What Is Google Gemini? A Guide to Google's AI Model in 2026

Most people know Google as the place you go to search. Today Google is also one of the big players in artificial intelligence, and the name of its AI model is Gemini. If you have heard of Bard, it is the same story. Bard was renamed Gemini, and the model has since grown into something woven tightly into search, Android, and Google’s office apps. This guide explains what Gemini is, who builds it, and why it is worth understanding if you work with visibility online.

What Gemini is

Gemini is a family of AI models developed by Google. You write to it in natural language and get answers back, just as you would with any other AI assistant. It can explain a topic, draft text, summarize long documents, help with code, and analyze images. Gemini is multimodal, which means it works with more than plain text. It also handles images, audio, and other kinds of input inside the same conversation.

In practice, people meet Gemini in several places:

• As a standalone assistant at gemini.google.com and in the Gemini app, where you chat directly with the model.
• Inside Google Search, where it powers the AI-generated overviews at the top of the results page.
• In Google Workspace, meaning Gmail, Docs, Sheets, and the other apps, where it helps write and rework content.
• On Android, where Gemini is taking over from the classic Google Assistant on many devices.

The point is that Gemini is not just one product. It is a layer of intelligence Google is placing underneath many of the services people already use every day.

Who builds it

Gemini is developed by Google and by Google DeepMind, Google’s combined division for AI research. DeepMind was founded in London and was later acquired by Google. Today the unit is led by Demis Hassabis, co-founder and chief executive of DeepMind. Google itself is headquartered in Mountain View, California.

DeepMind is known for research that reaches well beyond chatbots. The same organization was behind AlphaGo, the program that beat one of the world’s best players at the board game Go, and behind AlphaFold, a system for predicting the structure of proteins. That research background is what Gemini builds on. So when Google talks about Gemini, it is not talking about a detached side project. It is talking about a product that grows out of one of the most respected AI research environments in the world.

Tight integration with search and Workspace

What sets Gemini apart from other AI models most is its closeness to Google’s own products. Google owns the search engine billions of people use, and it owns the office apps on top of that. That gives Gemini a position no competitor can copy from day one.

In search, Google increasingly shows an AI-generated answer at the top of the results page, often called AI Overviews. Here Gemini combines information from several sources into one consolidated answer, and below the answer it links to the pages the content came from. For the user, that often means getting the answer without clicking through. For businesses, it means the fight for visibility is shifting from the classic link toward being mentioned and cited inside the AI answer itself.

In Workspace, Gemini works as a helper that sits directly inside the apps people already work in. It can suggest phrasing in an email, summarize a long thread, or pull key figures out of a spreadsheet. Because it has access to your own documents, it can work with your content and not only with general knowledge.

Strengths and limitations

Gemini has some clear strengths. It is good at processing large amounts of text at once, which makes it useful for summarizing and analyzing long documents. It is multimodal, so it works with images and other formats in the same conversation. And it has the advantage of living close to Google’s data and products, which gives fast access to fresh information from the web.

There are also real limitations worth being honest about:

• It can be wrong in a confident tone. Like other AI models, Gemini can present incorrect information as if it were certain. The phenomenon is called hallucination, and it applies to every model on the market.
• The answers depend on the sources. When Gemini summarizes content from the web, it inherits both the strengths and the weaknesses of what it reads. If the sources are unclear or out of date, that carries over into the answer.
• Quality varies with the task. For some tasks it is excellent, for others more average. That holds for all the large models, which is why many people run several assistants side by side.

The sensible approach is to use Gemini as a capable helper and not as a final source. Important information should always be checked.

Interesting details about Gemini

Some of the stories around Gemini say something about how fast the field is moving:

• From Bard to Gemini. Google first launched its AI assistant under the name Bard. Later it gathered the products under the name Gemini, so the model and the assistant share a name. That makes it easier to understand that it all belongs to the same family.
• From Assistant to Gemini on Android. Gemini is gradually taking over from the classic Google Assistant on phones. That moves AI out of a separate app and into the core functions of the phone itself.
• AI directly in the search results. With AI Overviews in search, many people meet an advanced AI model without ever opening a chatbot. They simply type a search the way they always have and get an AI answer back.

Taken together, that paints the picture of a model Google is trying to make a natural part of everyday life rather than a separate tool you have to seek out.

What Gemini means for marketing and GEO

This is where it becomes truly relevant for businesses. Because Gemini is tied directly into Google Search, classic search engine optimization and visibility in Gemini are closely linked. When Gemini builds an AI answer in search, it draws on content from the open web, and the pages it chooses to cite are often the same pages that already rank well organically. A solid SEO foundation is therefore still one of the best ways to become visible in Gemini’s answers.

On top of the classic SEO work comes the new discipline that is specifically about being cited by AI models. It is called GEO, or generative engine optimization, and it is about making your content easy for a machine to understand and cite. In practice that means clear answers to specific questions, a clear source and credibility, and technical clarity that makes the pages easy for the models to read. You can read more about that discipline in our guide to GEO.

The good thing about this situation is that the work is not wasted either way. The same virtues that get you ranking on Google also make you more likely to be mentioned in an AI answer from Gemini. You are building two forms of visibility on one foundation, and because Gemini and Google Search share so much, you get a lot for the effort.

In short

Gemini is Google’s AI model, formerly known as Bard, developed by Google and Google DeepMind under the leadership of Demis Hassabis. It is closely integrated with search, Android, and Workspace, and it powers the AI Overviews many people now meet at the top of the search results. For businesses, the tight link to search means SEO and visibility in Gemini go hand in hand. If you want to understand the new discipline of being cited by AI, read on in What Is GEO.