Chris Andersen began his career in public accounting before moving into the faster-paced technology industry. He has since held finance roles at several technology companies, including Novell, Progress Software, Akamai Technologies, and Aqua Security.
Today, he serves as CFO of Flexera, which helps organizations gain visibility across their IT estates, including hardware, software, software-as-a-service applications, cloud services, data platforms, and AI. His responsibilities extend beyond finance and accounting to include legal, corporate development, IT, procurement, facilities, and the company’s data platform.
That broad perspective is becoming increasingly important as AI changes how organizations spend money on technology. Flexera’s latest analysis found that every organization surveyed uses generative AI public cloud services in some capacity, while 45% use them extensively. During our conversation, Andersen explained why those costs can be difficult to predict, how companies can measure AI’s return, and why CFOs must bring finance, IT, and FinOps together.
What led you to become CFO of Flexera?
My career began in public accounting. One of my largest clients was a traditional pulp, paper, and timber company. I enjoyed visiting its facilities around the country, but I found the corporate culture slow and bureaucratic. That experience became a career anchor and pushed me toward faster-paced technology companies.
Flexera stood out because it addresses a problem I had faced throughout my finance career: understanding what technology the company owns, who is using it, what it costs, and how to optimize it. The opportunity to lead finance at a company helping other CFOs answer those questions was compelling. After nearly a decade as a CFO, I honestly believe it is the best job on the planet.
Why are AI costs harder to predict than traditional software costs?
The two primary reasons are variability and visibility. Traditional software was largely a fixed cost. A company purchased a license or subscription and knew what it would pay. AI is consumption-based, so costs change with usage. Something that costs one amount today could cost three times as much tomorrow without the company signing another contract.
Visibility is equally important because AI expenses can appear throughout the profit and loss statement. They may be included in AI-enabled software renewals, cloud infrastructure, data platforms, API calls, usage-based agreements, or autonomous agents. Finance, IT, and engineering teams need visibility into those costs because they cannot establish effective governance and controls around spending they cannot see.
How can CFOs measure the return on an AI investment?
The calculation sounds simple in principle. A company must consolidate its large language model, token, API, data, and employee-related costs and connect that spending to measurable outcomes. Those outcomes might include productivity, revenue, cost avoidance, or improvements in customer experience. In practice, gathering that information and calculating the return can be difficult.
CFOs who are early in the process can begin with two questions: What problem are we trying to solve with this AI investment, and how will we know whether it worked? The size of the AI budget matters less than having the visibility to trace spending to results.
Should companies manage technology spending as closely as workforce costs?
Absolutely. Technology is now one of the largest controllable expenses after people costs at many companies, but the discipline used to manage it is still catching up. Organizations usually know who works for them, what those employees cost, and what they produce. They often lack similar clarity about cloud workloads, SaaS agreements, and AI tools.
The pressure to move quickly with AI makes that gap a financial risk. Finance leaders need to bring the same governance to technology spending that they already apply to headcount and other workforce costs.
How can finance and technology teams work together more effectively?
The first step is simply working together. Finance, IT, and FinOps teams do not need to report to the same person, but they do need to be aligned. I believe the CFO should be the uniting force that brings those groups together around a common framework.
Finance contributes planning, forecasting, and accountability. Technology teams bring an understanding of architecture, usage, and business needs that finance may not have. The best results come when those perspectives are combined and everyone is working from the same data.
How can IT asset management help companies reduce unnecessary software spending?
IT asset management is one part of the broader technology-spending picture. Flexera provides visibility across hardware, software, SaaS, cloud services, data platforms, and AI. It also gives customers tools to optimize some of those costs through increasingly automated processes.
Reducing unnecessary spending also gives CFOs an opportunity to redirect money toward areas that need additional investment. Once the company can see and optimize its technology costs, the CFO can work with the CEO to determine where those savings could create greater value.
How is Flexera changing the way it plans and measures technology investments?
We practice what we preach through a program called Customer Zero. We use our own products to manage our technology spending, improve visibility, and identify opportunities for savings.
The program also creates a valuable feedback loop. We can share what we learn with our product and go-to-market teams, helping them improve our solutions and the customer experience. Using our own technology therefore supports cost control while also strengthening our internal processes and products.
What advice would you give CFOs who are trying to support innovation while controlling costs?
First, do not treat innovation and cost control as an either-or decision. CFOs can fund AI investments by finding efficiencies elsewhere and redirecting that money toward areas that will help the company grow.
Second, get visibility before trying to establish governance because you cannot control what you cannot see.
Finally, serve as the uniting force across finance, IT, FinOps, and the rest of the organization. That alignment is essential for investing in innovation while maintaining control over spending.
Chris Andersen began his career in public accounting before moving into the faster-paced technology industry. He has since held finance roles at several technology companies, including Novell, Progress Software, Akamai Technologies, and Aqua Security.
Today, he serves as CFO of Flexera, which helps organizations gain visibility across their IT estates, including hardware, software, software-as-a-service applications, cloud services, data platforms, and AI. His responsibilities extend beyond finance and accounting to include legal, corporate development, IT, procurement, facilities, and the company’s data platform.
That broad perspective is becoming increasingly important as AI changes how organizations spend money on technology. Flexera’s latest analysis found that every organization surveyed uses generative AI public cloud services in some capacity, while 45% use them extensively. During our conversation, Andersen explained why those costs can be difficult to predict, how companies can measure AI’s return, and why CFOs must bring finance, IT, and FinOps together.
