Cloud Economics and AI FinOps: Architectural Governance, Unit Economics, and Autonomous Cost Optimization

#AI #architecture #economics #FinOps #Cloud #Economics #Cost #Optimization #STEM
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Talk Series: GAP 0.1 (5th Talk)


  Date and Time

  Location

  Hosts

  Registration


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  • 960 River Road
  • TEANECK, New Jersey
  • United States 07666
  • Building: Becton Hall
  • Room Number: 205
  • Contact Event Hosts
  • Co-sponsored by Olsen College of Engineering and Science, FDU, Teaneck, NJ 07666
  • Starts 04 September 2026 04:00 AM UTC
  • Ends 16 September 2026 05:00 PM UTC
  • No Admission Charge

  Speakers

Satya of Ernst & Young (EY) LLP

Topic:

Cloud Economics and AI FinOps: Architectural Governance, Unit Economics, and Autonomous Cost Optimization

As enterprise software shifts from fixed, per-seat SaaS licensing to dynamic, activity-based AI consumption (tokens, credits, and capacity), traditional cost models no longer suffice. This session introduces AI FinOps—a discipline tailored to manage the unpredictable costs driven by user prompts, multi-step agents, and model architectures. It outlines the five foundational pillars of AI governance (inventory, visibility, attribution, guardrails, and value), examines the continuous optimization lifecycle, and explores how Agentic FinOps can autonomously assist with telemetry, policy enforcement, and cost optimization

Biography:

Satya Prakash is a Senior Cloud Architect Manager at Ernst & Young LLP, specializing in enterprise-scale Cloud and AI solutions, Azure Architecture, FinOps, and modern application delivery. With over 18 years in the technology industry, Satya leads large-scale digital transformations and actively publishes research at the intersection of Agentic AI, Machine Learning, and cloud economics. He holds a master’s degree in advanced software technology and industry credentials including Azure Solutions Architect Expert and FinOps Practitioner. Satya is a Startup Board Advisor, IEEE Senior Member, and an IETE Fellow, contributing regularly to academic and industry ecosystems as an IEEE conference reviewer and technology judge.

Email:

Address:New Jersey, United States




Agenda

Abstract

As enterprise software shifts from fixed, per-seat SaaS licensing to dynamic, activity-based AI consumption (tokens, credits, and capacity), traditional cost models no longer suffice. This session introduces AI FinOps—a discipline tailored to manage the unpredictable costs driven by user prompts, multi-step agents, and model architectures. It outlines the five foundational pillars of AI governance (inventory, visibility, attribution, guardrails, and value), examines the continuous optimization lifecycle, and explores how Agentic FinOps can autonomously assist with telemetry, policy enforcement, and cost optimization.