Snowflake’s global head of financial services breaks down the CFO role in 2026

At CFO Brew, we know that every CFO is their own unique, special snowflake. At the same time, many CFOs are going to be dealing with some of the same issues in 2026. As the global head of financial services at AI cloud platform Snowflake (see what we did there?), Rinesh Patel gets a front row seat to CFOs’ pressing concerns.

His job is to keep tabs on internal and external trends to build products that will keep Snowflake’s corporate customers on the front lines of data management, and create cost and productivity efficiencies.

CFO Brew recently talked with Patel about the challenges he expects CFOs to face in 2026.

This interview has been edited for length and clarity.

What do you see as the biggest change happening in the CFO office this year?

The first is really a mindset shift. It’s become very clear AI is no longer about experimentation. There’s an acceptance that AI is clearly a powerful technology, and we don’t need to prove that anymore. That said, what we do need to prove, the only question CFOs have is really about the ROI. How do we prove the ROI?

Historically, it was all about this shiny, hot new model that was available. That’s shifted. Now, customers are starting with the commercial outcomes led by the business…Is the problem we’re solving acquisition, retention, margin, capital efficiency? Then they’re defining the data, the quality, the governance, the accessibility of data. And then lastly, they’re looking at AI large language models to be the connective tissue between the data and the commercial outcome.

So they don’t mention AI or the hot new model until the potential ROI is now defined, the data is defined, and crucially, the business is bought in. CFOs are becoming more use-case specific, focusing on productivity at scale.

Have you noticed a difference in the issues CFOs are raising with you?

What they’re asking for is fundamentally changed. What they’re asking for is, now, how do you help me solve this business problem? Not necessarily the workload, but the workflow. This is what we do today, and this is how we’re doing it today. And these are all the manual interactions that are taking place. These are all the inefficiencies. These are all the frictions. How can your technology take this workflow and really improve it?

How do you think CFOs need to change this year?

They are driving an increased level of accountability. CFOs are demanding clear ROI. Everything connected to revenue, cost, or time benefits. AI budgets are looking very much like capital budgets.

The second is production grade standards. What they’re really solving for is scale. How do I make sure these model pipelines are expected to run reliably and in production again and again and again? With a level of predictability, transparency, [and] results which allow for a level of cost effectiveness. And then fewer experiments, but deeper employments. Scaling to thousands across the firm, not just demoing to one or two users, so a shift from individual intelligence to enterprise intelligence.

Any advice for CFOs?

Bring AI to the data. CFOs don’t need to move sensitive financial data into external AI tools…The second is, CFOs have always been operating with a huge amount of sensitive information. So trust and governance is going to become crucial. Ensuring that that data never leaves a customer’s secure perimeter, making sure they have the right controls in place as to who should and who can get access to that data and the tools that underpin that, including the large language models. And I think the third thing is a focus on training an organization to be AI ready…I think the CFO’s office is certainly driving some of that training.