Enterprises have spent years—and millions of dollars—cleaning data, breaking silos, and building governance frameworks. Yet, when it comes time to scale Generative AI, projects stall, budgets explode, and latency cripples performance. Why? Because the enterprise is trying to run the future of intelligence on the infrastructure of the past.

In this hard-hitting session, we move beyond data preparation and tackle the physical realities of engineering AI at enterprise scale. We will unpack the "Three Laws of AI Data Physics"—Data Gravity, Unstructured Chaos, and Sovereignty—and explore why legacy architectures inevitably choke on modern AI workloads. 

Discover the strategic paradigm shift from moving your data to the AI, to bringing the AI directly to your data. 

Join this session to learn how leading organizations are utilizing turnkey, co-engineered architectures like HPE Private Cloud AI to eliminate integration guesswork, protect their intellectual property, and finally move AI from isolated science projects to production-grade reality.

Who Should Attend

Chief Technology Officers, Chief Data Officers, Enterprise Architects, and IT Infrastructure Leaders who are responsible for operationalizing and scaling enterprise AI initiatives