With AI-powered shopping skyrocketing by 4,700% and travel sites experiencing a 3,500% surge in AI-driven traffic in just the past year, it’s hard to ignore how quickly the landscape of digital discovery is evolving. Customers are now looking to AI tools for recommendations, answers, and inspiration — and what shows up in those results can make or break your brand’s visibility.
Suddenly, every marketer is competing for attention in AI-generated answers, where the rules of engagement are in constant flux. Today’s challenge is not just about being present — it’s about being visible and credible. To achieve this, your teams must go beyond creating engaging content and place additional focus on how agents can read and interpret your content effectively, all while evolving how you measure success in this new context.
This blog lays out three key areas of focus for AI search optimization. With the right feedback and systems in place, your brand can transform AI-driven discovery from a challenge into an opportunity, connecting with customers where it matters most.
1. Identify gaps in your AI visibility.
The first step toward establishing a strong presence is understanding where your brand stands today — and where it’s falling short. Start with an AI search visibility audit, examining not just your own digital assets, but how your brand is referenced across the web. Are your product catalogs fully detailed, with all the identifiers and rich media that AI engines crave? Is your site’s content well-structured and up to date, from FAQs to support docs? More importantly, does your brand earn citations from trusted third-party sources, like expert forums and respected publications? These external references are what AI models look for when deciding who gets surfaced in answers.
Once you’ve pinpointed where your brand isn’t showing up — or isn’t showing up correctly — it’s time to get tactical and implement fixes.
2. Leverage AI to turn insights into optimizations.
Optimization in the agentic era is about working smarter, not harder. Rather than making blanket content revisions, teams should focus on precise, high-impact updates. These could include filling in missing specs, correcting identifiers, refreshing authority references, or even updating pricing. The key is to ensure every change is designed to help AI agents find, understand, and present your brand accurately.
Take a systematic approach by connecting your monitoring efforts directly to internal analytics, so you can see how quickly updates are reflected in AI-generated responses. Use tools like Adobe LLM Optimizer to automate cross-channel monitoring, spot additional optimization opportunities, and benchmark your brand against competitors. Document winning tactics and scale them across product lines. The goal is to make AI optimization part of the operational DNA, not a one-off project. For marketing leaders, this means empowering teams to act quickly, iterate, and double down on proven strategies without getting bogged down in endless guesswork.
