Business leaders are excited about generative AI (gen AI) and its potential to increase the efficiency and effectiveness of corporate functions such as finance. A May 2023 survey of around 75 CFOs at large organizations found that almost a quarter (22 percent) were actively investigating uses for gen AI within finance, while another 4 percent were pursuing pilots of the technology.
That enthusiasm has been tempered by concerns over safety, privacy, accuracy, copyright, and social manipulation. In the case of finance, where numerical data and the accuracy of mathematical operations are fundamental, there is also concern over the possibility that gen AI systems could produce inaccurate or misleading information, a phenomenon known as “hallucination.”
To capture the benefits of these exciting new technologies while controlling the risks, companies must invest in their software development and data science capabilities. And they will need to build robust frameworks to manage data quality and model engineering, human–machine interaction, and ethics. Case examples in this article show how these technologies can accelerate and enable access to critical business information, giving human decision makers the information to make thoughtful and timely choices.
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