Let’s take a closer look at one thing at a time:

Artificial Intelligence — the ability of an application to mimic human intelligence to the level at which it is difficult to distinguish between human and machine.

What is artificial intelligence in Procurement:

AI is automating or improving many time-consuming tasks or giving Procurement experts additional insights based on extremely complex and large sets of data. In simple terms, AI is simply a software solution aimed at resolving a specific task.

What is not artificial intelligence in Procurement:

chrome or plastic –plated sentient being as you see in movies. AI is not a magic solution you can tap to solve your problems. All AI solutions today in Procurement will require active expert guidance and oversight.

For what it is useful?

Artificial Intelligence algorithms can be used for the verification of users’ purchase requests and determination of the most relevant recommendations of profitable positions in real-time. With the help of AI algorithms, it is possible to analyze larger amounts of data and offer the most relevant solutions for traditional problems. What is more, AI has all power to determine more accurately and somehow hedge credit or counterparty risks.

Machine Learning is a method of letting an artificially intelligent application figure out the steps needed to accomplish a specific goal, instead of being given step-by-step instructions to perform.

For what it is useful?

Machine Learning can be used for e-planning includes the analysis of needs, sourcing planning, and source plan management.

Data Mining & Analysis — the practice of examining large pre-existing databases in order to generate new information.

For what it is useful?

Data mining allows detecting unpredictable patterns hidden in the data generated during users’ routine operations for improving the level of their effectiveness.

Smart interaction with suppliers and AI approval of this process minimizes the role of the buyer in the system reducing the risk of a human-made error to the minimum.

3 Silver Bullets of AI for Procurement and Supply Chain

And now let’s go deeper a little bit and explore more narrow and complicated things (but the most important!).

So, there are currently several major AI-based offers for strategic use in the procurement and supply chain. Let’s look at the basics of procurement automation, which are possible using AI:

• Data Classification methods will provide a source of information for determining ideal prices and make benchmarking and comparison a reality. AI has a wealth of data on suppliers, materials, products, etc. and about processes and therefore can easily provide user companies with accurate business data and increase the transparency of costs, with a high level of automation.
• Data Clustering methods allow you to combine and intelligently compare data for all benchmarking categories for the entire enterprise or do it separately, for prices and suppliers. By doing this, companies can obtain data on the most preferred areas for automating business processes or for making changes within individual work processes. These methods can also provide a solid foundation for more advanced analysis methodologies (for example, for linear evaluation of effectiveness).
• Verification and reconciliation algorithms can automatically determine critical errors of data and key performance indicators (KPIs), thus providing accurate information that is essential for determining the effectiveness of procurement processes, calculating valid benchmarking results, and maintaining a history of price changes, which greatly improves efficiency analysis, measuring the effectiveness of processes and can lead to significant savings.

If you want to establish your own AI expertise make sure your team uses these methods.

The Secrets to a Successful AI Strategy

# 1 Cost analytics

Cost analytics collects, cleans, classifies and organizes all cost data, helping purchasing departments identify excessive costs. For example, AI systems can determine when different companies bought the same goods from a supplier, when the best deal was completed or when payment for goods shipped expired.

To see what you can save on, the software will classify the data. Isn’t it perfect? AI methods often fail when working with on-time deliveries or suppliers with which the company does not cooperate constantly, but from time to time. Distractions for AI systems: unfamiliar language or new geolocation. Such problems are more often faced by companies that are constantly expanding their sales geography.

In this case, the best method of return on investment is the use of intelligent systems that can analyze large volumes of transactions, including standard re-purchases.

# 2 Search for sources of supply

Using AI, purchasing managers can equip oneself with knowledge of current market conditions, upcoming mergers, and acquisitions, as well as product comparatives and real-time support. This ensures that the purchase will be made in the best conditions for the company. The use of AI technology reduces the time required to analyze all supporting data. For example, analysis of the response to submitted applications is accelerated by 80%. The AI ​​is also looking for suppliers upon request. Subject to these conditions and, therefore, upon receipt of the necessary goods, the company will enter the market much faster.

One type of process optimization — managing the purchase. It allows you to quickly purchase goods or services and preferred suppliers with minimal time spent on procurement staff. Voice commands are used to find the best price or supplier that can fulfill an urgent order. Many of these systems provide direct communication with suppliers according to strict rules governing the process following the procurement policy.

# 3 Contract analytics

Most organizations do not have a database containing all contract data, and they need a simple way to extract such information. If the company uses AI, it will view contracts faster, and also accumulate large amounts of data about it, to significantly reduce the likelihood of disputes and increase the number of successful transactions.

The advantages of contract analytics (software for concluding contracts) — it helps companies fulfill the conditions of contracts and more quickly identify cases of non-compliance.

And although the AI ​​systems used in procurement and supply chain today are not perfect, the pace of development of machine learning is constantly growing. The platforms are improving with cosmic speed. So, it is likely in the coming years, AI will become a more reliable tool for the procurement process.

Takeaway: AI and The Future of Procurement

Artificial intelligence, machine learning, data mining — these cutting-edge approaches and more will allow more efficient use of company resources in procurement and the supply chain during the following 5 years. So, which areas will be affected by AI and how? Of course, AI won’t take procurement jobs but rather dives into P2P, sourcing, contract management, risk management, and innovation.

Let’s have a closer look at AI opportunities:

• strategic insight and foresight
• complete digitalization of purchasing
• automation of processes
• purchasing processes control
• delivery and counterparty risk management

Nowadays, procurement teams are understandably found under pressure to do more — not only in terms of greater savings but better insights, new sources of value, unexplored ways to drive even more efficiency. AI in procurement can become a perfect way of taking a measurable share of the burden.

But it is also important to remember one thing. It is impossible to simply introduce innovations in the system of the company. It is necessary, to correctly use these technologies by qualified personnel. This is the most important thing in order to get the desired result.

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