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Everywhere we turn, the impact of digital transformation is evident and undeniable. Digital innovation has forever changed how we live, work, and connect, and the rate of this ongoing transformation appears to be accelerating each year.

Every day, many companies in various industries use ML and AI. Procurement is no different. AI procurement is now used by businesses to monitor supplier performance in real-time, identify risks, classify spending, and automate routine tasks like invoice processing.

Many market participants, though, are unaware of what AI procurement is and how it functions.

This guide is an excellent place to start. We will discuss all aspects of Artificial Intelligence in procurement, including definitions, benefits, examples, and applications. 

Brace up for a lot of learning!

What is AI in Procurement?

Procurement is locating, negotiating, and acquiring goods, services, or works from a third party, typically through a tendering or competitive bidding process. It entails making purchasing decisions in times of scarcity.

The use of cognitive and predictive technologies to automate and improve the sourcing process is known as Artificial Intelligence in procurement. It can lower risk while also enabling businesses to save time and money. AI can also optimize workflows, identify cost-cutting opportunities, and enable real-time decision-making.

Simply put, Artificial Intelligence in procurement refers to the use of computers to carry out operations that ordinarily require human intelligence, such as comprehending natural language and identifying patterns. Leading procurement organizations already use this technology to streamline operations and drive business value.

Use Cases of Artificial Intelligence in Procurement

There are numerous uses for Artificial Intelligence in procurement, despite the fact that this field is still in its infancy. Some of the most common applications are as follows:

Spend Analytics

Spend analysis is one of the most troublesome areas for procurement professionals. It is critical for your bottom line to ensure that your organization is managing risks and optimizing its purchasing power.

When identifying cost-cutting opportunities, AI can help businesses become proactive rather than reactive. Detailed spend analysis data is the foundation of effective sourcing, category, and spend management strategy. Spend data can be classified into functional, structured, and standardized classes using ML algorithms.

AI-generated data provides a more precise and detailed picture of an organization's spending.

Contract Management

Contract management is an essential component of the procurement process that must be handled correctly. Managing contracts from all essential business partners can be time-consuming and, at times, difficult due to the legal jargon and implications that must be sifted through. While contract management has been digitalized in some ways over the years, the process still requires human input and analysis.

Using NLP can help to simplify the process and allow businesses to automatically manage terms and conditions, deadlines, and anything else that needs to be monitored.

Data Analysis to Enhance e-Strategic Sourcing

Using NLP, AI can be used in strategic sourcing to gather critical data such as supplier lists. Using data and expenditure analysis, AI has changed procurement sourcing.

One of the primary functions of AI in procurement is sourcing optimization. This enables businesses to identify sourcing issues, such as.

⦁ Payment terms that are uncompetitive or unprofitable

⦁ Supplier duplication

⦁ Poor purchases

These issues could take several man-hours to identify without the use of AI.

Another way to use AI in procurement is to specify which markets you want to enter. The AI procurement software will forecast market prices, analyze and identify potential vendors, and assist you in evaluating existing suppliers. Because you can easily access all necessary data with a complete view of these processes, your contract negotiations will likely become more accessible and practical.

Finally, AI can collect real-time automated data weekly, daily, or hourly. This enables procurement managers to make more accurate and timely decisions.

Automation of Manual Tasks

The procurement process is filled with time-consuming tasks. Artificial Intelligence can automate manual tasks such as invoice processing, which requires time to receive, check, and pay the invoice. AI can also help with the procure-to-pay (p2p) process, which takes nearly a month to complete manually.

Guided Buying

Procurement is an integral part of every department in the average organization. Many employees tasked with this responsibility spend significant time dealing with routine tasks.

Negotiating better prices, establishing contracts, and locating suitable suppliers take time. And once completed, these processes are frequently discarded in some filing system that neither party has time or energy to pursue. Off-contract spending is a risk in this type of process.

AI aims to address this problem by providing guided purchasing, which directs every employee in the organization to the appropriate purchasing channels. Typically, the AI will include a set of questions in its algorithm. The user must respond to be directed to the appropriate procurement channel.

Managing Supplier Risk

Supplier risk management is a powerful application of AI in procurement. Artificial Intelligence can detect sudden changes in a supplier or vendor's behavior and determine whether the change increases or decreases the risk.

Traditionally, this process would be reactive, but with AI, the system can help you quickly weed out high-risk suppliers. You can easily avoid the headaches of continuing to work with these vendors or suppliers. As a result, AI has become an essential component of the modern e-sourcing strategy.

Inventory Management

Inventory management is an essential aspect of the procurement industry. Traditional methods are time-consuming and necessitate many human resources, which can be costly. Artificial Intelligence can determine which inventory practices are best for your company, allowing you to maximize your available storage space.

Error Detection

There are some mistakes that humans will always make. AI can detect errors or anomalies in your markets, such as price changes, compliance irregularities, and even fraud.

Benefits of AI in Procurement

We do not want to underestimate the benefits of AI in procurement. Artificial Intelligence has unparalleled capabilities. The following key areas are the most likely to benefit from AI in any business:

⦁ Supplier Relationships: AI can improve supplier relationship management and identify new suppliers.

⦁ Decision Making: AI provides businesses with accurate analytics and data-driven insights to help them make better decisions.

⦁ Operations: AI can help to streamline complex business operations while causing minimal disruption to existing infrastructure.

⦁ Manual Tasks: AI can automate manual tasks for better resource and time management.

