What is generative AI used for?#
It helps by automating or assisting in the creation of this content, dramatically increasing productivity and enabling employees to produce high-quality work faster. This allows businesses to scale content production, accelerate innovation, and explore new creative ideas without a proportional increase in headcount.
How does generative AI work?#
Generative AI systems are "trained" by analysing massive amounts of existing data—for instance, much of the text on the public internet, or millions of images. During this training, the AI learns the intricate patterns, styles, and statistical relationships within the data. Mostly it internalizes the rules and structures that govern the data rather than storing the data itself — though models do memorise some of what they see, particularly examples that repeat across the training set, which is why generated output can occasionally reproduce a source closely.
When a user provides a prompt, like "write an email about our new product," the AI uses its understanding of these learned patterns to generate a response. It predicts the most probable next word, and then the word after that, and so on, building a completely new piece of text that matches the request. The same principle applies to creating images or computer code; it assembles the final output piece by piece based on the statistical likelihood learned from its training data.
How is generative AI different from predictive AI?#
Generative AI creates new content, whereas most other AI systems are used for analysis and prediction. For example, a traditional AI might analyse customer data to predict which clients are likely to leave (a classification problem). In contrast, Generative AI could be asked to write a personalized email to a customer at risk of leaving, creating something that did not previously exist.