Artificial Intelligence has rapidly evolved from a strategic consideration to a boardroom mandate. Enterprises today are actively investing in AI platforms like Vertex AI to unlock efficiencies, drive innovation, and create competitive differentiation.
However, while AI ambition is high, enterprise-wide scale remains limited.
Most organizations are still operating on legacy infrastructure, fragmented data environments, and architectures not designed to support the demands of real-time, production-grade AI.
AI initiatives are progressing—but not scaling.
The gap is not in models or intent, but in the foundation required to operationalize AI at scale:
Move beyond experimentation to scale AI across your organization
Identify infrastructure and data gaps holding you back
Leverage Vertex AI within an integrated ecosystem
Design scalable, cloud-native architectures
Modernize legacy systems to become AI-ready
The reality:
AI success is not determined by adoption alone—but by the ability to sustain and scale it across the enterprise.
To truly realize the value of AI, enterprises must move beyond isolated deployments and re-architect their environments for scale.
This requires a shift toward:
A clear understanding of why most AI initiatives fail to scale
The strategic role of infrastructure in enabling AI success
How Vertex AI fits into a broader enterprise transformation journey
Proven approaches to modernizing legacy environments
A roadmap to becoming a truly AI-ready enterprise
A clear understanding of why most AI initiatives fail to scale
Unified data ecosystems
Integrated AI platforms like Vertex AI
Architectures designed for continuous innovation
AI is no longer a layer on top.
It must be built into the core of the enterprise.
Registration
Kickoff
Google Presentation: From Vertex AI to Enterprise Readiness
Demo: Watch AI at work
Brio Presentation: Brio and Beyond
Q&A & Closing Remarks
Networking Dinner