For decades, finance teams have been branded as the “cost center” of the enterprise, a department primarily responsible for controlling budgets, approving expenses and delivering reports.
“Go to the finance team to get your expenses approved, right? Or to check on your budget, and they say yes or no,” Emanuel Pleitez, head of finance at Finix, said during a discussion for the PYMNTS B2B Payments 2025 event series “B2B.AI: The Architecture of Intelligent Money Movement.”
But that was then. Now, in an era defined by real-time data, global volatility and investor expectations, CFOs are reimagining their function as something far more ambitious: a driver of enterprise value.
The first step isn’t technology. It’s mindset. Too often, Pleitez said, finance professionals are seen as gatekeepers.
“But every single day we are spending money and we need to get an ROI on it,” he said.
For the embrace of artificial intelligence (AI) across the finance function in particular, this investor-style mindset has made AI adoption less about experimentation and more about hard value creation.
Companies are asking not “Should we try this?” but “How will this improve cash flow, forecasting accuracy, or decision speed?”
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Understanding AI’s Limits
The market is crowded with AI vendors promising transformation, but finance teams are learning to separate utility from vaporware. Many tools still buckle under the complexity of enterprise financial models, and CFOs are candid about the gap between promise and reality.
Pleitez has tested the limits himself: “I tried every single AI for Excel … and it just wigs out and can’t really comprehend the whole thing,” he said. “It starts telling you, actually maybe just load one little analysis at a time and think of like 20 silos. So, then the human still needs to know how to connect all the dots.”
The breakthroughs, it turns out, are in micro wins. Finance teams are using AI to accelerate reconciliation, refine SQL queries, and validate invoicing patterns.
“We’ve been able to shave off a couple days in a month just by using better AI tools to better reconcile data, better ensure that we’re having the right invoicing patterns,” Pleitez said.
These small victories matter in high-volume environments like payments, where shaving days off a monthly close can free up liquidity and sharpen decision-making. That speed, after all, can translate into better cash flow visibility, faster closes, and improved agility.
When asked about “data intelligence,” the foundational hygiene that enables AI to work, Pleitez drew a sharp distinction between enterprise-scale AI and micro-level use cases.
On the enterprise side, he was blunt: “You need to make sure your data is structured for the things that you need to be the most precise about … because if the AI gets confused … and starts hallucinating, then you’re screwed.”
That’s why, for its part, Finix has resisted massive, budget-heavy AI integrations. Instead, the company opts for incremental wins.
“If you just start using AI today without needing to make the big five, 10% of your budget investment into it, you can actually extract and get five to up to 20% more productivity gains,” said Pleitez.
It’s a pragmatic, low-risk approach, and one that allows the finance team to learn by doing, rather than staking the company’s future on unproven platforms.
Automate the Repetitive, Elevate the Human
The frontier question for CFOs is trust: How much autonomy should AI have in financial operations? So far, the answer is limited. Most teams, wary of error rates, keep AI firmly in the role of assistant rather than agent.
“We live and die by those dollars and cents, and we just cannot get it wrong,” Pleitez said, noting that, at least for now, human judgment remains the ultimate control system.
Finix itself currently focuses its AI investment primarily on semi-automated solutions, like custom GPTs trained on internal documents that can accelerate knowledge retrieval but stop short of making financial decisions.
Despite the short-term caution, Pleitez’s long-term vision is bullish. He imagines a future where month-end closes run themselves.
“If I can create an agentic way of doing this, where we can just know that on the first of the month, the month-end close process is already going … and within a few days we close the books, great. Phenomenal. I want it to happen,” he said.
Even more transformative would be an AI fluent in Finix’s own financial models, able to answer strategic questions like whether to pursue acquisitions or enter new markets.
“It is not rocket science. It should be possible. It will be possible, but it’s not there yet,” Pleitez said.
Ultimately, what’s emerging is a new mandate for CFOs: Guard capital, yes, but also deploy it strategically to accelerate enterprise value. AI is no longer a side experiment but is becoming core to that mission.
Source: https://www.pymnts.com/
