Databricks Announces $3 Billion Investment Across Europe and the Middle East to Accelerate Enterprise AI
Databricks has announced plans to invest approximately $3 billion across Europe and the Middle East over the next three years, marking its largest regional investment outside North America. The expansion aims to accelerate enterprise artificial intelligence adoption, strengthen research and development capabilities and support organizations moving AI projects from pilot stages into large-scale business operations.
Announced on November 11, 2026, the investment will expand Databricks' regional engineering teams and increase the availability of technical experts who can work directly with customers and partners. The company also plans to strengthen its support for startups and expand data and AI education initiatives across Europe, the Middle East and Africa (EMEA).
Expanding Enterprise AI Capabilities
A major focus of the investment is expanding adoption of three products within the Databricks Data and AI Platform: Lakebase, Genie and Unity Gateway.
Lakebase is a serverless PostgreSQL database designed for AI applications and agents. Genie enables users to interact with business data through natural-language questions and receive answers grounded in organizational information. Unity Gateway provides governance, AI model routing and cost-management capabilities.
Together, these technologies are designed to address key enterprise challenges, including data context, security, platform flexibility and the costs associated with scaling AI systems.
Databricks aims to help organizations build AI applications that understand their business operations while maintaining control over data access and model usage.
Strengthening Regional Operations and R&D
Databricks currently employs more than 2,000 people across EMEA and plans to increase its regional workforce by approximately 50% over the next three years.
The company has also opened four new offices in Amsterdam, Milan, Zurich and Frankfurt. Its engineering hubs in Amsterdam, Berlin, Belgrade and Aarhus are being expanded to bring product development closer to regional customers.
Organizations including adidas, Danone, Heineken, HelloFresh, Mercedes-Benz and Nationwide already work with Databricks on data and AI initiatives.
The additional investment is expected to improve customer support and help enterprises address regional requirements related to governance, AI model selection and infrastructure costs.
Training 500,000 People in Data and AI
Alongside infrastructure and product development, workforce education is another important part of the announcement.
Databricks plans to train approximately 500,000 students and professionals across EMEA in data and AI skills by 2030. The programme will cover areas such as building agentic applications, using AI assistants and developing skills in context engineering.
The company also reported that more than 80,000 people across EMEA signed up for its Free Edition over the past year, while professional certifications earned through its regional partner network increased by 70% year over year.
Supporting the Regional Startup Ecosystem
Databricks is also increasing its involvement in the regional startup ecosystem. Over the past six months, it has invested in French observability startup Tsuga, UK-based Advancing Analytics and AI startup Applied Computing through its investment and accelerator programmes.
The company also works with startups such as Flo Health, GetYourGuide, Linkup and Xoople, while supporting founder communities including STATION F in Paris.
A Larger Push Towards Enterprise AI Adoption
The planned $3 billion investment reflects growing demand for enterprise AI solutions across Europe and the Middle East. Businesses are increasingly looking beyond experimental AI projects and focusing on systems that can deliver measurable operational value.
By expanding its technology platform, engineering presence and training initiatives, Databricks aims to strengthen its position in the regional enterprise AI market.
The success of this expansion will depend on how effectively organizations translate AI capabilities into practical business outcomes, supported by reliable data, strong governance and skilled teams.
