In 2018, Marie Myers left HP after a decade-and-a-half to be CFO of RPA software company UiPath. Though she only stayed a year, the detour was crucial in her career journey.
Myers got to work with some of the coders on the “frontier” of AI and RPA. “It gave me a much better backdrop and appreciation for tech and the role that AI and digital transformation play in the enterprise,” said Myers, now CFO of Hewlett Packard Enterprise (HPE), the server, storage, cloud and networking company that split off from HP’s PC and printer businesses almost a decade ago.
Not coincidentally, after UiPath, Myers returned to HP in 2020 as chief digital transformation officer.
Myers will give the morning keynote presentation at the CFO Leadership Conference in Dallas on Wednesday. To get a sneak peek, we talked with her earlier in the month to discuss her first year at HPE, an upcoming transformative acquisition, and the horizon for applications of GenAI in corporate finance.
What did you move over to HPE? What opportunities did you see?
I was excited about the inflection point of AI. I felt like HPE was uniquely positioned to win in the subsequent waves of the Industrial Revolution. The company is based in Houston, so it made sense geographically. Finally, we’re acquiring Juniper Networks, a very transformative transaction I wanted to be part of.
More than half of our operating profit will come from networking, a very margin-rich business. Secondly, [the Juniper deal] puts us squarely as number two in the market. I’m a big fan of Geoffrey Moore, who wrote Crossing the Chasm. He said you must be number one or number two in a business to succeed.
What was your first exposure to AI?
About eight years ago I started building software bots—RPA, or robotic process automation. I was one of the first enterprise customers for UiPath in the United States. And I became intrigued by what AI could do in finance. I built probably the largest set of finance bots for the enterprise. We used that as a base to create more exciting models to help with accounting and forecasting. And that’s what got me into AI; I saw the opportunity in finance.
When I started in the HP enterprise business, I was a product manager; I used to build spreadsheets and pivot tables. Back in those days, you had to download all the data constantly. Today, you can write bot scripts and use AI to update data. I used to do regression analysis; I was a real progression nerd. Today, AI can build many of the algorithms to help with forecasting.
There are differing views on use cases for GenAI in finance and accounting. What have you seen, and are you deploying GenAI at HPE?
We’re looking at some early use cases. Interestingly, the use cases have a lot of similarities to some of the use cases we saw for RPA. Areas like forecasting rise to the surface very quickly as one of the more significant pain points for finance. How can GenAI augment our forecasting processes?
Some early wins in GenAI are in places you’d expect, like credit and collections. Overall, I’d say it’s nascent from a finance perspective. I just peeled off an organization to focus on AI innovation. I have a gentleman on my staff who will lead finance innovation around AI in addition to his day job. As with RPA, you must be deliberate and intentional about AI use cases are and then be pragmatic about driving outcomes.
Where will the ROI come from in some of these early AI use cases?
Apparent areas like forecasting tend to be very manual and people-intensive, so it’s relatively straightforward to identify productivity gains. Then there are financial gains from forecasting more accurately and more precisely.
One area that I’m interested in is IR [investor relations]. In my last job, we were early adopters of GenAI in IR. We used Gen AI to help us with sentiment analysis of [earnings] scripts. Before going to the Street, you run a sentiment analysis to see your overall tone.
The other application of GenAI in IR is to assess the tone of the entire earnings period quickly. Each earnings season has nuances in tone. In my last job, we took all the transcripts and all the analyst questions to help predict the questions that might be [asked] on the earnings call.
You mentioned the Juniper Networks deal. You were involved in the transaction that divided Hewlett-Packard into HP and HPE. What is it about large acquisitions and transactions like and the Juniper deal that appeals to you?
I was actually on the split team, and I was on the finance team that set up HP. It was a swift, action-packed period. We had to split the company in less than 12 months, and I had the chance to lead the whole financial setup. What I loved about it was you had to make fast decisions. Sometimes, I feel that all the collaboration we do elongates our decision-making. In that transaction, you had to get comfortable making a hard decision when you had only 60% or 70% of the data. Because unless you checked the box, the deal wouldn’t happen. It also tested our cross-collaboration skills. It involved figuring out everything from how to operate in Turkey, for example, to what tax structure would be used.
What would you say your leadership philosophy is in the day-to-day operations?
I’m Australian, so by nature, I’m collaborative but direct. I like to empower people to get the job done—setting the strategy and the vision and letting people get on with it. Everybody here agrees that the outcome is better when you work as a team and promote diversity of opinion. The last thing I want to do is get into the room and have everybody agree. But once you make a decision, move on.
