It’s been a hot topic for almost every treasurer over the past year, but – hype aside – what is the true value of artificial intelligence (AI) within treasury? Nikolai Diekert, Director Product Management at leading TMS provider BELLIN, explores the concrete use cases for AI in treasury, providing a candid view on where the technology can add value and where it still has room for improvement.
Eleanor Hill, Editor, TMI (EH): Before we talk about AI in treasury, it would be helpful to clarify what AI is – and what it isn’t. Would you be so kind?
Nikolai Diekert (ND): Of course. You’re right – there are many contradicting and confusing definitions of AI. A good first step is to split the definition into ‘artificial’ and ‘intelligence’. What we mean by ‘artificial’ is that it is non-human, but created by people. While we tend to think of modern computer devices in this instance, analogue machines also fall into the ‘artificial’ bracket.
As for ‘intelligence’, there are even more definitions of this than there are for AI! But there is an interesting and useful definition on Wikipedia, which states that it is the ability to ‘perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviours within an environment or context’. Taking these elements together, AI can be viewed as any device that perceives its environment and takes actions that maximise its chance of successfully achieving its goals.
You also asked what AI is not, though, and this is very important. We often hear the words ‘machine learning’ (ML) uttered in the same breath as AI – but these are not one and the same. ML is a subset in the field of AI whereby algorithms build a model based on sample data and perform tasks or make decisions on real data without being explicitly programmed. The model is ‘trained’ on the sample data in various ways, supervised, unsupervised, reinforcement, self-learning and so on.