Agentic AI

What is an Agentic DXP? 

An Agentic DXP is a digital experience platform that embeds autonomous AI agents capable of executing marketing, content, and optimization tasks with minimal human intervention. Rather than presenting data for a human to analyze or waiting for instruction to act, an agentic DXP monitors performance, identifies opportunities, generates recommendations, and in some cases takes direct action within the platform to improve digital experiences. Critically, it is built for a dual-persona reality: designed to serve not only human users but also the AI agents that increasingly access and interact with digital experiences on their behalf. 

The concept reflects a broader shift in how AI is integrated into enterprise software. Where earlier AI in DXPs provided assistance (content suggestions, classification, autocomplete), agentic AI provides execution. The platform becomes a goal-seeking environment where AI agents work alongside content and marketing teams, completing defined tasks autonomously while humans retain responsibility for strategy, governance, and final decisions. 

Where a traditional DXP scales with the people who operate it, an agentic DXP scales with compute. 

What are the key characteristics of an Agentic DXP? 

• Autonomous task execution: AI agents complete defined tasks (analyzing a content page, evaluating a customer journey, generating a campaign report) without requiring a human to initiate each step.
• Goal-oriented behavior: Agents are configured around outcomes (improve conversion rates, maintain brand voice, strengthen SEO performance) and work toward those goals by evaluating evidence and surfacing specific actions.
• Context awareness: Agents understand the current state of the platform (content, journeys, campaigns, customer data) and use that context to produce relevant, specific recommendations rather than generic advice.
• Human-in-the-loop governance: Agentic DXPs are designed with human oversight built in. Agents recommend, flag, or execute within defined boundaries, with humans retaining approval and governance responsibility.
• Continuous operation: Rather than running a one-time analysis, agents monitor ongoing performance and surface new recommendations as conditions change, enabling systematic improvement at scale.

How does an Agentic DXP work, and why does it matter for digital teams? 

In an agentic DXP, AI agents are configured with a defined scope: the data they can access, the tasks they can perform, and the boundaries within which they operate. When triggered by a user prompt, a schedule, or a performance threshold, an agent retrieves relevant data, analyzes it, and produces an output: a recommendation, a structured report, a draft, or an automated action. The quality of that output depends directly on the quality of the underlying content and data the agent can access. 

For digital teams, this matters because the gap between strategic intent and operational execution has historically been one of the biggest constraints in marketing. Teams know they should be optimizing more pages, analyzing more journey stages, and monitoring more campaigns, but capacity prevents it. Agentic DXPs close that gap by delegating defined, repeatable analytical and optimization tasks to AI, freeing human effort for decisions that require judgment, creativity, and accountability. 

How does Xperience by Kentico implement an Agentic DXP? 

Xperience by Kentico delivers agentic DXP capabilities through the AIRA Agentic Marketing Suite, a set of specialized AI agents embedded directly in the platform: 

• Content Strategist: Evaluates page content against a Content Strategy document, assessing style compliance, tone, and brand voice alignment. Produces structured feedback with severity levels (Critical, Major, Minor, Suggestion) and specific recommendations.
• Customer Journey Optimization Specialist: Analyzes customer journey performance data to identify underperforming stages and provides tailored, stage-specific recommendations to improve conversion rates.
• SEO and GEO Specialist: Evaluates pages against SEO best practices and GEO (AI readability) criteria, producing scored reports with recommendations prioritized across High, Medium, and Quick Win tiers.
• Campaign Manager: Generates campaign analysis reports, evaluates KPI achievement, and enables cross-campaign comparison. Supports AI-assisted brief creation within the Campaigns application.

AIRA agents are context-aware: the platform activates the appropriate agent based on where the user is in the admin interface and what they prompt. Each agent operates within a defined, configurable scope, with human teams retaining full governance and approval control.

How do organizations benefit from an Agentic DXP? 

Organizations using an agentic DXP report that AI agents significantly reduce the time spent on analytical and reporting tasks that previously required substantial manual effort. A content audit that would take days of manual review can be completed by the Content Strategist agent in a fraction of the time. A customer journey analysis that once required a data analyst can be initiated by a marketer directly within the platform. 

The strategic benefit is depth and coverage. Agentic DXPs make it possible to monitor more content pages, more journey stages, and more campaigns simultaneously than any human team could manage manually. Issues and opportunities that would otherwise go unnoticed (a content page drifting from brand voice, a journey stage with a deteriorating conversion rate) are surfaced proactively and systematically. 

How does an Agentic DXP fit into an AI-first digital experience strategy? 

An agentic DXP is the operational layer where AI-first strategy becomes continuous, systematic action. Without agentic capabilities, organizations must manually translate AI analysis into execution, a process that limits how consistently strategy is applied across all digital properties. Agentic AI removes that bottleneck, applying defined strategic goals at a frequency and scale that human teams cannot match alone. 

Gartner Senior Director Analyst Irina Guseva described the current moment as an inflection point that demands a categorical transformation for DXPs: a shift from platforms that present data and await instruction to platforms where agents actively orchestrate experiences. She also cautioned that agentic AI is only as good as the content and data it can access, making a well-governed content foundation the prerequisite for effective agentic capabilities. 

What is the difference between an Agentic DXP and a conventional DXP?

A conventional DXP provides infrastructure for creating, managing, and delivering digital experiences: content management, personalization, analytics, and channel delivery. It is a capable toolkit, but one that depends on human teams to analyze data, identify opportunities, and execute improvements. The platform presents information; humans decide what to do with it. 

An agentic DXP retains that infrastructure but adds an autonomous execution layer. AI agents can complete continuous tasks; like analyzing content performance, identify journey drop-off points, evaluate SEO quality, and generate reports without waiting for a human to initiate the task. The platform shifts from a passive tool to an active collaborator, one that surfaces issues before they become problems and executes defined tasks at a frequency and coverage that human teams cannot match alone. 

What is an Agentic CMS? 

An agentic content management system (CMS) is a CMS that operates autonomously, using AI agents to execute content management tasks without constant human intervention. Where a CMS is a tool that humans use to create, manage, and publish content, an agentic CMS acts as an active participant in content operations: processing content in bulk, making governance and workflow decisions, and dynamically orchestrating adaptive experiences in real time. The core distinction is one of scale: a traditional CMS scales with the people who operate it; an agentic CMS scales with compute.