Autonomous Procurement Agents: Hype or Real Value? 

Explore the real value of autonomous procurement agents, including benefits, risks, and real-world applications in decision-making and governance. 

Introduction 

Artificial intelligence agents are a work in progress. There is a lot of unhelpful hype clouding the discussion, and it is becoming exceedingly difficult to untangle the truth from all the falsehoods and exaggerated claims. So, let’s start with a definition. Agentic AI is like an AI with its own brain and initiative. It doesn’t wait for directions. It figures things out for itself, makes decisions, and takes action all on its own. It also learns from the results of its actions with a view to improving iteratively. 

If artificial intelligence relies on human prompts and inputs, it is not performing autonomously and it is not, therefore, agentic AI. If any person or organization tries to convince you that a software product that does not operate autonomously is agentic AI, then they are just using the term as a buzzword, hoping to surf the current wave of hype.  

Gartner also comments, “Many vendors are contributing to the hype by engaging in ‘agent washing’ – the rebranding of existing products, such as AI assistants, robotic process automation (RPA) and chatbots, without substantial agentic capabilities.” Gartner estimates only about 130 of the thousands of agentic AI vendors are real. 

Another way of putting it is that autonomous procurement agents enable computer systems to exhibit agency: set goals, make decisions and take actions through a perception, reasoning and action loop.  

If, on the other hand, a virtual assistant needs a human prompt to fetch some data, it is not agentic AI. It is generative AI. Nothing wrong with that but if someone is calling it “agentic” in order to promote it as something shiny and new, it is a fraudulent claim. And today, the claims are getting out of hand. 

That said, there are some applications which use agents that are not yet autonomous. This of course is a further complication! 

In this article we hope to show that if you look beyond the hype, autonomous procurement agents will, in time, become a real game changer. Agentic AI is already emerging as a powerful innovation in many areas of business, enabling a more dynamic and effective collaboration between humans and AI to enhance interactions with customers, suppliers, partners and other stakeholders.  

What are autonomous procurement agents? 

An AI agent in procurement automates specific routine tasks within the source-to-pay spectrum based on pre-set rules. However, autonomous procurement AI agents are more than just advanced automation tools. They are decision-makers that use artificial intelligence to understand data, learn from outcomes and continuously improve. An AI agent performs tasks autonomously, adapting actions based on context, data and behavior.  

This does not mean that such agents are 100% autonomous. They operate with fixed workflows that require manual configuration and updates, and some degree of human-in-the-loop intervention. Some human intervention is especially necessary in complex or high-stakes situations. As is the case with generative AI, agentic AI can be susceptible to errors, biases, and security vulnerabilities. 

Generative AI requires user prompts and training data. In procurement, for example, it requires a user to input a question or task (such as “Draft an RFQ for ball bearings” or “Create a supplier report” or “Draw up a draft contract with Supplier X”). It does not act unless explicitly asked to.  

Predictive AI, which is used in procurement to perform tasks such as on-time delivery predictions, risk scoring and trend forecasts, also requires human prompts before it can do anything. 

By contrast, the autonomous procurement agents will act without human prompts, using data and inferences to initiate and execute actions and its behavior is goal oriented. What is crucial to understand is that an AI agent makes decisions, learns and evolves workflows through interaction, feedback, and data patterns. 

Real-World Examples & Pilot Programs 

JAI (pronounced “jay”) is JAGGAER’s agentic AI platform. It will transform the way procurement works from source to pay. As mentioned above, it is a work in progress, but there are already some real-world successes. From supplier onboarding to payment, JAI acts as an intelligent, proactive partner for faster decisions, automated workflows and proactive recommendations. JAI is an embedded conversational chatbot powered by large-language models (LLMs), incorporating Q&A capabilities, PO invoice anomaly detection and Gen AI drafting and summarization with new, more powerful orchestration.  

Right now, it is more accurate to describe JAI as an intelligent copilot that provides conversational support to users. But there are some autonomous capabilities in JAI that can be used right now, such as initiating tasks for RFP creation and supplier evaluation. Later in the year JAI will offer agent orchestrators to handle tasks such as forecasting, spend management, cash flow management, contract management, and RFx automation. These are already being trialed in pilot projects. 

The underlying technology is MCP/A2A. MCP standardizes the interaction between LLM-based agents and external tools or APIs. Think of it as a universal way for AI agents to access and interact with data sources, tools, and instructions in a consistent manner. It provides the basic grammar for agentic AI communication, ensuring different applications can understand each other when accessing data, tools, and LLMs.  

Agent-to-Agent protocol (A2A) aims to create a world where agents, possibly built on different frameworks and by different vendors, can seamlessly collaborate. A2A is like universal meeting rules for AI, ensuring smooth collaboration and information exchange between different agents. 

This is the current state of the art and it provides the basis for the JAI Agentic Platform & Autopilot to be launched in 2026. JAI agents will enable truly autonomous procurement thanks to their ability to execute adaptive as well as deterministic workflows independently. Human users will act as high-level overseers and decision-makers. 

