Artificial intelligence (AI) is transforming every sector and business function, resulting in a growing interest in it, its subcategories, and related areas such as machine learning and data science. 

While AI and automation might sound like the same concepts to many. But, in terms of procurement, both vary differently. Let’s find out how. 

Automation Vs. AI

Automation of procurement operations helps streamline the entire procurement process by relieving staff of time-consuming and repetitive activities so that they can focus on mission-critical tasks like decision-making and strategy formulation.

Whereas, AI in procurement might entail unprecedented levels of data and visibility into transactions, inventories, contracts, spending, financial analysis, suitable supplier identification, supplier onboarding, supplier performance, risk assessment, security, and so on.

Although more than half of the world’s supply chain, procurement, and financial experts indicate that their companies plan to spend heavily on artificial intelligence (AI) during the next two years – it cannot be a direct answer to all problems faced in a traditional procurement setup.

Know What’s Best for Your Procurement Team

Here are a few questions to ask yourself to know if your procurement team is ready for AI:

Question 1: Do I Have an Automated Procurement System in Place?

If your company is still operating on a traditionally-based procurement system that involves processing tasks manually, then AI is not for you yet. 

Let’s take these areas for an example: When it comes to procurement, automation of purchase requisition forms, purchase orders, and invoices involves companies creating an electronic purchase order, which the supplier receives, converts the information into an invoice, and delivers it digitally.

Take this automation to the next step, and procurement artificial intelligence (AI) might design the conditions of a new contract based on current data and previous patterns of the purchase orders and invoices, emphasizing areas that buyers should be aware of.

To blend AI into your procurement process, you’ll first have to digitalize all the procurement-related documents and be able to store your data digitally. Then you’ll have to automate these processes with the help of good procurement software to simplify the process further. Only then can you use AI and reshape the future of your procurement system.

If your company has already adopted a procurement automation system and successfully automated daily routine tasks. In that case, you are ready to take your procurement to the next level and incorporate AI into the system.

Question 2: Do I Have Enough Volume of Data?

The next question you’ll ask yourself is about the quantity of data involved in your procurement process. 

Data is procurement teams’ lifeblood; without it, they can’t track how much their company spends on products and services. 

Every day, terabytes of data are collected and stored. There are various internal and external sources, including employees, transporters, competitors, sales personnel, suppliers, and the Internet. 

For procurement teams, big data improves the visibility of expenditure, allowing them to manage cost reductions and risks associated with supplier/vendor performance. It’s also tough to track and manage supplier and vendor relationships without the data. 

Suppose you have enormous data gathered from different sources, but your procurement teams cannot make informed decisions using this data because of its complex nature. In that case, you can transform the stored data into meaningful procurement analytics using AI.

But if you are a small or medium organization that does not have enough volume of data or if your data is still primarily a manual process, which means you “pull” or extract the data you want, then forget about using AI – for the moment. 

Data processes must be completely integrated and automated to benefit from AI. Both complement each other and together provide invaluable information.

Question 3: Do I Need AI to Accomplish My Procurement Goals and Objectives?

To answer this complex question, you first need to identify what your procurement goals and objectives are. Different organizations have multiple goals depending upon the status of their processes and changing external or internal environments. 

If your processes are mostly executed manually or involve greater human interaction, then your goal may be to make these processes more efficient by automating the repetitive tasks. Your organization could be on its way to complete digital transformation for which you might need to ensure that each and every process in your procurement cycle is automated. 

It takes years for an organization or a department even to fully transform itself digitally. Instead of jumping to the next big thing, take a step back, analyze what is really needed to achieve your goal.

If you think you have possibly eliminated every bottleneck with the help of automation, have a perfect procurement automation system, and are looking for more cost savings then you might be ready to explore AI.

AI can be used in the following areas of your procurement process only if it is needed:

Supplier Risk Management: If you already have control over your supply chain through vendor management software, you won’t need AI in your procurement process. Using Artificial intelligence in the procurement process can help procurement managers to track and detect possible danger points across the supply chain. If you are working in a stable market with minimum risk potential, procurement automation will serve your purpose. 

Contract Management: AI is also used to pick up and consolidate information from the contracts to help you find leverage. But if you don’t have various lengthy contracts and multiple suppliers, you can skip using AI.  

Anomaly Detection: Any spike or dip in the values that are being noted can be considered an anomaly. In simple words, any out of proportion value is an anomaly. If the chart is set to 100 and it is going to 120, then it is an alert for procurement managers that highlights the anomaly. 

If your procurement process does not have significant anomalies to detect, then you should stick to automation.

Vendor Matching: Machine Learning helps procurement managers connect the supplier data in the invoice and PO to the overall vendor hierarchy while a good procure-to-pay software may also help you achieve similar goals.

Capturing Supplier or Market Data: This helps the procurement managers to understand how the market is moving ahead, using NLP. Signals via the internet and social media can be used to intimate the user on which suppliers are in demand more. 

While automation will suffice if you are not concerned about external market development affecting your procurement operations.

Spend Classification: AI (unstructured machine learning) helps teams understand the classifications of their purchases. For example, analyzing millions of invoices to identify spending in different categories of cardboard packaging automatically.

If you think these and related processes are already running smoothly in your organization with the help of automation, then there is no need for AI in your procurement process.

Conclusion

According to a study, just 32% of procurement organizations have established a digital strategy, and only 25% have the necessary skills and resources. In contrast, nearly 85% of procurement organizations anticipate that digital transformation would profoundly impact the way they supply services in the next three to five years.

There is no doubt AI is the future of procurement and is here to stay, but it is necessary to implement it at the right time; otherwise, you won’t be able to harness its potential.