⦁ Acquiring Data: Using AI, any organization can gain access to critical new data from external sources.

⦁ New markets: With AI, any company can quickly sift through massive amounts of data to uncover new opportunities worth investigating.

Top AI Companies in Procurement

Artificial intelligence (AI) advancements have transformed procurement, making it more efficient and effective. Today, numerous AI firms offer procurement solutions to businesses of all sizes and industries. Some of them are described below.

LevaData

LevaData is a supplier management platform powered by Artificial Intelligence that provides real-time insights into supplier performance, risk, and cost optimization.

Their platform assists procurement teams in making informed decisions by providing visibility into supplier performance and potential disruptions, allowing them to proactively mitigate risks and optimize costs.

Procurement teams can use LevaData to streamline their sourcing processes and drive more organizational value.

Tealbook

Tealbook is a supplier intelligence platform powered by AI that assists procurement teams in discovering, qualifying, and managing suppliers.

Their platform employs machine learning to provide real-time insights into supplier performance, risk, and compliance, allowing procurement teams to make informed decisions and reduce risks.

Tealbook's AI-enabled visibility and transparency enable procurement teams to streamline supplier discovery and management processes, reducing workload and improving decision-making.

Tamr

Procurement teams can unify and cleanse their data for optimal processes using Tamr's AI-powered data management platform. Their platform automates data unification by detecting and resolving inconsistencies and errors.

Tamr boosts procurement teams by improving data accuracy, allowing them to make more effective decisions by eliminating unnecessary spending and providing opportunities to increase revenue.

Icertis

Icertis' AI-powered contract management platform assists procurement teams in managing contracts much more efficiently. Machine learning is used by the Icertis platform to extract critical data from contracts, automate the contract review process, and provide real-time insights into contract performance.

The platform gives procurement teams a comprehensive view of all contractual obligations and rights, allowing them to make informed decisions and avoid potential risks.

JAGGAER

JAGGAER is a comprehensive procurement platform that employs artificial Intelligence (AI) to optimize the procurement process from sourcing to payment.

Their platform enables procurement teams to make data-driven decisions and drive greater value for their organizations by providing end-to-end visibility and spending control.

With JAGGAER, procurement teams can use cutting-edge AI to automate workflows, reduce workload, and improve the accuracy of their procurement decisions.

Successes and Challenges of Getting AI in Procurement

Successes

⦁ Task Automation: RPA has proven helpful in automating basic payment tasks. In addition, robotic automation has wholly transformed the manufacturing sector in the general supply chain industry. Recent advances in NLP, however, have aided in essential contract management, as well as virtual assistants and chatbots.

⦁ Risk Management: AI/ML technologies can be used to scrape, analyze, and interpret publicly available data, as well as internal data stored in ERPs (Enterprise Resource Planning) and other systems, and assign risk scores and actionable insights to procurement managers.

⦁ Spend Analysis: Accurate spend data is critical for sourcing and evaluating suppliers and overall procurement performance. According to Deloitte, AI technologies can analyze spend data with an accuracy of 97%. While other factors will influence accuracy, successful implementation, and oversight can yield invaluable results.

Challenges

As with anything else, there are some challenges or drawbacks of using Artificial Intelligence in procurement.

While they are not unmanageable, you must know them before jumping on the bandwagon.

⦁ Pure Complexity: Because AI is a complex technology, organizations may slowly adopt it in procurement. While it can assist procurement by delivering clean, well-organized data, the business still requires human experts to analyze that data and take appropriate actions based on it. According to industry experts, companies should engage in re-tooled hiring, which is hiring a new segment of expert professionals specifically hired to work with AI systems.

⦁ Trust Issues: Machines are taking over human jobs, and as a result, lives have been a source of concern for humans, mainly industrial workers, who are currently confronted with this issue. Understandably, modern workers will be skeptical of management when it attempts to implement new technology and automation because they are concerned about their future in the company. They may believe they have lost control and are concerned about their future.

Senior management and business owners are responsible for reassuring them about their job security. They should persuade employees of the advantages of implementing Artificial Intelligence in procurement and provide opportunities for employees to feel valued.

Future of Artificial Intelligence in Procurement

Despite the wave of digital transformation in various aspects of business, procurement remains a manual process in many organizations. Procurement managers used to negotiate with hundreds of vendors. The goal was to be as efficient as possible regarding inventory and cash outlay. This procurement process is streamlined by artificial intelligence (AI), which reduces human error to achieve the lowest cost and most efficient solution.

The goal remains to implement a pull system in which components for product creation are delivered at the same rate as consumer demand, avoiding costly inventory build-up and cash outlays. Experts predict that AI will significantly impact procurement activities in the near future.

⦁ AI can analyze large amounts of data, identify patterns, and then apply what it has learned to new data.

⦁ Allowing AI to do this should give procurement staff more time to focus on strategic tasks, such as identifying opportunities to improve operational efficiencies.

⦁ AI can also capture data and assist in making sense of it.

As a result, it is widely regarded as the most effective tool for revolutionizing procurement intelligence in the coming years. It can also integrate with various other systems, allowing data to be easily transferred and visible throughout the organization. Procurement can use this information to improve cash management.

Conclusion

Although the Intelligence is artificial, the results are real.

Aside from the hype, incorporating Artificial Intelligence in procurement processes will provide your team with the tools they need to support organizational goals while setting a new standard for transforming data into greater process efficiency, more substantial financial health, and a business foundation that is agile, resilient, and ready to take on all challengers in the new data-driven marketplace.