With so much written on Artificial Intelligence it’s hard to know where to look. However, there are companies from whom we can take our lead.
Artificial Intelligence (AI) is one of the hottest topics in business right now. It’s also a bit like teenagers and sex. Everyone seems obsessed with it, everyone feels left out, few actually know what they are doing, so everyone claims they are doing it.
There is so much hype about AI we recently collaborated with Procurious on a quick AI challenge for CPOs at the Big Ideas Summit in Chicago. From their savvy answers you’ll see that many procurement leaders understand the value of AI. What we need as a community is transparency on how it affects us here and now.
The new book AI in Procurement explores many realistic use-cases for artificial intelligence within procurement. The authors Sammeli Sammalkorpi and Johan-Peter Teppala were among the first to pilot AI solutions in procurement software and scoured much of the literature available today on the topic to write their book.
Don’t worry. We won’t get in to too many details about the mechanics and jargon of AI. Before we go through the examples from procurement, there is just one thing to understand.
Artificial Intelligence in Procurement
Many people have a somewhat distorted view of AI. They may remember futuristic movies where chrome-plated androids interact in human-like ways, or computer systems that have natural language conversations.
In reality, most AI applications today are a lot more boring and inconspicuous. You’re likely to interact with AI when you search for address details on Google Maps, or look up a playlist of music on Spotify. It’s already a part of the software you use every day, but you rarely see it.
This is much the same in business. Most of the applications of AI we see in procurement come as solutions to existing problems humans have a hard time solving. They are enablers, rather than replacements to human expertise.
AI in Procurement presents the concept of “human machine collaboration” to explain how AI builds on the strengths of both humans and machines.
7 Examples of Artificial Intelligence in Procurement in 2019
Now that we’ve covered the background, let’s dive into those fresh AI examples across seven different areas of the procurement cycle.
Supplier risk management
AI can be used to monitor and identify potential risk positions across the supply chain. For example, RiskMethods identifies new and emerging supply chain risk events by handling data gathered from different sources, helping to identify emerging risks faster.
AI can be used to automatically review and approve purchase orders. For example, it allows employees to order office supplies without requests for approval, making the process leaner and more efficient.
To state an example, in Tradeshift’s platform a chatbot called Ada can be used to check the status of purchases or automatically approve virtual card payments, regardless of the user’s location.
Accounts Payable Automation – Machine learning is increasingly used in accounts payable automation. ML assists in identifying errors and potential fraud in large amounts of automated payments. An example of this is Stampli, which leverages machine learning to speed up payment workflows and automate fraud detection.
At Sievo, machine learning algorithms are widely used in spend analysis to improve and speed up a number of processes, including automatic spend classification and vendor matching.
For example, if you have DHL, DHL Freight, Deutschland DHL, and DHL Express in your data, the machine learning algorithms are easily able to consolidate these together as DHL for increased visibility and data coherence.
Supplier Information Management
Big data techniques enable new ways to identify, manage and utilise supplier data across public and private databases. Tealbook is one platform that applies machine learning to supplier data in order to create and maintain accurate supplier records across all systems and areas of the business.
AI can also be used to manage, guide, and automate sourcing processes. Keelvar’s sourcing automation software uses machine learning for the recognition The reality of AI in procurement 59 of bid sheets and specialises in category-specific eSourcing bots such as raw materials, maintenance and repair.
AI has many potential use-cases in contract management. Seal Software uses optical character recognition (OCR) and advanced text analytics to clean up and consolidate information contained in contracts.
We’re likely to see many more successful examples of AI shared across procurement functions in the coming years. The more we share as a community, the better we get.
If you would like to dive deeper into the topic, you can get early access to AI in Procurement as a free download before the printed book comes on sale on Amazon in 2020.