Unlocking operational insights with AI Assistant in Adobe Experience Platform.

AI Assistant in Adobe Experience Platform is a generative AI tool that will redefine how customers work in Adobe Experience Cloud applications, such as Adobe Real-Time Customer Data Platform, Adobe Customer Journey Analytics, and Adobe Journey Optimizer.

When querying AI Assistant, users should consider two kinds of questions: product knowledge and operational insights. Product knowledge refers to concepts and topics grounded in Adobe documentation including product usage, tutorials, and more. Operational insights refer to answers AI Assistant generates about the metadata of a customer’s objects — including counts, lookups, and lineage impact — without looking at any end customer or account data within a customer’s sandbox.

Here is a sampling of operational insights questions users can ask within AI Assistant:

• How many datasets do I have?
• How many schema attributes have never been used?
• Which audiences have been activated?
• Show me audiences that are duplicated

The ability to query AI Assistant about operational insights will become generally available to all Real-Time CDP and Journey Optimizer customers as of February 18, 2025.

What can operational insights in AI Assistant do for users?

The operational insights capability within AI Assistant serves as a productivity companion for diverse teams across the organization, from marketing operations to data and IT departments. Marketing operations teams can gain insights into optimizing audience and journey strategies, while data engineers and architects can use the tool to track dependencies, conduct value and impact analysis, and ensure data hygiene. Below are some specific use cases for how to leverage operational insights in AI Assistant.

Data management.

AI Assistant helps users track and monitor the flow of data across their schemas and datasets to gain a deeper understanding of how existing Experience Data Model (XDM) fields are utilized. Customers have reported time savings of up to one day when they use AI Assistant to keep track of their data in the platform. As one user put it, “I love how I can find which attributes are used in audiences, without API calls.”

• Example prompts:

  • “How many datasets have been ingested using the same schema?”
  • “How many XDM fields are not used in any audience?”

Audience management.

With AI Assistant, users can gain insights into where their audiences are being used and maintain data hygiene to ensure the accuracy and relevance of their audience inventory. Customers can expect to save 12 hours each time they use AI Assistant to manage their audience inventory. One user shared “We have thousands of audiences, and AI Assistant makes it so easy to find where they are used.”

• Example prompts:

  • “Show me duplicate audiences based on definition.”
  • "Which audiences are activated to destination X?”

Journey management.

AI Assistant empowers users to track the number of active journeys, identify the audiences used within each journey, and maintain journey hygiene. With AI Assistant, users have reported saving more than one day when they use AI Assistant to track their most used journeys. As one put it “Practical questions on journey counts — like how many active or live journeys we have — have been quite useful.”

• Example prompts:

  • "Which audiences are activated to journey X?”
  • "Do I have any journeys that have “test” in the name?”

For the full list of domains supported by AI Assistant, please refer to this guide.

What’s coming next for AI Assistant?

Adobe is focused on bringing the potency of AI Assistant to a range of use cases beyond the ones described above. In addition to product knowledge, operational insights, and even AI Assistant Content Accelerator in Adobe Journey Optimizer, AI Assistant will soon be able to perform data analysis and visualization, optimize audience strategies, and resolve customer care issues for users. These new use cases will empower users with predictive analytics and recommendations to help optimize business outcomes.

Learn more about what AI Assistant can do for your business.

Rachel Hanessian, Ariel Sultan, and Brooke Bell also contributed to this article.

Huong Vu is a product marketing manager for Adobe Experience Platform. She focuses on bringing innovative Experience Platform capabilities to market and driving awareness and adoption around Adobe’s Unified Customer Experience offerings. Vu has over five years of experience in product and brand marketing. She joined Adobe in 2024 after obtaining her MBA from Kellogg School of Management at Northwestern University.

Namita Krishnan is a product manager for Adobe Experience Platform. Her work focuses on building artificial intelligence capabilities and conversational experiences. She brings over six years of experience in engineering and product management. Krishnan joined Adobe in 2024 after graduating from University of Chicago Booth School of Business with an MBA.