AWS and Databricks are highlighting a broader phase of their collaboration during Data + AI Summit 2026, where they are presenting new capabilities across artificial intelligence, governance, and data platforms. Returning as a Legend Sponsor, AWS is participating with an expanded program that includes technical sessions, demonstrations, customer examples, and expert-led discussions. The event is expected to attract more than 30,000 attendees across in-person and virtual formats, reflecting growing interest in enterprise data and AI strategies.

A major focus of the summit is how organizations are moving AI initiatives from experimentation into operational environments. AWS and Databricks are showcasing customer implementations that use the Databricks Platform on AWS to generate business value from enterprise data. Mastercard is among the organizations featured, while Talkdesk, nCino, Addepar, and Workday are also being presented as companies using Databricks on AWS to support innovation through data-driven approaches. Themes highlighted throughout the event include generative AI deployment, governance frameworks, and open data architectures.

The companies are also presenting what they describe as a combined agentic AI stack. Amazon Bedrock provides access to managed foundation models and includes guardrail capabilities, while Databricks contributes governed data resources designed to support AI reasoning. Amazon Bedrock AgentCore serves as the runtime layer, bringing functions such as memory, identity management, observability, and tools for enterprise agents. Through governed connections, agents can access Unity Catalog-managed data, interact through AI/BI Genie, and retrieve information from Lakebase while maintaining existing permissions.

Another component of the stack is Kiro, AWS’s development environment for agent-driven software creation. According to the summit program, Kiro helps developers translate specifications into functional applications that operate across AWS and Databricks environments. Alongside these technologies, AWS is hosting featured sessions that explore topics such as catalog federation and data silo reduction. One highlighted presentation examines how Mastercard federated Databricks Unity Catalog with AWS Glue as part of its effort to address multi-catalog challenges.

At AWS Booth #100, attendees can explore demonstrations designed to show how modern AI and data applications are built and operated. These demonstrations include AI agents that query governed data, natural-language interactions through AI/BI Genie, and end-to-end agent development using Amazon Bedrock, AgentCore, Mosaic AI, and Genie. The booth also offers technical consultations and strategy discussions with AWS specialists. Beyond product demonstrations, AWS is organizing executive receptions and networking forums focused on financial services, public sector organizations, and media, entertainment, and gaming leaders seeking to discuss AI-related developments within their industries.

📊 What This Means (Our Analysis)

The most notable aspect of this announcement is the emphasis on connecting AI systems directly to governed enterprise data rather than isolated datasets. The partnership highlights how organizations are attempting to combine data management, governance, and AI execution within a unified framework. By bringing these capabilities together in demonstrations, sessions, and customer examples, AWS and Databricks are presenting a practical view of how enterprises can operationalize AI initiatives at scale.

Equally important is the focus on real-world deployment rather than experimental use cases. Customer examples, technical deep dives, and industry-specific forums all point toward a broader effort to help organizations translate AI investments into measurable business outcomes. The collaboration underscores a growing demand for platforms that simplify data access, governance, and application development while supporting increasingly sophisticated AI workloads.

📌 Our Take: The summit showcases how enterprise AI adoption increasingly depends on the ability to connect intelligence, governance, and operational data within a single ecosystem.