9 themes defining the unified data and AI platform at the Databricks Data + AI Summit

Enterprise AI is moving beyond experimentation as organizations focus on deploying governed, cost-effective systems that deliver measurable business value. Meanwhile, companies are increasingly investing in a unified enterprise data platform to bring together data and AI and create a foundation for production-scale intelligence.

During the Databricks Data + AI Summit 2026, theCUBE host John Furrier (pictured, right), co-founder and chief executive officer of SiliconANGLE Media Inc., spoke with Databricks leaders and customers about how the company and its ecosystem are helping enterprises move from fragmented data and AI experiments toward governed, production-ready intelligence at scale.

“Data is going to be the key and unification — bringing it all together is the fun part,” Furrier said. “With AI, the value is when the engagement of the users and the domains are using it. That’s really the value.”

Here are nine themes defining the unified enterprise data platform.

1. There’s a move beyond AI pilots.

Enterprise AI is moving from experimentation to deployment as organizations focus more on value, ROI, governance and security. There’s an effort to ensure customers have access to the best AI agents at a great cost and with a great experience as the enterprise data platform becomes the foundation for production AI, according to Jonathan Frankle, chief AI scientist at Databricks Inc. Governance and quality, meanwhile, remain critical because organizations will not deploy AI systems they do not trust.

Catch the full segment on theCUBE.

2. There’s a need for localized AI adoption.

Europe presents a unique AI landscape due to its mix of countries and varying levels of digital maturity. The company addresses that complexity by maintaining local teams and engineering resources across the region to stay close to customers and their specific needs, according to Samuel Bonamigo, senior vice president and general manager of EMEA at Databricks. By listening to organizations across different industries and maturity levels, the company aims to share knowledge and help customers take advantage of the latest platform technologies.

Here’s theCUBE’s complete interview.

3. There’s a move toward a single copy of data.

The LTAP (Lake Transactional/Analytical Processing) is designed to eliminate the complexity of managing multiple database copies, brittle pipelines and the movement of data between systems. The platform translates row-based PostgreSQL data directly into a columnar format, helping create a more streamlined data architecture. The result is a single copy of data in an open format that customers can access with the existing tools and workflows they already use, according to Bryan Clark, director of product management at Databricks.

Catch the entire segment on theCUBE.

4. There’s a rethinking of how businesses operate.

Major technology transformations often begin with infrastructure before moving up the stack, and Databricks has aimed to help drive that progression by bringing together data science as well as analytics and business intelligence capabilities. The next major shift will be the re-architecture of the software silos that have long existed across data centers and SaaS environments, according to Mike Palmer, chief executive officer of Sigma Computing Inc.That transformation is expected to reshape how organizations build on their enterprise data platform, restructuring business workflows, productivity and software usage as organizations increasingly rebuild operations around AI.

Don’t miss the full segment on theCUBE.

5. There’s a need for machine-speed security.

AI-powered attackers are becoming increasingly automated, using agents and large language models to identify vulnerabilities at a speed and scale that was previously impossible. At the same time, the rapid pace of software development is creating more vulnerabilities as organizations produce code faster than ever, according to Patrick Wright, chief technology and operations officer of National Australia Bank Ltd. As a result, security teams must broaden the data they monitor and automate more security operations, shifting from manual processes to agentic, machine-speed defense.

Watch theCUBE’s full exclusive.

6. There’s a focus on decision intelligence.

AI’s value extends beyond workflow automation to improving the decisions organizations make on behalf of their customers. For Addepar Inc., the goal is to connect processes across the business, from operations, risk management and data quality to front-office investment and portfolio decisions. The greatest value is realized when AI helps advisors and investors make better-informed decisions that directly impact financial outcomes, according to Bob Pisani, chief technology officer of Addepar.

For the full story, check out the segment on theCUBE.

7. There’s a growing investment in AI talent and skills.

Databricks is seeing strong momentum internationally, particularly in the Asia-Pacific region. To support that expansion, the company is continuing to grow its regional team and customer presence. There is also a plan to train more than 700,000 people across the region to help build data and AI skills, according to Simon Davies, senior vice president and general manager at Databricks.

Catch the entire segment on theCUBE.

8. There’s a push to build agentic AI on a unified data foundation.

Intercontinental Exchange Holdings Inc. is using Databricks Unity Catalog as part of a hybrid AI and analytics platform designed to process large volumes of unstructured data more efficiently and compliantly. It is also exploring how agentic AI can further optimize those workflows across the organization. The effort extends to customer-facing applications, where AI-powered chat and voice capabilities are being embedded into core business services, according to Anand Pradhan, vice president, head of the AI center of excellence and mortgage data at Intercontinental Exchange Holdings.

Don’t miss the full segment on theCUBE.

9. There’s a growing focus on the enterprise data platform.

To support its global operations, PepsiCo Inc. has spent several years modernizing its data infrastructure and moving the majority of its data backbone to the cloud. The company adopted a Databricks lakehouse architecture to unify fragmented data, improve governance and create a standardized foundation for analytics and AI. The goal is to accelerate the path from data to insights and action by building a unified enterprise data platform that provides cataloged, secure and harmonized data across the enterprise, according to Magesh Bagavathi (center), senior vice president and global head of data, analytics and AI at PepsiCo.

Here’s theCUBE’s complete interview.

Here’s the complete video playlist, part of SiliconANGLE’s and theCUBE’s coverage of the Databricks Data + AI Summit 2026:

Photo: SiliconANGLE