Migrating/Scaling AI Workloads for Enterprise ROI on AWS – Going beyond Pilots or Isolated Use Cases

Executive Dinner

April 1, 2026 - Atlanta, GA

Visionaries

Anand Saokar Wellstar Health System
Anand Saokar

Head of Omnichannel Experience & AI Data Platforms

Wellstar Health System

About Me

Anand Saokar is the Head of Omnichannel Experience & AI Data Platforms at Wellstar Health System, where he oversees a multi-million-dollar AI and data transformation portfolio. With a unique career arc that spans from building Amazon’s "Today’s Deal" promotion platform to spending over four years navigating healthcare’s regulatory and clinical complexities, Anand brings 20+ years of tech-operator expertise to shipping production-grade agentic AI. At Wellstar, he has driven greenfield AI initiatives to production in under nine months - deploying live agents across HR, Talent, Marketing, and Contact Centers - while architecting a unified Patient360, Provider360, and Teammember360 platform on a robust stack that integrates EPIC, FHIR, Dynamics, Workday, and ServiceNow. A proven enterprise leader, his career includes standing up global delivery centers for $250MM+ portfolios, driving ML-led digital transformation at Macy’s, and spearheading critical distribution and fulfillment strategies at Lowe’s and SunTrust. Anchored by the belief that AI success relies on data plumbing, org design, and change management, Anand is a hands-on technical strategist (proficient in Claude, Azure AI, Databricks, and GCP) who helps healthcare provider enterprises and high-growth health-tech companies scale impactful, real-world AI solutions.

April 1, 2026

Agenda

All times Eastern Time

5:30 PM - 9:00 PM

Migrating/Scaling AI Workloads for Enterprise ROI on AWS – Going beyond Pilots or Isolated Use Cases

Many organizations have successfully experimented with AI and machine learning, yet few have translated early pilots into scalable, production-grade systems that deliver sustained business value. As AI adoption accelerates in 2026, the challenge is no longer whether to invest in AI, but how to modernize legacy ML workloads, control infrastructure costs, and architect platforms that can support enterprise-scale performance, governance, and return on investment.

Designed for senior technology, data, and engineering leaders, this peer-to-peer engagement brings together technology and data leaders to explore what it takes to move beyond proof-of-concept deployments and isolated use cases toward fully operational AI systems on AWS. Executives can expect to walk away with a bank of insight into designing production-ready AI platforms that move beyond isolated use cases and support long-term business impact.


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