The benefits of autonomous procurement agents 

The benefits of autonomous procurement agents are numerous, but they can be arranged under four headings: the automation of routine tasks, enhanced decision making, increased efficiency and cost savings, and a shift to more strategic approaches to procurement. 

1. Automation of routine tasks 

Agentic AI can automate many time-consuming, manual tasks within procurement, such as purchase order creation and management, RFx initiation and management, and contract management. Gartner predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028. 

2. Enhanced decision making 

Agentic AI can analyze vast amounts of data to identify patterns and trends, leading to better informed decisions. This includes spend analysis, supplier performance evaluation, risk assessment and inventory management.  

3. Increased efficiency and cost savings 

By automating tasks and improving decision-making, the deployment of autonomous procurement agents can lead to significant efficiency gains and cost savings for procurement teams: less manual effort frees up procurement professionals to focus on more strategic work, such as developing long-term supplier relationships and negotiating complex deals. Agents can be deployed to identify opportunities for cost savings, improve supplier relationships and streamline procurement cycle times. 

4. Focus on strategic initiatives 

By automating routine tasks, autonomous procurement agents allow procurement teams to focus on more strategic initiatives, such as developing long-term sourcing strategies, building stronger supplier relationships, and driving innovation in procurement. 

The risks and challenges posed by autonomous procurement agents

Agentic AI poses many of the same privacy, security, and compliance challenges as other types of AI (such as guarding against bias, protecting individuals’ personal information, and avoiding the use of stolen data). Although — or rather because —agentic AI acts autonomously, it, in particular, requires human oversight. Agents can lack critical human-level understanding, context, and ethical reasoning. Human-in-the-loop oversight ensures accuracy, mitigates biases, prevents harmful outcomes, minimizes risk and helps the AI learn and adapt to complex situations.  

There are also a number of challenges to successful implementation of agentic AI projects. In fact Gartner estimates that around 40% of agentic AI projects will be cancelled by 2027. The main challenge arises with fragmented data and a lack of digital maturity. Agents can only function properly if they have access to high quality and current data, and they work within an existing technology framework (for example, JAI is a part of the JAGGAER One platform, having evolved from JAGGAER Assist).  

Other challenges include the need for a governance framework, skills gaps in procurement, resistance to change and cybersecurity and compliance risks. 

These can all be overcome, of course, but if an organization has a highly complex supplier ecosystem with poor visibility below top-tier suppliers, it will be difficult for agents to assess risks and opportunities holistically. 

The role of autonomous procurement agents in decision-making & governance 

Agentic AI offers significant potential to transform procurement processes, but careful consideration of governance, compliance, and ethical implications is essential to maximize the benefits while mitigating risks. Organizations need to develop clear strategies for implementing and managing AI in procurement, ensuring human oversight, data security, and adherence to ethical and legal standards. Although procurement agents can help overcome human biases, AI algorithms may also reflect and amplify existing biases in training data, potentially leading to unfair or discriminatory outcomes in supplier selection or contract awards. Ensuring transparency, accountability, and fairness in AI-driven procurement processes is vital to maintain public trust and avoid legal challenges. The legal and regulatory frameworks governing AI in procurement are still developing, requiring organizations to stay informed and adapt their practices accordingly. 

Will autonomous procurement agents replace humans? 

The short answer: no. The introduction of autonomous procurement agents will, for the foreseeable future, transform procurement jobs rather than eliminate them. The biggest impact will come through the automation of manual and repetitive tasks, and as we have already explained, there will always be a need for human oversight. 

The repetitive tasks that fill a procurement professional’s typical workday should, however, shrink substantially thanks to autonomous procurement agents, freeing up time for more strategic, and therefore more interesting activities such as category and supplier relationship management. While it is unlikely that procurement professionals will be fully replaced by AI agents, those who adapt and use AI agents may have an advantage over professionals who don’t use them. In fact, there may be a talent shortage as procurement needs to recruit people with the right skills. 

Here are three things that humans excel at, and AI cannot replace: 

• Emotional intelligence and trust-building – AI can analyze supplier performance and risk factors, but it can’t build trust, negotiate beyond logic, or foster collaboration that drives innovation. 

• Abstract and divergent thinking – AI can optimize decisions based on existing data but struggles with unconventional problem solving. 

• Strategic vision and business alignment – AI can process vast amounts of information but can’t inherently align procurement strategies with evolving business goals beyond what it has been trained on 

Key takeaways: is autonomous procurement really valuable? 

The short answer: yes. Autonomous procurement will bring great efficiencies and cost savings, and other benefits. Over time, procurement in its current, transactional form will become obsolete as autonomous procurement agents will take over routine tasks, driving down costs, achieving process efficiencies, and making companies more agile. But this will still require human oversight; meanwhile procurement’s strategic role will become more critical to competitive success.