Google Gemini is Google’s family of multimodal AI models, available as a chat assistant, inside Google Workspace, through the Gemini API and built into Google Ads and other Google products. At Alien Road we use it for research, first drafts, translation support, data analysis and ad asset ideas, always with a person reviewing outputs before anything reaches a client or goes live.
What is Gemini, and where does it appear?
Gemini is built by Google DeepMind. The models handle text, images, audio, video and code, and some versions accept very long inputs, which helps with large documents. Google offers lighter models such as Flash and Flash-Lite for speed and cost, and Pro models for harder tasks.
For an agency, Gemini shows up in several places at once:
- The Gemini app for chat, research and file analysis
- Gemini in Google Workspace: Gmail, Docs, Sheets, Slides and Meet
- The Gemini API through Google AI Studio and Vertex AI, for our own tools and scripts
- Google Ads features that generate headlines, descriptions and images, many of them powered by Gemini models
- Google’s AI Overviews and AI Mode in Search, which shape how our clients are found
That last point matters as much as the tools. Gemini is not only something we use; it also decides part of our clients’ visibility.
How Alien Road applies Google Gemini in client work
Our process follows the same four steps for each use: discovery, setup, measurement and reporting. The tool changes; the discipline does not.
Discovery and research
At the start of an engagement, we use Gemini with long documents: the client’s past reports, sales materials, competitor pages and market studies. We ask it to extract positioning claims, recurring customer objections and gaps between what competitors promise and what the client offers. A strategist checks every claim against the source before it enters the strategy document.
Content drafting and translation support
For blog and landing page work, Gemini helps produce outlines and first drafts from a brief with keyword data. Writers then rewrite for voice, add real examples and verify facts. Because many of our clients publish in several languages, we also use Gemini through the API for first-pass translation, followed by human review on key pages.
Google Ads assets
Inside Google Ads, AI features suggest headlines, descriptions and images for responsive search ads and Performance Max asset groups. We treat suggestions as raw material. Each asset is checked for accuracy, brand terms and policy before approval, and we track asset performance labels to retire weak ones.
Data analysis in Sheets and through the API
Campaign exports go into Sheets, where Gemini helps summarize trends and build formulas. For larger analyses, we run scripts through the API with structured prompts and a fixed output format, then verify a sample of numbers by hand.
Which tasks do we keep away from Gemini?
Some work stays with people because errors are costly or judgment matters most.
- Final strategy recommendations and budget decisions
- Any claim about a client’s results, prices or legal terms that has not been checked
- Sensitive client data that the client has not approved for AI processing
- Crisis communications and statements on behalf of a client
How do we handle data and privacy?
Data settings differ between Gemini products. Consumer use, Workspace with enterprise terms and the paid API through Vertex AI each have different data handling commitments. We use business accounts and paid API access for client work, follow each client’s data policy and remove personal data from exports before analysis.
- Use Workspace and API terms suitable for business data
- Strip names, emails and phone numbers from data files
- Keep a record of which client data was processed by AI and for what purpose
What limits do we plan around?
Gemini, like any language model, can state wrong facts with confidence, especially about recent events, local markets and niche topics. It may also produce generic copy if the brief is thin.
- Fact checks for every number, date and claim
- Clear briefs with audience, tone, keywords and examples
- Rate limits and quotas on the API, which affect large batch jobs
- Model changes over time, so we re-test prompts when Google updates models
How do we measure whether Gemini helps?
We track time and quality, not just output volume. For each use case, we compare hours spent before and after and the number of editing rounds needed.
- Hours per deliverable type, such as a monthly report or a blog draft
- Editing rounds before approval
- Errors found in review, logged by type
- For ads: performance of AI-assisted assets versus manually written ones
Reporting to clients focuses on results: campaign performance, content published and quality. Where AI assisted, we say so plainly.
How do we choose between Gemini models?
We match the model to the job. Light models such as Flash-Lite handle high-volume tasks like tagging, short summaries and first-pass translation, where speed and quota matter more than depth. Flash covers most drafting and analysis. Pro models, or thinking modes, are reserved for long documents and multi-step reasoning where quality justifies slower answers.
Each model has its own quota on the API, so spreading batch work across models also keeps large jobs moving. We re-test a fixed set of prompts whenever we change models, so the switch does not quietly lower quality.
- Light models: volume tasks and routing
- Mid-tier models: drafts and everyday analysis
- Top models: long research and hard reasoning
How does Gemini change SEO work for clients?
Because Gemini models power AI Overviews and AI Mode, we also work on how clients appear there. That means answer-first content, clear structure, accurate structured data and strong third-party mentions. We monitor a fixed set of queries for each client and record whether their pages are cited in AI answers.
Where to start this week
If you run Google Ads, open one responsive search ad and review the headlines Google’s AI suggests. Accept only the ones that are accurate and on brand, then check the asset performance labels after two weeks. In parallel, put last month’s campaign export into Sheets and ask Gemini for the three biggest changes. Verify each by hand. Those two small tests show where Gemini fits your own work.
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