Databricks Data + AI Summit 2025 highlighted a bold vision for the future of enterprise AI with a series of announcements showcasing its growing generative and agentic AI capabilities. In a clear response to increasing competition — especially from Snowflake, which hosted its own AI-centric event just a week prior — Databricks unveiled a suite of innovations under its Data Intelligence Platform, aimed at democratizing AI and simplifying data workflows across organizations.

Although many of the features are still in beta or preview, the announcements reflect a race to redefine how enterprises engage with their data using automation, natural language interfaces, and low-code or no-code tools.

Databricks Data + AI Summit 2025: 5 Key Announcements

Here are five key announcements from Databricks Data + Ai Summit 2025.

Agent Bricks: Automating Agent Creation

A standout announcement was Agent Bricks, Databricks’ new tool for automating the process of building AI agents. Rather than targeting seasoned developers or data scientists, Agent Bricks is designed for organizations that lack deep in-house AI expertise — offering a streamlined, no-fuss method to design, deploy, and manage AI agents.

What sets Agent Bricks apart is its deep integration with Unity Catalog and MLflow 3.0, shifting agent lifecycle management away from complex interfaces and into a more structured governance layer. It supports the Model Context Protocol (MCP) and is expected to add compatibility with Google A2A protocol, signaling a commitment to emerging agent interoperability standards.

Analysts note that Databricks is filling a gap left by rivals like Snowflake, which have yet to offer comparably mature agent lifecycle tools — making Agent Bricks one of the more forward-looking aspects of the Databricks Data + AI Summit 2025.

Lakeflow Designer: Tackling the Data Engineering Bottleneck

AI projects often stall not because of model limitations, but due to data preparation challenges. To address this, Databricks unveiled Lakeflow Designer, a visual tool powered by generative AI that enables data analysts to create and manage ETL (extract, transform, load) pipelines — traditionally the domain of data engineers.

Dubbed by some as the “Canva of ETL,” Lakeflow Designer provides an intuitive interface where users can visually construct pipelines with AI assistance. It’s tightly integrated into Lakeflow Declarative Pipelines, enabling Git and DevOps workflows along with full lineage tracking, access control, and auditing. By bringing analysts and engineers into a shared environment, Databricks aims to improve collaboration and accelerate time to insight.

Databricks One: No-Code Analytics for Business Users

Another major announcement at Databricks Data + AI Summit 2025 was the introduction of Databricks One, a no-code, conversational analytics platform aimed at non-technical users. Still in private preview, Databricks One packages AI and BI tools with natural language interfaces and governance built-in, allowing business teams to explore data securely without needing to write SQL or Python.

At the heart of Databricks One are three new features:

• AI/BI Dashboards: Let users create data visualizations and conduct analytics without coding.

• Genie: A natural language assistant that can answer questions about business data conversationally.

• Databricks Apps: Lightweight applications built on top of the Data Intelligence platform for specific vertical or departmental use cases.

Databricks One is available for free to existing subscribers, and the company also announced a free edition of its Data Intelligence platform to further lower adoption barriers for developers and data professionals.

Lakebase: PostgreSQL Integration via Neon

Just a month after acquiring Neon in a $1 billion deal, Databricks introduced Lakebase at Databricks Data + AI Summit 2025, a managed PostgreSQL offering integrated directly into the Data Intelligence Platform. This marks a significant shift, bringing a transactional SQL engine natively into the lakehouse ecosystem.

Lakebase allows developers to build applications and AI agents without worrying about the usual headaches of scaling storage and compute independently. By simplifying infrastructure and avoiding performance bottlenecks, Lakebase positions Databricks as an even more compelling option for full-stack data development.

Lakebridge: AI-Assisted Migration with BladeBridge

Databricks also launched Lakebridge at Databricks Data + AI Summit 2025, a new data migration tool built on the capabilities of BladeBridge, which it acquired earlier in the year. Lakebridge offers an AI-assisted experience for enterprises migrating data warehouses, SQL code, and business intelligence reports to Databricks SQL.

The timing is notable, as competitor Snowflake recently introduced SnowConvert, a similar agent-powered migration tool. Both companies are betting that helping enterprises bring their legacy systems into modern AI-powered platforms will be a major growth vector in the coming years.

Governance and Open Table Formats

In a quieter but equally important announcement at Databricks Data + AI Summit 2025 , Databricks revealed expanded support for Apache Iceberg within Unity Catalog, its centralized governance layer. This extension reinforces Databricks’ commitment to open data formats and multi-cloud compatibility while maintaining tight access control and lineage — a key concern for enterprises navigating complex compliance requirements.

Looking Ahead

The breadth of announcements at Databricks Data + AI Summit 2025 reveals a company moving aggressively to position itself not just as a lakehouse leader, but as a full-stack AI platform. From agentic automation with Agent Bricks to visual ETL in Lakeflow Designer and democratized analytics via Databricks One, the company is clearly targeting users across the technical spectrum.

While many features remain in preview and questions remain about maturity and scalability, the direction is clear: Databricks is betting that AI-powered tools, open standards, and unified governance are the keys to winning the enterprise data platform race — and it wants to set the pace.