Written by Marijn Overvest | Reviewed by Sjoed Goedhart | Fact Checked by Ruud Emonds | Our editorial policy

How to Apply AI in the Procurement Process

AI is transforming procurement by making it faster, smarter, and cost-effective. Whether it’s finding suppliers, negotiating contracts, or managing relationships, AI helps automate tasks and provide data-driven insights to improve decision-making.

Here’s how AI is applied to the 7 stages of the procurement process:

1. Sourcing Methodology

Traditionally, before you choose a supplier, you need to research, analyze, and compare different options to ensure you find the best fit for your procurement needs. This process takes weeks of manual work. 

AI automates this process by scanning global supplier databases and analyzing factors like pricing, quality certifications, past performance, and financial stability, allowing you to identify the most suitable suppliers within minutes rather than weeks. AI also uses predictive analytics to assess potential supply chain risks such as supplier’s likelihood of delays, financial instability, or raw material shortages. 

Moreover, AI-powered chatbots streamline communication by reaching out to suppliers, collecting necessary data, and answering procurement related questions which significantly save time and effort. 

2. Market Research

Market research is a crucial step in procurement, as it helps businesses understand supplier availability, price trends, and potential supply chain disruptions. In a traditional setting, this process requires you to manually analyze market reports, industry news, and supplier data which is time-consuming and prone to human error. AI improves this process by continuously tracking pricing trends, supplier performance, and geopolitical events that may affect procurement. 

Using natural language processing (NLP), AI also helps scan thousands of industry reports, news articles, and industry updates to extract relevant information in real-time. Additionally, AI-based demand forecasting further strengthens market research by predicting future supply and demand trends, allowing organizations to plan ahead and avoid stock shortages or excess inventory. 

3. Request for Information (RFI)

RFIs help procurement teams gather essential data about potential suppliers before making a decision. However, manually sending RFIs, tracking responses, and evaluating supplier details can be a slow and complex task. 

AI simplifies this by automating RFI management, instantly sending RFIs to multiple suppliers, and compiling their responses into a structured report. Machine learning algorithms then evaluate and rank suppliers based on their reliability, compliance, and past performance to help you choose the best ones. 

AI also summarizes supplier responses in an easy-to-read format, helping procurement managers make quick but informed decisions. 

4. Request for Quotation (RFQ)

After gathering supplier information, the next step for you is to request pricing details and compare multiple supplier offers. Traditionally, this requires you to manually send RFQs, collect responses, and evaluate quotes based on various factors.

AI automates this process by instantly sending RFQs to multiple suppliers and organizing responses into a structured format. It then uses intelligent quote comparison tools to evaluate pricing, delivery schedules, payment terms, and past supplier performance, highlighting the best option for you. 

AI-powered price prediction models further enhance decision-making by forecasting future pricing trends, allowing your company to decide whether to lock in current rates or wait for potential cost reductions. 

5. Negotiation Phase

Negotiation is one of the most important steps in procurement, as it determines the final pricing, terms, and conditions of a supplier contract. In a normal procurement, to negotiate better deals, businesses rely on past experiences and manual data analysis that can be time-consuming and inconsistent. 

AI enhances the negotiation process by analyzing past contracts, supplier behavior, and industry pricing trends to suggest the best negotiation strategy. AI-powered predictive analytics can also anticipate how a supplier is likely to respond to price reduction requests, allowing you to negotiate with confidence. Additionally, AI chatbots can help you during negotiations by suggesting talking points, potential counteroffers, and key concessions that can help you secure a favorable deal. 

6. Contracting Phase

Once a deal has been reached, contracts need to be reviewed, signed, and continuously monitored to ensure compliance. Manually managing contracts is a tedious process, that often leads to errors, missed deadlines, or hidden financial risks. AI can help in this process by automatically scanning the contracts to detect missing clauses, non-compliant terms, or hidden cost escalation conditions. 

Smart contract storage and tracking systems powered by AI also help organizations keep track of key deadlines, renewal dates, and supplier obligations by sending automated alerts when action is required. AI-based risk detection further ensures that businesses are protected from financial penalties or legal disputes by identifying contract vulnerabilities before they become an issue. 

7. Supplier Relationship Management (SRM)

After a contract is signed, ongoing supplier relationship management is crucial to ensure consistent quality, timely deliveries, and long-term business partnerships. Normally, tracking supplier performance requires manual record-keeping and periodic audits, which can be again time-consuming and inefficient. However, AI can continuously monitor supplier performance by analyzing key metrics such as on-time deliveries, product quality, and overall service levels. 

