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By Jay Litkey, SVP of Cloud & FinOps at Flexera
Large companies like Meta, Microsoft, and OpenAI are pouring billions into AI infrastructure as the race to deploy AI spans across every sector. The AI boom is impossible to ignore, yet one lingering question remains: who’s going to prove the ROI?
Flexera’s recent IT Priorities Report found that 94% of IT leaders are looking to integrate AI into their tech stack, yet only a shocking 19% say demonstrating AI effectiveness and ROI is a priority. As organizations continue reporting disappointing results from early AI experiments, they are beginning to realize that the AI hype cycle without defined outcomes or financial governance is risky. 2026 will force companies to instead return to the basics.
The Challenge: AI Without Defined Outcomes
In today’s competitive landscape, it’s no longer realistic for organizations to ignore AI’s impact. Reflected in the same Flexera survey, 80% of IT decision-makers reported increased AI spending and over a third (36%) believe they’re overspending on AI applications.
Experimentation with Al is the new normal, but Al is an expensive experiment, especially as many projects are not landing as expected. With AI often integrated across multiple facets of an organization, many businesses struggle to calculate the actual ROI and are entering the AI hype cycle without defined outcomes or financial governance. This oversight leads to various business risks, including:
- Wasted spend: The ROI from AI isn’t just about direct savings-it’s about enabling teams to make smarter decisions, encouraging cross-team collaboration, and eliminating waste. Without a clear strategy, AI can quickly become a cost accelerant rather than a value multiplier.
- Disjoined initiatives: Consolidating siloed efforts starts with acknowledging that AI will show up in pockets across the business. Whether or not leadership has a step-by-step strategy perfected, companies can bring informal AI use cases into the open by engaging employees.
- Vague long term business impact: Because AI does not always produce immediate ROI, it is important to make a business case positioning AI as a driver of company-wide transformation, rather than focusing on the short-term.
A few years into the AI revolution, companies are recognizing that proving AI success requires a return to foundational practices.
The Solution: FinOps as the Bridge Between Investment and ROI
In the year ahead, leaders must remember that FinOps isn’t just about cutting costs: it’s about bridging the gap between finance, engineering, and business teams to work around shared goals. With widespread alignment, companies can better measure AI investments and ensure they’re delivering a lasting impact without stunting innovation. Companies that treat FinOps as a key strategic step rather than an afterthought will be the ones turning their 2025 AI investments into 2026 success stories.
By establishing mature FinOps practices and discipline early in the cloud adoption process, organizations can optimize costs, reduce waste, and ensure that their cloud usage aligns with business priorities. This enables them to steer their cloud usage intentionally and build more sustainable cloud practices that support AI innovation without compromising financial health.
How Leaders Can Reset in 2026
Starting with a proof of concept before beginning AI experimentation is essential to avoiding unnecessary tech debt in today’s AI hype cycle. A strong financial strategy is the first step to any successful project. By leveraging timely, data-driven insights to help improve forecasting and encouraging cross-functional accountability and collaboration, a comprehensive FinOps infrastructure has proven invaluable for curbing overspending and maximizing business value. FinOps principles are not limited to cloud cost management alone, offering a viable option for AI spending as well.
In 2026, leaders can reset their approach to AI by starting with defined objectives and measurable outcomes prior to deploying AI. To ensure long-term business impact, organizations can establish FinOps playbooks that track AI governance and business goals. Equally important is fostering collaboration between teams to maximize ROI and break down silos.
Lessons Learned from 2025
Companies that ignore governance and ROI risk repeating experiment failures and losing their investment in the process. By building intentional FinOps strategies and governance, organizations can elevate AI from an idea to a true competitive advantage.
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ABOUT THE AUTHOR
Jay Litkey is a governing board member of the FinOps Foundation and serves as SVP of Cloud & FinOps at Flexera. He joined Flexera through the acquisition of Snow Software, where he played a pivotal role following Snow’s acquisition of Embotics, a company he founded. He has over 25 years of executive leadership experience (CEO, president, EVP) in enterprise software, SaaS, FinOps, and Internet companies.
