How AI is shaping marketing—and how to prepare.

Discovery is becoming less predictable.

In Pew Research Center’s analysis of U.S. browsing activity in March 2025, users clicked a traditional search result on 8% of visits with an AI summary, compared with 15% without one. This was an observational study of a particular sample and period; it does not establish that AI summaries caused every difference or predict what will happen to your website. It does show why traffic assumptions deserve another look. Pew Research Center: browsing behavior and AI summaries, July 2025 ↗

Treat search as one part of a broader discovery journey. Your website should clearly explain who you help, what you do, and why someone should believe you. Useful comparisons, specific service descriptions, and original examples give a prospective customer more to work with than broad claims about innovation.

AI visibility starts with solid fundamentals.

Google says its established SEO practices remain relevant to AI Overviews and AI Mode, with no special markup or additional technical requirements for inclusion. Eligibility does not guarantee a citation or appearance. That guidance concerns Google’s systems; it should not be treated as a universal rule for every AI product. Google Search Central: AI features and your website ↗

Our recommendation is to focus first on a website people can use and search systems can access. Make important information available as text, connect related pages, and keep business details accurate. Then improve the substance: answer the questions your sales team hears, explain tradeoffs, and show evidence that is specific to your work.

Faster production needs a stronger editorial standard.

AI can help a team explore headlines, organize a brief, or produce a rough first draft. The useful output is the finished work, so include fact-checking, revision, and approval when you judge whether the process saves time. A quick draft that needs extensive repair may not improve the workflow.

Create a short editorial standard before scaling production. Define the audience, tone, acceptable sources, and claims that require evidence. Give a person responsibility for the final result. For a product page, that means checking every feature and promise against the actual product. For an article, it means adding a point of view that reflects your expertise.

Connect the workflow before expanding the experiment.

A writing tool is only one part of a marketing process. Briefs, product information, approvals, publishing, and customer records may live in different systems. Map where information comes from and who can change it before introducing automation. Use approved data and define which actions still require review.

Start with one bounded task, such as preparing an internal summary from approved product material. Record the current time and quality of the work. Test the new process against that baseline, including how often people need to correct it. Expand only when the result is useful and repeatable.

Build a practical 90-day preparation plan.

In the first month, review your key website pages and interview the people closest to customers. Gather the questions, objections, and information gaps they encounter. Choose one content priority and one internal workflow to improve.

In the second month, run small tests with named owners and clear review criteria. In the third, compare the results with the starting point: qualified enquiries, completed tasks, quality of output, and time spent correcting mistakes. Treat checks of AI answers as snapshots that can vary, rather than a fixed ranking to chase.

Prepare for AI by strengthening your website, your evidence, and the way your team works. The advantage comes from learning where the technology helps and building that learning into a reliable process.