Artificial intelligence (AI), sometimes called machine intelligence (MI), is intelligence displayed by machines as opposed to the natural intelligence displayed by humans. The term is often used to describe machines or systems that mimic cognitive functions that humans associate with the human mind, such as learning or problem solving.
There are three main types of AI systems: analytical, human-inspired and ‘humanised’ AI. Analytical AI has characteristics consistent with cognitive intelligence, that is it uses learning based on past experience to make future decisions. Human-inspired AI has elements of both cognitive and emotional intelligence, so that it has a limited appreciation of human emotions and takes them into account in its decision-making. Humanised AI embraces cognitive, emotional and social intelligence, is able to be self-conscious and self-aware in interactions with others.
AI has become an established tool for companies aiming to drive growth and profitability: between 2017 and 20i8 McKinsey research found the percentage of companies using at least one AI capability in their business processes more than doubled, and nearly all those using it reported some level of value. However, AI does require careful management to prevent damage not only to brand reputation but more importantly to workers, individuals and society as a whole. There are many debates under way about the rights and wrongs of AI applications in areas such as autonomous weapons and surveillance systems.
The impact of AI on treasury is not always immediately evident, but it does have very positive implications for processes, structure and staff, including improving the quality of cash flow forecasts and the elimination of some expensive and labour-intensive manual processes. It can be useful in optimising cash management and hedging strategies, and it could also help treasurers to improve their procurement processes, supply chain management and sales forecasts.
In addition, AI is increasingly being used to replace legacy technology to ensure that trades, customers, suppliers and the company itself are compliant with current regulation – there can be hundreds of tax and legal updates in just one week across an international network. By treating regulations as data, AI brings compliance into the enterprise risk management environment, enabling treasurers to take a properly risk-based view of regulatory compliance. As they get ever smarter, AIs will begin to look at the corporate landscape in entirely new ways – and they have the potential to redraw the map of how the financial sector works, including the treasury function.