Gemini is the engine that doesn't quite know what it wants to be — yet that ambiguity is part of why it matters. It powers Google's AI Overviews, runs as a standalone consumer chatbot, plays the assistant role inside Google Workspace, and increasingly anchors enterprise contracts under the Vertex AI umbrella.
For UK B2B brands, the enterprise side is the part to watch. Companies that have standardised on Workspace are now getting Gemini baked into Gmail, Docs, Sheets, and Slides. Employees are using it to summarise research, draft sales notes, compare vendors, and decide what to shortlist. Many of those employees don't think of it as an "AI engine" at all — they just think of it as the help button in their email.
That broadens the question your brand has to answer. It is no longer enough to be discoverable on consumer ChatGPT or in a research-grade Perplexity query. You also need to surface inside the Gemini-powered tasks that happen on company time, in company documents, on company workflows.
Gemini, like its sibling AI Overviews, leans heavily on schema markup, structured organisation data, and content that an engine can extract precise facts from. Where it differs is in its multimodal preference: Gemini engages with diagrams, charts and images more naturally than the others. Brands that publish well-captioned visual content — pricing tables, architecture diagrams, comparison charts — see citation lifts that text-only sources don't.
The brands that win on Gemini are the ones treating their visual content with the same rigour they treat their text. Clean alt text, clean captions, structured visual data. It feels like a small detail; it's increasingly a real lever.