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Enterprise AI Spending Shift
Transition from application-focused AI investment to infrastructure-heavy spending.
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A veteran CFO's advice for managing budgets in the AI era
Finance chiefs need to think through three areas, says veteran CFO Amy Butte. Amy Butte 2026-05-04T10:01:01.291Z This post originally appeared in the Business Insider Today newsletter. You can sign up for Business Insider's daily newsletter here. Is being a CFO in the AI era one of the toughest jobs going? With CEOs plowing big money into AI, it sometimes feels like that. We're starting to see success stories, but tangible results aren't yet guaranteed.And for CFOs holding the purse strings, it's like standing between a hungry dog and dinner.I decided to ask someone who's worn those shoes. Amy Butte is a four-time CFO, including at NYSE and, most recently, Navan. She said the CFO role has always been tough, but there are some "unique" challenges this time around."It's always incumbent on a CFO to measure outcomes or measure impact and to translate the language of numbers into behavior or behavior into the language of numbers. But I think today we're dealing with rapid transformation, new usage of AI, new things to measure," Butte told me. "And so a CFO has to be willing to try new things — and let's remember, CFOs are not always risk takers." That doesn't mean CFOs need to reinvent the wheel. Butte said "old-school approaches" can work in this new environment. We talked through three key things for CFOs to be thinking about.Define success: Figure out what your investors are looking for to measure your growth. (Honestly, if you don't know that, you might have bigger problems.) Maybe it's revenue. Maybe it's pretax earnings. Maybe it's return on equity. Whatever the case, Butte said to make sure your AI bets are working toward that.Behind-the-scenes metrics: Now you can identify the key performance indicators that help you reach your ultimate goal (see above). Figure out a way to measure them. It could be comparing customer support interactions between AI and humans, or the percentage of code delivered successfully within a given timeframe.Don't be the one to stop innovation: "This is not the time for finance leaders to sit on the sidelines," Butte said. "It's important to take risks. It's important to try new things in an environment where change really can move the needle."None of this is set in stone. The measurements and definition of success can change, Butte said. Everyone just needs to be on board with the adjustments and make sure they're working together.She gave the example of someone who wants to get fit and lose weight. They might decide to...
CFOs Shift AI Budgets Toward Infrastructure Spend
In recent times, reports and statements from various firms show a pattern emerging in their resource allocation for artificial intelligence. They are shifting away from being heavily weighted toward applications to being centered on the system’s foundation. This change in strategy is impacting their AI budget enterprise-wide. The backbone of this move is an increasing focus on infrastructure spending, as firms realize the importance of scalable infrastructure to keep up with the expansion of artificial intelligence. Why CFOs Are Shifting Their Focus In most organizations, the early stages of AI investments involved acquiring AI tools, running pilots, and experimenting with them. However, as firms become more comfortable with AI and its benefits, the shortcomings of the infrastructure have become obvious. Some of the factors influencing the shift: AI model requirements increase. Cloud and data center dependency Scalability and security considerations Cost reduction in the long run From Apps to Infrastructure It represents a major shift in the enterprise’s approach to AI technology. Previous emphasis: AI-based software solutions and applications Innovations geared toward consumers Testing and trial runs. Present-day emphasis: Investments in data centers and cloud services Development of high-performance computing resources Storage and networking technologies This shift underscores the growing importance of infrastructure costs as the foundation of AI activities. Where Money Flows A closer look at enterprise budget allocation unveils a significant reallocation of funds. Key investment categories: Expansion of cloud infrastructures Creation of AI-compatible hardware (GPU, accelerators) Developing data pipelines and storage capabilities Setting up security and compliance standards The evolution of enterprise AI spending indicates the need for sustainable capabilities development. Traditional vs Current AI Investment Strategy Focus Applications Infrastructure Time Horizon Short-term gains Long-term scalability Spending Type Experimentation Core investment Risk Fragmented systems Centralized efficiency This shift shows why infra spending is now central to enterprise AI strategy. Effects on Technology Vendors The new spending pattern is changing the dynamics of competition. Positive for: Cloud technology providers Chipmakers Firms selling data infrastructure products Negative for: Independent AI software firms SaaS firms Comp...
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Finance Leaders: Managing Digital Risk + AI ROI - SAP Concur
In 2026, finance leaders face rising digital risk, pressure to prove AI ROI, and persistent data quality and skills gaps. Explore these challenges and key actions from SAP Concur CFO Insights research.
