Adobe has launched a new “brand visibility” solution designed to help companies manage how they appear across AI-driven discovery tools, as generative AI and chat-based interfaces rapidly reshape how consumers find and interact with brands.
Announced at Adobe Summit, the system is built around a simple premise: customers are no longer only discovering brands through search engines and websites, but increasingly through AI agents, chat interfaces and browser assistants that interpret, summarise and recommend content on their behalf.
That shift, Adobe says, is creating a new imperative for businesses – not just to optimise content for humans, but to ensure it is also accurately understood and surfaced by AI systems.
“There is a new intermediary between brands and their customers, and unlike every one that came before it, this has the ability to reason,” said Loni Stark, vice president of strategy and product at Adobe. “For decades, brands have managed content, but now they also need to manage context.”
At the centre of the announcement is an expansion of Adobe Experience Manager (AEM), which thousands of enterprises already use to manage digital experiences. The platform is gaining a new contextual layer that allows AI agents to help build, govern and optimise content across both human-facing and AI-facing channels.
Adobe is positioning the update as a response to what it calls a “dual challenge”: ensuring brand visibility across AI discovery surfaces, while also improving personalised engagement on owned digital properties such as websites, apps and commerce platforms.
New Adobe data shared at Summit shows AI traffic to U.S. retail sites increased 269 per cent year-over-year as of March 2026, highlighting how quickly AI-driven discovery is becoming mainstream. However, Adobe says many brands still lack visibility into how they are represented within these systems.
The company’s solution is built around an “experience flywheel” that connects four continuous functions: sense, generate, reach and learn.
In the sense phase, tools such as Adobe LLM Optimiser and Adobe Commerce enhancements analyse how AI systems interpret products, content and brand presence across both traditional search and AI-driven interfaces, helping identify visibility gaps.
The generate phase is anchored in AEM Sites, which now includes new contextual management capabilities and AI agents designed to accelerate content production. These include a Brand Experience Agent, which can update or create pages; a Content Advisor Agent, which surfaces approved assets for use across channels; and a Brand Governance Agent, which enforces brand rules, permissions and compliance requirements.
Adobe says these tools are intended to help organisations produce “AI-ready” content at scale, ensuring consistency across both human and machine consumption.
The reach phase focuses on distribution across channels, including AI-driven shopping journeys. Adobe Commerce is being enhanced to improve product visibility, while Adobe Brand Concierge is being updated to support conversational shopping experiences that include real-time product information and checkout functionality.
A new capability called LLM Apps will also allow brands to build experiences that run directly inside large language model interfaces, extending brand presence into AI-native environments.
Finally, the learn phase allows businesses to measure how they are performing across both AI and traditional channels, tracking metrics such as recommendation share within AI systems, engagement growth on owned platforms and customer lifetime value. Insights from human corrections and editorial decisions are fed back into the system to continuously refine brand accuracy and governance.
Adobe says the aim is to create a closed-loop system where every interaction – whether human or AI-driven – improves future performance.
The company also emphasised that the system is designed to unify “brand truth”, governance and content sources into a single operating layer within Experience Manager, ensuring that both internal teams and AI agents work from consistent, approved information.
Early enterprise adopters include Vanguard, which highlighted the importance of maintaining trust as it integrates AI into customer-facing experiences.
