Leaders are often confused about when to use generative AI versus predictive AI (machine learning and deep learning) tools. The issue isn't that one technology is superior: It's about matching the technology to the specific business problem. This column presents a pragmatic way to help you make the best decision and avoid costly mistakes. The analytics landscape has evolved significantly during the past decade. Many organizations have progressed from basic statistical modeling to machine learning, and some have added deep learning to their toolkits as well. In this context, the emergence of generative AI ' with its ability to create humanlike text, generate images, and write code ' introduces new possibilities and new questions. While generative AI promises to revolutionize everything from customer service to product development, its optimal role alongside predictive AI tools (that is, machine learning and deep learning tools) remains a work in progress. That often leaves leaders...
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