HPE CFO Marie Myers aims to transform finance operations with AI

It goes all the way back to 1997, the year Marie Myers joined Compaq Computers, and when artificial intelligence first made headlines when the IBM supercomputer Deep Blue defeated world chess champion Garry Kasparov.

That was more than a quarter-century ago, but two years after taking over as Hewlett Packard Enterprise’s CFO, Myers said AI is still in the early stages of reinventing the way companies and finance teams operate.

After HP’s original unit, Hewlett-Packard Co., acquired Compaq in 2002, Myers remained with the company in an increasingly prominent role until 2018, when she took over. First CFO job We partner with UiPath, a leading robotic process automation vendor. As a global controller at HP, she was an avid user of UiPath products.

She returned to HP a year later and was promoted to the CFO post by early 2021, before moving to finance a year before that. At HPEHPE ranks 143rd on the 2025 Fortune 500 list with sales of just over $30 billion and is primarily a vendor of server, storage, and networking technologies.

Myers is currently aiming to become an AI innovator. are cooperating We worked with Deloitte to develop CFO Insights. It combines agent and generative AI in one solution, powered by the Deloitte platform and running on HPE’s private cloud AI. According to a recent blog post from Deloitte, the parties call this a “purposeful transformation” that will shift the CFO’s focus from “retrospective performance analysis to forward-looking enterprise intelligence.”

In a conversation with CFO.com, Myers discusses his evolving role at HPE, some AI use cases, and the challenges of upskilling his workforce to AI proficiency.

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marie myers

Hewlett Packard Enterprise CFO

First CFO position: 2018

Notable previous employers:

• HP Co., Ltd.
• UiPath
• compaq computer

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This interview has been edited for brevity and clarity.

DAVID McCANN: How would you describe HPE’s current identity and its relationship to AI?

Marie Myers: HPE is at the heart of the data center, and the data center is the heart of AI. We are an infrastructure provider for everything from servers to storage to networking. When you look at building large scale infrastructure, a lot of the infrastructure is provided by us, but we obviously compete with Dell and other companies.

You were a traditional HP employee for several decades, with the exception of a short stint outside the company, before moving to HPE two years ago. Why did you make that switch?

We saw an opportunity for AI. When I started my RPA journey, it became clear that automation alone could not solve many of the problems I faced as a CFO.

At that time, we automated many tasks, built RPA and started early machine learning. But we understood that GenAI in particular was a new wave of transformation and that HPE could be a key player.

In that regard, I understand that your innovative work today is focused on how agent AI and GenAI can transform these data management processes. How does this transformation work with CFOs?

This benefits decision-making and positions them as architects of agile, efficient, and future-ready organizations. While the CFO is clearly the primary driver of capital allocation, they are also the stewards of how the company moves forward on this journey.

During earnings calls, most CFOs talk about how their companies are leveraging AI. You can’t be a CFO today without knowledge of AI.

At HPE, we’ve been trying to find the most important processes [that can be enhanced with AI]. For example, the financial sector is applying GenAI to operational reviews. We have a conference call every Monday that lasts about an hour and a half with all of our business leaders, and traditionally our finance team would create a PowerPoint of about 100 pages.

When I took on this role, I realized that an AI platform could (1) make a huge difference in the amount of preparation that was done and the quality of reporting, and (2) redirect the conversation from what happened to what to do about it by looking at data in real time, rather than stale information that probably took a weekend to prepare.

In other words, CFOs are no longer just reporters. You can play a very active role in guiding AI transformation through these initiatives and showing others in your company how to approach AI transformation.

One of the questions that keeps coming up with AI is how to apply it responsibly. Can you give an example of how that manifests itself within HPE Financials?

There are governance and management issues that need to be resolved. One of the issues we’ve been working on is around data accuracy and accuracy. [resulting] insight. You’ve probably seen this before: If you ask two models the same question, they don’t necessarily get exactly the same answer. And in finance, you can’t get different answers from your team members. If the return is 99.9, it should be 99.9 regardless of who asked the question. So we worked with NVIDIA to build it. [our own] model.

I think the reskilling of organizations required to make AI reliable within the enterprise is a big issue.

Yes, this is one of the biggest problems we have to solve, but I think it’s the most underrated problem. When implementing RPA a few years ago and now AI, I learned the hard way that when projects don’t succeed, some of the reasons are: [usually] A lack of understanding or investment in change management.

You need to prepare your organization and invest in it. This may include transforming your workflow. Agent AI must do so because some workflows can be very sloppy and AI cannot reproduce sloppy workflows.

Additionally, we need to identify the roles that agents have and the roles that humans have. Humans need to feel that they have a role in this new world.

We did a lot of re-education on RPA years ago, teaching people how to build bots. Now, we’re teaching them how to build agents so they can decide which workflows to automate to improve productivity.

At what level are people reskilling? Everyone in the financial world?

My organization has over 3,000 employees, which is a little broader than finance. My leadership team is looking at the changes we’re driving and the metrics and outcomes we want to get from them. No organization hierarchy can be omitted.

Considering the continued development of AI tools, it seems necessary to continually improve skills. ○Is it possible that there is a visible plateau where most of what is currently envisioned is plugged in and there is some kind of stagnation for a while?

Oh, I think we’re in a very early innings now. The real impact in terms of financial transformation is yet to be seen.