Generative AI is a type of artificial intelligence that uses billions of existing data points to produce (or "generate") new data and content. This includes sounds, music, voices, text, images, video, animation, 3D models, and code.
Generative AI is a technological breakthrough in two big ways.
First, it marks an innovation that sets it apart from predictive AI. Predictive AI typically uses smaller data sets than generative AI. While predictive AI analyzes subsets of past data to forecast future trends, generative AI is trained on billions of data points so it can create new information.
Second, generative AI makes working with machines more accessible to humans everywhere. Thanks to natural language processing (NLP), humans don't have to communicate exclusively in numbers or code with machines. Now humans and machines can communicate through written and spoken words, art, design languages, music, and so much more.
How does generative AI work?
When a user prompts a generative AI tool for new information, the tool mines the billions of inputs it's been trained on. It's looking for reference points, patterns, and structures it can adapt to produce (or reproduce as) new information. That's why the content it produces resembles the data that goes into the inputs.
As a user gives feedback on what's been generated by the tool, the AI uses machine learning (ML) to adapt and improve its output. It keeps generating content through trial, error, and incremental user feedback.
How do brands use generative AI as a differentiator?
Brands and other users turn to generative AI to help create everything from social media posts and product animations to content outlines and review management. The most common use of generative AI among marketers is:
Basic content creation (76%)
Writing copy (76%)
Inspiring their creative thinking (71%)
Analyzing market data (63%)
Generating image assets (62%)
As more and more customers turn to AI-driven search experiences like ChatGPT, Google's AI Overviews, and Bing Copilot, brands need to understand generative AI's impact on natural language search (NLS). They also need to adjust their strategy for building brand awareness, especially in local SEO marketing.
1 out of every 2 customers (45%) is likely to use and trust an AI tool to find more information about a brand.
But where do generative AI models get information about brands?
And what will make a brand surface on an AI-driven search platform, especially in unbranded searches?
AI will prioritize brands with data it trusts. It trusts brands that have organized their data so the AI tool can "read" it, see it's accurate thanks to consistency, and know that it's published broadly across hundreds of data sources.
Using Yext's Knowledge Graph as your brand data source gives you complete control over how AI sees your brand. Yext also fuels artificial intelligence with your approved content used to generate information about your brand, reputation, products, services, brick-and-mortar locations, staff, and more.