Agentic DXP: What It Is, and Which DXPs Use AI Agents

Last updated October, 2026

Short answer: An agentic DXP is a digital experience platform with built-in AI agents. The agents carry out multi-step marketing and content tasks, such as checking content against brand rules, analyzing campaigns, or finding where customers drop out of a journey, while people decide what goes live. Most DXP vendors now offer some AI, but fewer offer agents that work with the platform's own content and customer data. Vendors with agentic capabilities in 2026 include Acquia, Adobe, Kentico (Xperience by Kentico), Optimizely, Progress Sitefinity, and Sitecore. The best AI-enabled DXP is the one whose agents fit your team's daily work, your data, and your governance rules. 

What is an agentic DXP? 

An agentic DXP is a digital experience platform (DXP) where AI agents take on tasks across content, marketing, and customer data. You give an agent a goal, and it plans the steps, uses the platform's data and tools, and returns results or recommendations for people to approve. 

AI in a DXP usually comes in three levels: 

• AI features complete one task when asked, such as generating text, translating a page, or tagging an image.
• AI assistants help a user through a task in a chat, one prompt at a time.
• AI agents work toward a goal. They plan and carry out several steps using the platform's content and data. They don't stop at recommendations: once a person approves, they do the work, such as applying the changes they proposed.

A DXP becomes agentic when it offers the third level: agents that carry out real work inside the platform, with people approving what they do, not only text generation on request. 

What's the difference between an AI-enabled DXP and an agentic DXP?

Every agentic DXP is AI-enabled, but not every AI-enabled DXP is agentic. The difference is how much of a task the AI handles on its own.  

What can AI agents in a DXP do?

• Check content quality and brand voice. Review pages and emails against style, tone, and terminology rules, and point out what to fix.
• Improve search and AI visibility. Audit pages for SEO and for how well AI assistants can read and quote them.
• Build audiences. Turn a plain-language description into segment rules.
• Optimize customer journeys. Find the stages where customers drop out and recommend changes.
• Analyze campaigns. Compare results with goals and across campaigns, and summarize what worked.
• Support developers. Help build, migrate, and maintain projects through tools that AI coding assistants can use.

Which DXP vendors offer agentic AI in 2026?

Listed alphabetically, not ranked. Based on each vendor's product pages and DXP Scorecard (dxpscorecard.com), October 2026.  

Agent offerings change quickly. Before you shortlist, check each vendor's current documentation and ask for a demo on your own content. For a wider view of the market, see DXP Vendors.

How do DXPs use AI for personalization?

AI can support personalization at several points, from deciding who to target to creating the content each audience sees: 

• Audience building. AI turns a description, such as "visitors who downloaded a whitepaper but haven't requested a demo," into segment rules.
• Recommendations. AI suggests products or content based on behavior. This is most common in commerce-focused platforms.
• Content variants. AI drafts versions of a headline, page, or email for different audiences.
• Journey optimization. AI finds where customers drop out and suggests what to change.
• Automated decisions. Some platforms let AI choose which variant each visitor sees, based on predicted results.

In Xperience by Kentico, AI supports the steps around personalization while marketers stay in control of who sees what. AIRA builds segments from a plain-language prompt, drafts content variants for each audience, and checks them against your content strategy. The Customer Journey Optimization Specialist shows where customers drop out and recommends changes. Marketers then decide which content each segment sees, using the personalization rules built into the platform. 

How do you evaluate an AI-enabled DXP?

• Agents that use your data. Check whether the agents work with your platform's own content, customer journeys, and campaigns, or only with the text you paste in.
• Human approval and audit trail. Check who approves agent output before it goes live, and whether you can see what each agent did.
• Data protection. Ask where AI requests are processed and whether your content or customer data is used to train AI models.
• AI pricing. Find out whether AI is included in the license, charged through credits, or sold as an add-on, and how usage is reported.
• Model choice. Check which AI models the platform uses and whether you can connect your own AI provider.
• Fit for your team. Check whether marketers can use the agents without developer help, and whether developers get AI tools for building the site.
• Proof in your scenario. Ask for a demo of the agents on your own pages, emails, and journeys, not on sample content.

How does Xperience by Kentico use agentic AI?

Xperience by Kentico is a unified, hybrid headless DXP. Its AI, AIRA, is built into the same application that marketers, editors, and developers already use, so agents that are a part of the AIRA Agentic Marketing Suite work with the platform's own content, customer journeys, and campaigns. 

• AIRA for everyday content work. Generates and refines text in any text field, translates content, writes image descriptions, and tags content and images.
• Content Strategist. Checks pages against your content strategy for style, tone, and voice, and lists issues by severity with suggested fixes.
• SEO & GEO Specialist. Analyzes pages for search engine optimization and for how well AI assistants can read and quote them and ranks recommendations by priority.
• Customer Journey Optimization Specialist. Finds the journey stages where customers drop out and recommends changes to the related pages and emails.
• Campaign Manager. Analyzes campaign results against goals, compares campaigns, and helps draft campaign briefs.
• AI-built segments. AIRA turns a plain-language description into segment conditions, based on your pages and forms.
• KentiCopilot for developers. AI agent skills and MCP servers that help developers model content, build pages and widgets, and migrate projects using AI coding assistants such as Claude Code, Cursor, and GitHub Copilot.
• Visible usage. AI features run on credits, and the AIRA Usage Overview shows how they are used by feature and agent.

The agents analyze and recommend, and marketers decide what changes go live. The result is faster, more consistent marketing work in one platform, without connecting separate AI tools. 

What are the benefits and limits of an agentic DXP?

Benefits

• Faster routine work. Checks, audits, and analyses that took hours take minutes.
• More consistent content. Brand and style rules are applied the same way on every page.
• Better-informed decisions. Agents surface problems in journeys and campaigns that are easy to miss in reports.
• More output per team member. Small teams can cover more channels and campaigns.

Limits

• Maturity varies. Many agents launched in 2025 and 2026, and their depth differs a lot between vendors.
• Costs can grow with usage. Credit-based or usage-based pricing needs monitoring.
• Governance is required. Someone has to define rules, approve output, and review what agents do.
• Results depend on inputs. Agents work best with well-structured content, clear brand rules, and clean data.