Cost Discipline Is the Missing Operating Model for Scaled AI

Featuring Research from Forrester
AI Cost Optimization: The Why, What, and How

 

thank you

 

Thank you for your submission!

 

Optimizing Enterprise AI: Balancing Cost, Value, and Scale

With the growing frenzy around generative AI (genAI), companies today are scrambling to instill AI into products and workflows while building production-ready use cases.

The core concepts leaders must focus on: Cost levers and weighing the trade-offs.

How can organizations optimize their AI costs without compromising outcomes? How can tech leaders weigh the trade-offs between cost reduction and value optimization?

This report outlines Forrester’s best-practice framework and the key levers organizations need to understand for effective AI cost optimization. EdgeVerve recommends this framework for CEOs seeking to build sustainable AI initiatives, enabling them to strike a balance between cost and results while confidently scaling AI enterprise-wide.

Key Takeaways

Automation Blueprint

Transition to a cohesive, platform-based strategy for effectively harnessing Agentic AI
Automation Prioritization

Role of EdgeVerve AI Next in equipping organizations with an agentic workforce
Automation Blueprint

Getting AI costs under control to maximize business outcomes
Automation Prioritization

Leveraging AI cost levers to make informed trade-offs between cost, performance, and AI efficacy risk

Automation Prioritization

Establishing a financial backbone that puts cost in the context of AI ROI

EdgeVerve Contributors

Swaminathan Natarajan,

VP & Engineering Head,
EdgeVerve

Sathish Kumar E V,

AVP- Product Management,
EdgeVerve

How EdgeVerve AI Next Powers FinOps-Driven AI Operations

Discover how EdgeVerve AI Next embeds FinOps into the operational fabric of the platform, enabling real-time visibility into infrastructure and compute usage, spend guardrails, and value-aligned consumption patterns.

Download Report

Request a Meeting