Conversely, predictive AI makes predictions about future
Generative and predictive (also referred to as
events based on historical data. These models analyze
traditional) AI serve different purposes, but both are
past data to find trends or patterns that inform strategic
needed to advance an emerging program. For creative
planning and resource allocation. The most common
industries, generative AI can provoke thoughts and drive
applications include:
innovation; for data-driven or operations-focused
industries, predictive AI can help with planning and
•
Forecasting: Used in finance to manage risk, in
decision-making. But, for many industries — healthcare,
meteorology for weather forecasting, and in supply chain
fashion, tech, to name a few — combining both types of
management for demand forecasting.
AI can turn cutting-edge consumer behavior trends into
•
Risk assessment: In healthcare, it can predict disease
innovative new customer offerings.
outbreaks or patient readmissions. In finance, it assesses
credit risk and fraud detection.
•
Customer insights: In business, predictive models analyze
customer behavior and predict future buying patterns,
aiding in personalized marketing and sales strategies.
A Blueprint for CMO Success in the High-Stakes AI Marketplace
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