Generative AI is a type of artificial intelligence that is built to create new content, things like text, images, audio, or even code, by learning from examples in existing data. Instead of just analyzing or sorting information like traditional AI, generative models can actually produce original work. This ability powers tools like chatbots, image generators, and AI-driven marketing content creation.
Generative AI Defined
How to Use it in a Sentence
The marketing team employed generative AI to swiftly create personalized push notification messages for various customer segments, resulting in enhanced engagement and conversion rates.
Common FAQs
Traditional AI focuses on analyzing data to make predictions or classifications, such as identifying spam emails or recommending products. Generative AI, on the other hand, creates new content by learning from existing data patterns, enabling it to produce original text, images, or other media.
Yes, generative AI can be integrated into real-time applications, such as chatbots, virtual assistants, and dynamic content generation.
Marketers use generative AI to create blog content, social media posts, email copy, product descriptions, visual assets, and even ad creatives. It can also help personalize content for different audiences at scale.
Generative AI can save time, lower production costs, increase creative output, and support personalization efforts. It helps teams move faster by automating parts of the creative process that would otherwise take significant manual effort.
Predictive AI forecasts future outcomes based on existing data (like predicting customer churn), while generative AI creates entirely new content (like writing a blog post or designing an image) based on learned patterns.