The advent of artificial intelligence (AI) has created a lot of noise. Many people have been afraid, and still are afraid, that AI is coming to take their jobs. But is this well-founded?
If we look at the past, new technologies have always taken jobs away—but it’s not as bad as it sounds! For example, we used to have people who would walk the streets every night to fill lanterns with oil and light them so that people could see in the dark. But seeing as street lights today are all connected to the electricity grid, these lantern lighters are out of work. But as we all know, electricity has led to countless new jobs since those darker times, and that’s a good thing.
Street lights do continue to fulfill the same solution (lighting the street), but the use of electricity makes it less labor intensive and more efficient. We see this happening with EDI as well; it’s not what it used to be, but the function remains the same, and that’s namely the electronic exchange of data. That being said, AI only makes EDI better at its core. It becomes less labor-intensive, more efficient, and so much more.
AI has had (and continues to have) a major influence on EDI. This influence has even extended beyond EDI exchanges to include advanced capabilities for other digital and paper documents, including, but definitely not limited to, PDFs sent via e-mail.
What Is Artificial Intelligence (AI)?
Artificial intelligence (AI) is a technology that is, quite simply, intelligent. By intelligent, we mean that it can learn, reason, plan, and correct, in an almost human way.
There are two primary categories of AI: General (Strong) AI and Narrow (Weak) AI. General AI is closest to human intelligence. This type of AI can learn and make decisions without human action. Narrow AI, in contrast, is especially good at performing one task and is not comparable to human intelligence. This type of AI, in general, is the most widely used. It’s also the type of AI used to enhance the capabilities of EDI.
The features of AI are shaping EDI in ways we could only dream of in the past. Namely, it allows for even less human intervention, taking the benefits of EDI to a whole new level.
But that’s not all. Below are just a few capabilities that AI adds to EDI:
Automation: AI detects patterns in data, like that of invoices, purchases orders, and so on. It ultimately enables automatic document entry and processing to reduce manual entry.
Validation: AI ensures that all data contained within an invoice is automatically verified by comparing it to other documents relevant to the transaction. This ensures greater accuracy.
Deviation Detection: If there’s a certain pattern, such as company address, and it deviates, AI can recognize this based on historical data and report on it.
What Is Machine Learning (ML)?
Machine Learning (ML) is a subset of AI that focuses on teaching computers how to learn without the need to be programmed for specific tasks. It combines large amounts of data and processes it with smart algorithms so that the software automatically learns the patterns and properties of the data, as well as specific human interactions. Basically, the software gets smarter and smarter as it is exposed to more data and human interventions. In other words, it learns and improves itself automatically by gaining experience.
Because of the patterns ML pick up on, the software can also make predictions based on historical data. This allows AI to create interesting and, better yet, useful predictive analytics that can be used in making strategic decisions.
If we relate this back to EDI, the main benefit is that machine learning further enhances the capabilities of AI by picking up on human interactions. To clarify, if a human repeatedly corrects a certain field on an invoice, ML technology will detect that interaction and begin to make the correction automatically. It also enables quick insights that can be used in, for example, inventory forecasting scenarios.
Going Beyond Electronic Documents
In addition to being able to apply artificial intelligence to regular EDI exchanges, AI can also be used to ensure greater accuracy when converting non-EDI documents into a particular format. For example, TIE Kinetix's solution, PDF-2-FLOW, uses AI and machine learning to reach 100% accuracy when converting PDF invoices to EDI, or any other type of format.
As machine learning technology has gained experience in its hosting software, it will start to recognize exchange patterns. For example, it will begin to recognize all invoice fields, such as account number, price per line item, and all other information that would typically be found on an invoice. ML then enables the software to read these properties and convert everything to an EDI format, or any other format you may need. AI then kicks in to ensure that all the data lines up with the original document and anything else that may be relevant in the transaction.
Another major benefit is that the AI and machine learning technologies incorporated in PDF-2-FLOW prevent the need to create a new mapping instance for every minor change in document structure. For example, if the company logo changes position on the invoice in a typical OCR (Optical Character Recognition) scenario, the model has to be retrained in order to provide accurate conversion. With AI and machine learning, the change is automatically detected. This prevents countless errors, as it is very common that a company doesn’t think to inform their trading partners when there has been a slight change in document structure.
And these are just a few examples. With further development of AI and ML, you can expect business solutions, such as those from TIE Kinetix, to only evolve. The best is yet to come.
This blog was written by Julia Reijnen, Marketing Specialist based in Breukelen, the Netherlands
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