By 2020, Gartner predicts that the use of artificial intelligence and machine learning will be pervasive. In 1983, Sting famously released his song "Every Breath You Take" and sung "Every step you take, I'll be watching you." And I'm not sure if the world has ever unanimously decided if we should be creeped out or feel safe when listening. In a lot of ways, I think that's the association that a lot of people have with Machine Learning (ML) and Artificial Intelligence (AI), especially when it comes to using this technology in daily life. But, there's nothing to be afraid of.

The Basware Assistant uses natural language processing and artificial intelligence to create a new and simplified way for people to interact with Basware's e-procurement solution. They can communicate with the Basware Assistant like they would with a person, to search for orders and purchase requests using vendor and item names, as well as ID and document numbers. By giving people the ability to specify what they are looking, it eliminates the need for having to navigate a series of screens to reach their intended purchase. Through its natural language processing and AI capabilities, the virtual assistant improves system usability, taking another step in streamlining the overall procurement experience. Not only does it help people find purchase orders and order requests more quickly and save them time, it also reduces the training required for new people to buy with Basware.

EW: When you're looking at overall technology trends within procurement systems, ERP systems or whatever kinds of enterprise systems these days, you're going to have to get your head out of the weeds of individual pieces of functionality and realize that the way of "tomorrow" is to be able to take advantage of these technology advances like AI, machine learning and even beyond that, prescriptive and predictive analytics, and pure benchmarking. But all of those technologies have data as a basic prerequisite -- and not just some data, but gobs and gobs of data because these machines can't offer predictive insights if they don't have tons of data to consume. They can't actually prescribe actions unless they have a full set of data on which to make those predictions. That's why we say the first thing you'd better be thinking about when considering enterprise systems (whether P2P or back-end ERP) is, "Can it and does it capture all of that transactional data necessary, and is it architected in a way that not only allows you to get value from your transactional data, publicly available data, as well as the transactional data from many, many other enterprises because that's where AI and similar technologies are truly going to provide a lot of value.