April 21, 2026
Adobe Summit: Adobe’s CX Enterprise Hands the Keys of Experience Orchestration to AI Agents
Adobe has introduced CX Enterprise, an end-to-end agentic AI system designed to unify how businesses manage the full customer lifecycle, from acquisition and engagement through to conversion and long-term loyalty.
The announcement, made at Adobe Summit alongside a suite of connected product launches, represents Adobe’s most ambitious attempt yet to embed AI agents into the daily mechanics of customer experience orchestration (CXO).
With more than 20,000 global brands already running on Adobe’s ecosystem, CX Enterprise extends agentic capabilities across data, content and customer journeys, all underpinned by what the company calls a contextual intelligence and governance layer.
From Campaign Execution to Continuous Engagement
At the core of CX Enterprise is the Adobe CX Enterprise Coworker, an AI-driven orchestration layer designed to move businesses away from campaign-based marketing execution towards continuous, intelligent engagement. Rather than running individual campaigns in isolation, the Coworker coordinates work across multiple agents by translating high-level business objectives into multi-step actions.
If a marketing team sets a target of increasing cross-sell performance by 3%, for example, the Coworker can assemble the necessary audience segments, creative assets and performance insights, generate an execution plan, and, once approved, help run and monitor the campaign against its original goal.
“Adobe CX Enterprise Coworker will be the next step for businesses that are retooling marketing workflows to help teams take advantage of agentic AI technology,” said Anjul Bhambhri, SVP of Engineering, Customer Experience Orchestration, at Adobe. The system is architected on open standards, including Model Context Protocol (MCP) and Agent2Agent (A2A), meaning it can operate across Adobe’s own applications and platforms from AWS, Anthropic, Google Cloud, Microsoft, OpenAI and others.
Adobe is also partnering with NVIDIA to integrate the NVIDIA OpenShell secure runtime and Nemotron open models, combining security and governance with CX Enterprise’s workflow orchestration, particularly for regulated industries.
Brand Visibility in an AI-First Discovery Landscape
A second pillar of Adobe’s announcements addresses a challenge that is becoming increasingly urgent for experience leaders: how brands appear when customers discover and evaluate them through AI-powered interfaces rather than traditional search.
New Adobe data shows that AI-driven traffic to US retail sites increased 269% year-over-year as of March 2026. Despite that growth, the company says most businesses have significant shortcomings in how AI systems interpret their products, content and brand presence.
Adobe’s response is a brand visibility solution built around what it describes as an experience flywheel. Brands sense how they appear across AI discovery surfaces, generate content and experiences grounded in brand context, reach both human audiences and AI systems from a shared foundation, and learn from every interaction to improve performance.
Loni Stark, Vice President of Strategy and Product at Adobe, said: “There is a new intermediary between brands and their customers, and unlike every one that came before it, this has the ability to reason. For decades, brands have managed content, but now they also need to manage context.”
New agentic capabilities within Adobe Experience Manager (AEM) include three purpose-built agents: a Brand Experience Agent that accelerates content production and modernises legacy sites for AI-driven discovery; a Content Advisor Agent that surfaces approved content and prepares it for any channel; and a Brand Governance Agent that enforces brand policies, tracks asset rights and manages permissions.
A new capability called LLM Apps will also enable brands to build branded experiences that run directly within large language model interfaces, extending a brand’s presence across AI surfaces.
An Agentic Content Supply Chain
The third major thread is Adobe’s expansion of its GenStudio content supply chain solution, anchored by a new offering called Adobe Brand Intelligence.
Brand Intelligence replaces static brand guidelines with a learning engine that absorbs feedback from review cycles, annotations and approvals, giving AI agents a continuously updated understanding of what on-brand content looks like.
Across the content supply chain, Adobe is introducing several new agentic capabilities. A Workflow Optimisation Agent within Adobe Workfront automates connected actions across planning, execution, review and approval workflows. AI agents can now be added as assignable resources within Workfront project plans, operating as permissioned collaborators that can be assigned tasks, resolve issues or perform reviews.
Adobe is also launching Firefly Creative Production for Enterprise Workflow Builder, enabling creative technologists to compose reusable, end-to-end production workflows that link creative and generative actions and run batch production. A new GenStudio module for Content Marketing will enable enterprises to repurpose long-form documents and videos into tailored campaigns, web articles and customer case studies.
New Intelligence Layers
Beyond the agents themselves, Adobe is introducing several new decisioning and analytics engines to underpin these workflows. Adobe Engagement Intelligence is a decisioning engine optimised for customer lifetime value, designed to deliver personalisation at scale. Next, Journey Optimiser Loyalty enables teams to deliver personalised, gamified experiences that incorporate loyalty status. Finally, CX Analytics provides a unified, governed intelligence layer that connects customer journeys, content and data across all touchpoints, including emerging LLM-powered interfaces.
An expansion of Adobe Real-Time CDP profiles now unifies unstructured and structured data, bringing more AI context into customer engagement.
Taken together, Adobe’s announcements amount to a vision of agentic AI as the connective tissue for customer experience, not a set of isolated tools but a continuously learning system that spans the full customer lifecycle.
