reasoning and real-time adaptability: Agentic AI can analyze situations, make nuanced decisions, and adjust strategies based on changing conditions.  

• Multi-step problem-solving: It can break down complex tasks into smaller steps and execute them autonomously.

• Integration with external tools: Agentic AI can interact with various data sources, APIs, and software tools to accomplish its objectives.

• Continuous Learning: Improves outcomes over time by analyzing historical and current data.

‍

Overview of AI agents in procurement  

These traits make AI agents especially interesting, where multiple agents can interact with each other to drive deeper automation along the end-to-end procurement process. Agents exist along the entire process chain of Procurement. Here are some agents that can support procurement.

‍

Plan-to-Strategy

During the plan-to-strategy phase, AI agents can automate spend and data analytics tasks, such as collecting market information and classifying data. Agentic AI can also identify cost-saving opportunities by analyzing historical and real-time procurement data and detecting anomalies in spending patterns, such as overpayments or non-compliant purchases.

‍

Examples of agents in Plan-to-Strategy include:  

‍

• ‘Stewart Data’, who cleanses and harmonizes data.  

• ‘Classy Taxonomy’, who classifies transactional data.

• ‘Richie Records’, who enriches supplier data with external information.  

• ‘Hunter Opportunity’, who detects savings opportunities from spend and pricing patterns.

‍

Source-to-Contract

AI Agents can be used to automate the RFP process, from bid solicitation to evaluation and negotiation. Using predictive analytics, AI agents can provide insight into the best negotiation strategies or anchoring points. Regarding Supplier Relationship Management, agents can evaluate supplier performance in real time, identify and mitigate risks, and streamline onboarding and contract management by automating document validation and compliance checks.

‍

Examples of agents in Source-to-Contract include:  

‍

• ‘Samantha Sourcing’, who can run tactical sourcing events alongside stakeholders, including supplier identification, quote requests, and proposal analysis.  

• ‘Natalie Negotiator’, who autonomously negotiates commercial terms with suppliers.

• ‘Peter Performance’, who monitors supplier performance and creates mitigation actions based on performance anomalies.

• ‘Claus Contract’, who redlines contracts and proposes alternative clauses and language.

‍

Procure-to-Pay  

Procurement teams can use agentic AI to automate purchase order creation, approvals, booking Goods Receipts and Service Entry Sheets, and match invoices to purchase orders to ensure compliance. It can also monitor external events, assess their implications on open orders, and initiate mitigating actions. Agentic AI can monitor inventory levels and trigger automated reorder requests to prevent stockouts.  

‍

Examples for agents in Purchase-to-Pay include:  

‍

• ‘Perry Turner’, who checks and completes PRs before turning them into POs.

• ‘Booker Sheets‘, who captures and writes GR & SES information against Purchase Orders.

• ‘Eva Payne’, who matches invoices to POs, checks for compliance, and processes them for payment.

‍

Benefits and challenges of agentic AI in procurement  

As procurement teams explore the adoption of agentic AI, it's essential to weigh both the advantages and potential obstacles. While AI can bring significant benefits, organizations must address challenges to ensure successful implementation.

‍

Key benefits

• Increased Efficiency: Automating repetitive tasks reduces manual effort and speeds up processes.

• Better Decision-Making: AI agents provide real-time insights, enabling faster, more accurate decisions.

• Cost Savings: Identifying spend inefficiencies, optimizing supplier contracts, and sourcing and negotiating tactical spend, directly impacting the bottom line.

• Risk Mitigation: Proactive monitoring of supplier and market risks increases supply chain resilience.

‍

Challenges to address

• Data quality: Inaccurate or fragmented data scattered across multiple systems can result in unreliable AI outputs and flawed recommendations.  

• Integration complexity: Agentic AI requires seamless integration with existing procurement systems, such as ERP platforms, supplier databases, and contract management tools. Achieving this can be technically challenging, especially if an organization’s systems are abundant or siloed.  

• Change management and skills gaps: Procurement professionals often lack the technical expertise required to engage with or interpret AI-generated insights effectively. Resistance to change and insecurity about the role of the new co-worker needs to be carefully managed.  

‍

Building AI agents on our Procurement Automation Platform

Procure Ai reimagines enterprise procurement with an AI-powered Procurement Automation Platform. By combining Generative AI, advanced predictive analytics, and autonomous execution, we build AI agents for Procurement that streamline operations, reduce operational risks, maximize cost savings, and automate processes end-to-end.

‍

By orchestrating advanced AI/ML models and GenAI on a secure and connected platform, we can build AI agents that cover a broad spectrum of tasks along the source-to-settle Procurement process. Our agents support the standardization of spend and supplier data across systems, identify savings opportunities in spend analytics, guide stakeholders through compliant buying experiences with Intake Management, autonomously execute tactical sourcing events and negotiations, and provide predictive insights to operational teams.  

‍

By eliminating administrative tasks, we enable CPOs to grow their team with AI agents and reassign scarce resources to strategic opportunities. With an emphasis on seamless adoption and user-centric design, we enable procurement to tackle the complexity and harness the full potential of AI. Customers like EnBW, Kärcher, and DMG Mori report 37% reduced order processing times, 47% faster award decisions, and 4.6% average savings in tail spend negotiations.

‍

Take the next step toward Procurement automation

Integrating agentic AI into procurement marks a paradigm shift in how organizations think about their workforce and manage their purchasing, sourcing, and supply chain processes. From automating routine tasks to providing strategic insights, agentic AI empowers procurement teams to achieve unprecedented levels of efficiency and cost savings.

While adopting agentic AI requires overcoming challenges around data quality, AI literacy, and managing change, collaboratively designing a roadmap against desired results will ensure organizational readiness. Organizations that are unsatisfied with their status quo should invest in agentic AI to tackle the complexity in procurement - today and tomorrow. It will give them a competitive edge in an increasingly dynamic business environment.

‍

Are you ready for AI in procurement? Contact us to learn how we can help you turn pressure into progress with our AI-powered Procurement Automation Platform.

‍