Generative AI is making waves in the world of accounts payables, and it's not just a passing trend. This technology is revolutionizing how we analyze purchase invoice data, and the potential benefits are enormous.
First off, let's talk about the treasure trove of information hidden in those purchase invoices. Every invoice a company receives from its suppliers is packed with essential data that often goes underutilized. Imagine being able to mine all that data to understand everything the company is doing and how well it's performing. Controllers can make better decisions by quickly calculating important KPIs or comparing the margins between different products. A great example is using AI to check all company transactions for tax compliance, making sure everything is accurate and follows the rules. Also, cost center owners, who are not always professional buyers, might need help too. How powerful it would be to have a spending assistant that could guide them in managing their budget effectively?
"Every invoice a company receives from its suppliers is packed with essential data that often goes underutilized."
The challenge, however, has been the sheer amount of unstructured data. If the data is only in invoice pictures, it's not in an understandable format. This is where Large Language Models (LLMs) come into play. Instead of trying to categorize every word in the invoices or drawing boxes around the necessary data, LLMs can understand the invoice data semantically. They can make sense of the data in a way that traditional methods can't.
But there's a flipside. AI is incredibly powerful at mining all the information in invoices and analyzing it beyond normal measures. This means our invoice data becomes sensitive information. For example, how could this information be used in phishing? What sensitive information can AI uncover that we don't see ourselves? Some real-life examples include instances where regular electricity bills have been used maliciously to reveal governmental locations. Delivery records to different addresses can also be revealing, especially when considering the content of the deliveries. Generative AI could probably figure out the KFC recipe and Coca-Cola's syrup content without breaking a sweat.
Despite these concerns, the potential of generative AI in accounts payables is immense. It can help increase profits by identifying gaps, prevent fraud through deep analysis, and even assist in ESG reporting, which is notoriously difficult to gather data for.
In conclusion, generative AI is not just a buzzword; it's a game-changer for accounts payables. By leveraging this technology, companies can unlock new levels of efficiency, security, and insight. So, let's embrace the future and see where generative AI can take us!
