Whitepaper

Addressing SaaS Sprawl will Free Up Budget for Agentic AI Success

A practical approach to reducing SaaS costs and funding agentic AI without expanding IT budgets.

Addressing SaaS Sprawl will Free Up Budget for Agentic AI Success

Every enterprise wants to do more with AI.

But finding the budget to make it happen? That’s another story. What if some of that money is already sitting in your existing software stack?

Over the years, enterprises have accumulated SaaS subscriptions, overlapping applications, and integrations that cost more to maintain. And the subscription fee is only the beginning.

According to HFS Research, every $1 spent on SaaS licenses can add $2 to $7 in implementation, integration, and upkeep. With agentic AI changing how enterprises build and run software, CIOs have an opportunity to rethink what they buy, what they keep, and what they could own instead.

But where do you start? And how do you reduce SaaS spending without disrupting the systems your business depends on?

This HFS Research whitepaper explores how enterprises can uncover hidden SaaS costs, make smarter decisions about their application portfolios, and turn the resulting savings into funding for agentic AI.

Inside the whitepaper, you’ll learn:

  • Six warning signs that your SaaS estate may be costing more than you think
  • A framework for deciding what SaaS capabilities should stay, go, or be replaced by AI
  • How to identify early savings opportunities without disrupting critical operations
  • What CIOs should consider before their next SaaS renewal
  • A practical approach to funding AI initiatives through existing technology spending

The whitepaper also explores how Hexaware’s Zero License offering reduce SaaS dependencies by rebuilding capabilities with AI agents and enterprise-owned code.

Your next AI investment might not need a bigger budget. Just a better look at the one you already have.

Download the whitepaper to discover where your SaaS spending could become your next AI opportunity.

Disclaimer: This whitepaper was first published on hfsresearch.com

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