CFOs are uniquely positioned to lead a broader organisational shift into digitization. They have insight into all business units and can help leaders from every area of the organisation understand the why of finance data, not just the what — ultimately leading to smarter business decisions throughout the enterprise through the use of Artificial Intelligence (AI).
AI is quickly moving from the experimental to the operational. It is already being driven deep into the operating muscle of the enterprise – from predicting how competitors will react, to identifying which machines will need repair, and even forecasting best customers five years from now. The CFO is in a unique position to bring AI to the enterprise. He or she sits at a confluence of the most important data of the firm – operating costs from production, receivables from the customer, financial performance from the business units – that serve as the digital foundation of AI.
To date, most of the investments in AI for business have to do with specific industries; stock trading, portfolio management, banking and insurance underwriting. Customer development and customer service have also benefited from large investments in AI. The CFO responsibility areas, although ripe with automation, have not adopted AI to the extent these other industries or functions have. The opportunity is vast, but we need a methodology to identify where to start and continue our AI investment.
The main benefits to AI are derived from three aspects; speed, accuracy and volume. Identifying the value of these different variables is the key to selecting an appropriate AI strategy and developing a work plan to implement it. What many finance leaders recognize is that AI is more than another cutting-edge tool. By unleashing its full capabilities in finance and throughout the business, companies can turn it into a driver of differentiation that not only increases productivity, but also boosts growth. Within the finance function, for example, AI can be applied to replacing repetitive and labor-intensive tasks, performing such transactional work with increased speed and accuracy. Moreover, with its capacity to learn from large data sets, the technology can also be used to improve accuracy in such areas as budgeting and forecasting to enhance companywide decision-making.
We present to you “Top 10 Artificial Intelligence Solution Providers - 2020.”
