At the Cannes Lions festival on June 16, 2025, Adobe introduced Adobe LLM Optimizer, a new enterprise-grade tool designed to help businesses improve their visibility in generative AI-powered environments.

As conversational interfaces like ChatGPT, Gemini, and Claude reshape how consumers search and engage online, Adobe’s new application aims to give brands the ability to understand and influence how they appear in these rapidly evolving digital spaces.

Backed by data from Adobe Analytics showing a 3,500% increase in AI-sourced traffic to U.S. retail sites and a 3,200% spike to travel sites between July 2024 and May 2025, Adobe’s move comes at a time when the shift toward generative interfaces is accelerating. These tools are not only changing the mechanics of discovery—they are redefining what it means to be visible and influential online.

“The adoption of GenAI-powered chat services is astounding, with massive year-over-year growth,” said Haresh Kumar, senior director of strategy and product marketing for Adobe Experience Manager. “It’s fundamentally changing how consumers interact, search, and find information.”

“Generative AI interfaces are becoming go-to tools for how customers discover, engage and make purchase decisions,” added Loni Stark, vice president of strategy and product for Adobe Experience Cloud. “With Adobe LLM Optimizer, we are enabling brands to confidently navigate this new landscape, ensuring they stand out and win in the moments that matter.”

GEO is the new SEO

Haresh Kumar described the new digital reality as one in which brands no longer just optimize for search engines—but for AI models.

“SEO is no longer just about keywords and backlinks,” he said. “In the era of generative AI, we’re entering a new paradigm—Generation Engine Optimization or GEO—where relevance is judged differently.”

This evolving landscape demands new methods for tracking performance and influencing discoverability. Adobe LLM Optimizer aims to address this with a three-pronged framework:

1. Auto Identify: The system detects how a brand’s content is being used by major AI models. Adobe tracks the “fingerprints” of indexed content and determines whether—and how—it appears in responses to relevant queries.
2. Auto Suggest: Drawing on Adobe’s own AI models trained for generative interfaces, the tool recommends improvements across technical infrastructure and content. These could range from fixing metadata errors to improving authority and context in FAQ content.
3. Auto Optimize: For many brands, the challenge isn’t just knowing what to fix—it’s executing the fixes quickly. LLM Optimizer allows users to apply recommended changes directly, often without heavy involvement from development teams. “We help brands auto-identify how their content is performing in LLMs, auto-suggest improvements, and auto-optimize to actually implement those changes,” said Kumar.

Revealing gaps in your brand’s visibility to LLM users and assisting with filling them

Adobe’s system enables marketers to see where their brand is underrepresented in AI-driven results. “The goal is to help brands understand the gaps—where they’re not showing up in AI answers—and what fixes can make them more visible,” said Kumar. The application calculates projected traffic value for each suggested change, letting teams prioritize high-impact actions.

“Brands often ask, ‘Do I need to care about this new AI box?’” Kumar added. “The answer is yes—because traffic is shifting there. If you’re not optimizing for it, you’re missing out.”

One example of content optimization includes focusing on formats that LLMs naturally prefer.

“FAQ pages tend to perform exceptionally well in LLM indexing,” said Kumar. “They provide direct, authoritative answers that LLMs prefer when generating responses.”

Adobe’s platform not only recommends creating such content but also assists in generating it within a brand’s existing voice and structure, thanks to native integration with Adobe Experience Manager.

Always on analysis and expanding coverage for the growing library of LLMs

LLM Optimizer uses a combination of push and pull models to keep content indexing current. When new content is published or accessed by an AI model, the system updates its analysis and surfaces insights to the user.

“Our infrastructure includes both push and pull models. Whenever content is updated or accessed, we capture that fingerprint and feed it into our analysis engine,” Kumar explained.

Currently, the product tracks performance across several top AI models, including ChatGPT, Claude, and Gemini, with plans to expand coverage as new models emerge.

Availability and integration

Adobe LLM Optimizer is available now as a standalone product or as a native integration with Adobe Experience Manager Sites. While pricing is not publicly disclosed, Adobe confirmed it is a separate product requiring opt-in and agreement updates.

“LLM Optimizer is a new product offering, fully integrated with Adobe Experience Manager but available as a standalone solution,” said Kumar. “Customers need to opt in based on their AI readiness and strategy.”

With more consumers spending time inside AI-driven interfaces, Adobe positions LLM Optimizer as a forward-looking solution for enterprises navigating this new terrain. It offers a blend of visibility, automation, and strategic clarity as digital engagement moves beyond traditional search engines into the generative future.