Brighterion recently surveyed more than 200 financial institutions across the U.S. with assets ranging from $1 billion to more than $100 billion to determine how AI and machine learning are being used in the financial services industry. According to our findings, adoption of AI and machine learning is admirably high, with many financial organizations working to implement the technology to more effectively service their customers, manage new and ongoing investments, combat fraud and augment their workforce. However, our data also indicates that few financial organizations are successfully leveraging AI to the full extent of the technology’s power.

Too often, financial organizations fail to recognize the stark differences between various supervised and unsupervised learning technologies, and many neglect to consider which AI and machine learning functions are best suited to specific business objectives. To realize the full potential of AI and make the most of such a substantial technological investment, financial organizations need to resist getting swept up in the collective AI hype and instead focus on the technology’s most fundamental capabilities.

Check out Dr. Akli Adjaoute’s recent piece in Banking Exchange to learn more about what true AI technology includes and how financial organizations of all sizes can realistically incorporate AI and machine learning to power large-scale, hyper-personalization.