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.
Explore how Adobe LLM Optimizer can help you track GEO performance.
3. Build a continuous feedback loop.
Metadata and content optimizations alone won’t ensure continued visibility for your brand. As AI search continues to evolve, marketing leaders will need to understand precisely which levers to pull and which blind spots to address first, in order to stay ahead.
A continuous feedback loop will be essential for identifying and acting on these levers quickly. Consider focusing on these areas:
- Track visibility and sentiment by building a registry of influential external authorities, including Reddit and Wikipedia, review platforms, and industry standards, and monitor how their updates ripple through AI search results. By keeping a clear log of what’s changed and mapping those changes to how your brand appears in AI-generated answers, you’ll reveal the gaps where you’re losing share of voice or missing out on key citations.
- Coordinate every change that could impact AI search by setting up governance workflows to coordinate across marketing, legal, and brand teams. This approach allows each modification to be assessed for its effects and helps reduce unexpected outcomes.
- Share operational metrics with executive teams including answer share-of-voice, citation quality, and time-to-refresh so that everyone’s aligned on where the brand stands, how changes have impacted search results, and where to invest next.
The brands that thrive will be those that treat measurement as an ongoing discipline, continually refining their approach to maximize visibility, credibility, and competitive displacement in the AI-driven search landscape.
Act now, win later.
The era of AI-powered discovery is truly here, reshaping how visibility, authority, and influence are earned online. Staying competitive means more than just keeping up — it’s about being proactive, measuring impact, and refining your approach with every insight gained. By establishing repeatable processes, sharing key operational metrics, and coordinating across teams, your brand remains agile and ready to seize new opportunities.
While the landscape may feel complex, the right tools make all the difference. LLM Optimizer offers practical support, helping your marketing team automate the heavy lifting and focus on strategic improvements that matter. Forward-thinking brands that embrace these changes will be positioned for sustainable growth and lasting relevance.
Learn more about LLM Optimizer or discover how it works in a guided product tour.
Questions about AI search? We have answers.
What is the Adobe LLM Optimizer, and how does it help marketers?
What are common gaps in AI search visibility, and how can they be addressed?
How does AI search optimization vary by geographic location?
What are the benefits of acting early in AI search optimization?
How does AI search optimization compare to traditional SEO strategies?
What are the challenges marketers face when implementing AI search optimization?
Tory is the Senior Director, Web Marketing for Adobe for Business. With over 20 years of experience in B2B marketing within Fortune 250 companies, Tory is a seasoned leader known for driving revenue and margin growth. She currently leads the Adobe for Business web team, overseeing web experience, journeys, SEO and web analytics with her global team across North America, EMEA and APAC regions. Her expertise lies in crafting innovative strategies and operational plans that align marketing, product, and sales teams, ensuring seamless cross-channel execution. Passionate about technology, she has a keen interest in understanding and leveraging AI capabilities in all aspects of the website and her team's work. She is especially keen on unpacking the AI based search space to evolve the SEO practice to include improving visibility in AI search engines and LLMs.
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