AI-powered predictive risk analysis also helps identify potential supplier failures before they happen, allowing you to take proactive measures and avoid disruptions. Additionally, AI-driven supplier relationship management tools like GEP Smart, Jaggaer, and Medius suggest collaborative opportunities with top-performing suppliers to strengthen long-term partnerships.

How to Get Started With AI in Procurement?

Implementing artificial intelligence (AI) into procurement is an exciting prospect that demands careful planning and innovative thinking. Here are some helpful tips to guide you in adopting AI in your procurement process:

1. Begin with small steps

Integrating AI into your procurement processes might seem overwhelming, so it’s wise to start small.

AI like ChatGPT, Claude, Gemini, or Perplexity. However, for starters, we recommend ChatGPT as it is more easy to use.

You can use ChatGPT by asking it to make RFQs, RFIs, or RFPs that will enable you to streamline your process when it comes to these documents. It can also be used to answer a wide range of procurement-related questions including the definition of terms, regulations, and best practices in procurement.

Moreover, chatGPT can assist with negotiation simulations. To start, simply ask it for a negotiation prompt. Once you do, it will ask for more details on the topic you’d like to negotiate.

It’s important to note that clear prompts are key for ChatGPT to provide better responses. Our AI Prompt Engineering for Procurement Course will teach you how to craft effective prompts, helping you make the most of generative AI tools like ChatGPT in procurement.

2. Select the right technology

Not all AI tools are the same, so it’s crucial to choose one that aligns with your specific procurement needs and can seamlessly integrate with your existing systems. Prioritize technology that caters to your unique business requirements.

Avoid getting caught up in the hype of trendy AI tools; instead, focus on selecting the one that genuinely suits your needs. This choice is vital for unlocking AI’s full potential and gaining a competitive advantage.

3. Emphasize data quality

Data is the lifeblood of AI. To ensure AI operates effectively, maintain accurate, up-to-date, and consistent data. Quality data fuels AI-powered procurement processes, enhancing efficiency and enabling informed decision-making.

By prioritizing data quality, you can maximize the benefits of AI technology and deliver greater value to your organization.

To help you craft your own prompt to maximize AI tools like ChatGPT in Procurement, try our Prompt Engineering tool.

Best Practices of AI in Procurement

To further narrow your search as a Procurement professional you should know the best practices of AI in our field specifically. Here is a list of AI’s best uses in procurement below.

1. Start it on existing processes

AI is not some kind of magic that can automatically grant your desires in the procurement process.

The value of AI in your process will not come from new applications but by integrating it into your menial tasks that consume too much of your time.

You can also embed it into your spending analysis and contract management to improve these processes.

2. Capture all procurement data you can gather

You should start collecting data even if your data quality is not yet perfect. The key is to gather data as much as possible because it can help you interpret the data you have collected.

3. Experiment with it

AI has improved in a lot of ways in the procurement process. But, there are still many things that have not yet improved.

Allow your AI technology specialist to experiment with ways to help your procurement processes. Make allowance for mistakes. After all, that is when you will learn.

4. Enable collaboration

You must know that AI demands the active support and guidance of a procurement professional.

You should plan for human and machine collaboration. Do not replace your team with AI. Instead, use AI to increase the expertise and productivity of your team.

The Benefits of AI in Procurement

The following are some of the benefits that you can gain by implementing AI in your procurement process:

1. Cost optimization

Through improved supplier selection, contract management, and demand forecasting, it enables organizations to negotiate better deals, curtail uncontrolled spending, and realize significant cost savings.

2. Scalability and adaptability

AI systems can efficiently handle large data volumes and adapt to evolving business requirements and market dynamics, scaling to accommodate growth and delivering real-time insights for agile decision-making.

3. Continuous enhancement

AI systems continually learn and improve through machine learning algorithms, identifying patterns, trends, and anomalies to enable ongoing optimization of procurement processes and outcomes.

4. Streamline operations

Its ability to automate manual tasks boosts efficiency, accelerates processes, and reduces administrative burdens, allowing your procurement team to focus on strategic activities.

5. Improved risk management

It can proactively detect patterns of fraud, assess supplier financial stability, and identify potential disruptions in the supply chain, allowing organizations to take preventive measures and safeguard against operational and reputational risks.

The Challenges of AI in Procurement

Although AI has a lot of benefits, many companies may also face the following challenges when implementing it in procurement:

1. Data challenges

Artificial intelligence heavily relies on data quality and availability, and the scattered nature of procurement data can pose a challenge. To counter this, you must know how organizations can enhance data quality and ensure its availability.

2. Overcoming resistance

The successful implementation of it in the procurement process requires overcoming resistance to change and addressing fears of job displacement. You must learn about strategies to foster a positive mindset and gain buy-in from procurement professionals.

3. Building AI Expertise and skills

Effective use of artificial intelligence in the procurement process needs a skilled workforce. Thus, you must invest in upskilling and reskilling initiatives and provide training programs that can equip procurement professionals with the necessary expertise.

Procurement Expert’s Advice on AI in Procurement

For this article, we asked an experienced procurement expert to share her insights to help answer common questions about using AI in procurement.

The Different Subsets of AI

AI is an umbrella term for numerous computational strategies. In this section, we are going to tell you some of the subsets of AI.

1. Machine Learning (ML)

Machine learning is an algorithm that detects patterns. The detected patterns are used for prediction or decision-making in the procurement process.

2. Robotic Process Automation (RPA)

This algorithm copies human actions to reduce repetitive simple tasks. Although RPA offers many opportunities for procurement to improve, it should not be considered AI.

Think of RPA as a software robot that copies human behavior while AI is the simulation of human intelligence.

3. Natural Language Processing (NLP)

Natural language processing is an algorithm that interprets, generates, and transforms human language. It can also analyze and understand the human language. 

Myths Surrounding AI in Procurement

Myths make their daily rounds on weary ears every day. But as a good procurement professional, you should know better than to listen to things without facts to back them up.

Here are some of the myths about it that you may have heard of.

1. AI will replace humans

Many people fear that they will lose their jobs when AI is implemented. This fear is genuine and understandable but this is far from the truth. However, it can be offset by redirecting these people into other sectors that will contribute more to the organization.

It can perform many things but it cannot replace the cognitive and emotional intelligence of a human.

2. AI requires great effort to adapt

We know that letting go of something that you are used to is so hard because we have been there. But you must remember that all new things you will pursue require great effort to master which is also true in procurement.

No one can deny that the initial step is hard. But once it has been employed, over time you will adapt it and you will see AI’s efficiency in the procurement process.

3. AI is time-consuming and expensive

AI can be expensive but over time you can see how it can reduce costs in the procurement by streamlining the procurement process.

To answer if it is time-consuming, it is with great confidence that we can say no. As a matter of fact, one of the benefits of AI is to eliminate time-consuming tasks in your procurement procedure.

Do You Want to Learn More About AI in Procurement?

AI integration in procurement is gaining momentum, and you don’t want to miss out on leveraging it to your advantage. Explore our popular courses on how to effectively use AI in procurement:

1. ChatGPT and AI in Procurement Course

The first module of our ChatGPT and AI in Procurement Course offers a foundational understanding of artificial intelligence (AI) and its applications in procurement.

It covers the basics of AI, the role of natural language processing (NLP) in ChatGPT, and provides an overview of the procurement chatbot market.

It highlights the benefits of using ChatGPT in procurement, offering insights into how this technology can streamline processes and improve efficiency.

By the end of the first module, you will have a solid grasp of AI and ChatGPT fundamentals, along with a clear appreciation for their potential impact on the procurement industry.

Visit our page to learn more about the contents of our ChatGPT and AI in Procurement Course!

2. AI Prompt Engineering for Procurement Course

In the first module of this course, you’ll develop a solid understanding of how to communicate effectively with AI by crafting well-structured prompts.

We’ll begin by examining the importance of AI in modern technology and the critical role prompt engineering plays in unlocking its potential. You’ll explore different AI models, and their functionality, and learn how to apply core principles to create clear and effective prompts.

As we progress, we’ll dive into advanced techniques, such as simplifying complex tasks and systematically refining prompts to improve AI performance.

By the end of the first module, you’ll be able to apply prompt engineering concepts that enhance AI-generated outputs, empowering you to leverage AI effectively in your professional tasks and beyond.

Visit our page to learn more about the contents of our AI Prompt Engineering For Procurement Course!

Conclusion

To sum it all up, the integration of artificial intelligence (AI) into procurement processes holds immense promise for organizations striving to stay competitive in today’s dynamic business landscape. However, successful AI adoption in procurement requires a thoughtful approach.

Additionally, you must remember that it is still in its early stages. Thus, you must be ready for any updates or changes that can be integrated into your existing system.

I have created a free-to-download, Productive Procurement with ChatGPT Toolkit template. It includes a PDF file that contains prompts that can help you streamline the procurement process and boost efficiency. I even created a video explaining how to use the templates.