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Artificial intelligence (AI) has become the new electricity powering financial operations, and nowhere is this more apparent than in the office of the CFO.

“It’s no longer a nice-to-have,” Steve Wiley, VP of product management at FIS, told PYMNTS. “Artificial intelligence is a must-have, and that’s happened very, very quickly.”

Even as recently as a year or two ago, AI was considered a fringe benefit or experimental tool. Now, amid a backdrop of growing macro uncertainty, AI systems are becoming increasingly embedded in the core strategic infrastructure of finance departments, particularly across key functions such as treasury, payments and risk mitigation.

“Seventy-five percent of knowledge workers, and those are people in the office of the CFO, now use AI at work, and half of those started using it in the last year,” Wiley said. “There’s an expectation now that AI-based solutions will be embedded within these financial products.”

Still, why now? Historically, the office of the chief financial officer (CFO) has lagged in forward-facing functions like marketing or customer service when it comes to technology adoption. But ongoing inflationary pressures and volatile global markets have forced the hand of finance leaders when it comes to embracing digital transformation at pace.

“AI makes technology a real differentiator for a business,” Wiley said. “And the expectation will be for CFOs to adopt those technologies and work with partners who can facilitate that.”

Read also: FIS Introduces ‘Treasury GPT’ in Conjunction With Microsoft AI

AI Finds Its Footing in Finance

There are two main, and growing, categories of AI usage: qualitative applications, such as language-based interfaces that enhance knowledge discovery and communication, and quantitative applications, like predictive analytics, cash forecasting and fraud mitigation.

While qualitative tools can improve user engagement and reduce training overhead, it’s the quantitative applications that are radically shifting finance’s functional value.

“People were using tools like ChatGPT to formulate policies, learn best practices — all outside of the enterprise system,” Wiley said. “There was an immediate opportunity to embed that within the system. Tools like Treasury GPT from FIS are leveraging that AI technology to offer that data access specifically for the treasury industry.”

Take cash forecasting. Traditional methods rely on backward-looking statistical models. But generative AI can synthesize real-time market data, customer behaviors and economic signals to forecast future liquidity needs more accurately.

“Treasurers are expecting tools to improve cash forecasting,” Wiley said. “Now, instead of using traditional historical-based models, treasury departments are expecting generative AI to project cash flows. And that’s already the new normal.”

Yet not every organization is ready to use artificial intelligence. A wide technological maturity gap separates early adopters from legacy holdouts.

“We still encounter organizations who are living in pre-digital, really operational eras. They have inadequate technology, manual processes, limited data visibility,” Wiley said. “Those with inadequate cash forecasts are paying more for capital. They’re not able to really invest with precision, and they’re leaving money on the table.”

On the other end of the spectrum are finance departments that have already embraced cloud-based infrastructure, advanced analytics, and automation. These organizations are not only ready for AI but are demanding it.

ROI Recalibrated for the AI Era

One of the most persistent questions CFOs ask when evaluating new technologies is: how do we measure ROI? For his part, Wiley believes AI is not an exception to traditional SaaS metrics, but that it does expand the frame.

“On the receivables side, you have elements like DSO [days sales outstanding], which AI can improve. On the treasury side, it’s about liquidity optimization — improving investment performance, managing FX and interest rate risk,” he said, also calling attention to more overlooked areas that AI can affect, such as bank fee analysis, payment security and payment efficiency — all of which add up quickly in large enterprises processing hundreds of thousands of transactions per month.

What’s next for AI in finance?

“CFOs are wanting centralized reporting and decision-making, and AI is going to facilitate that,” he said. “Historically, CFOs have observed things like liquidity, payments, receivables in isolation, but now you’ll see AI-based dashboards that look at the relationship between these areas — automatically.”

Ultimately, Wiley envisions a unified command center powered by AI that bridges previously siloed functions, adding that this evolution from functional to integrated financial intelligence promises to transform not just efficiency, but strategic decision-making.

Putting aside the exceptional volatility we’ve witnessed on Wall Street since the beginning of April, the can’t-miss trend over the last two and a half years has unquestionably been the evolution of artificial intelligence (AI).

In its simplest form, AI empowers software and systems with the ability to reason and act on their own. This capacity to make split-second decisions without human oversight, as well as evolve to (potentially) learn new skills or jobs, gives this technology a truly jaw-dropping addressable market. In Sizing the Prize, PwC pegged this market potential at $15.7 trillion, globally, by the turn of the decade.

When most investors think of the AI revolution, Nvidia (NVDA 2.95%) is probably the first company that comes to mind. In less than two years, Nvidia went from being a fringe leader in the tech industry, with a $360 billion market cap, to the greatest thing since sliced bread, with a valuation that easily topped $3 trillion. Nvidia’s Hopper (H100) graphics processing units (GPUs) and successor Blackwell GPU architecture rapidly became the preferred hardware in Al-accelerated data centers.

But Nvidia has been usurped as Wall Street’s AI darling by data-mining specialist Palantir Technologies (PLTR 1.44%). Heading into this week, Palantir was worth $293 billion, and its shares had risen by roughly 1,840% since the start of 2023. It went from being one of many high-growth tech stocks to a foundational piece of the AI revolution.

Yet following the release of Palantir’s much-anticipated first-quarter operating results, there’s a new label that can be added: Wall Street’s biggest bubble stock.

Palantir’s moat and growth rate continue to dazzle Wall Street

Though I’ll explain how it’s a bubble stock in detail in a moment, let’s take a closer look at how Palantir has dazzled Wall Street and added $278 billion in market value in 29 months.

The biggest catalyst for Palantir is that its AI-driven software-as-a-service (SaaS) solutions can’t be duplicated at scale. While the company’s Gotham and Foundry platforms may contend with small-scale competition, there simply isn’t a one-for-one replacement for the services they provide. Nothing on Wall Street is more valued by investors than a sustainable moat — and Palantir certainly offers one.

Gotham continues to be the crown jewel. This is the segment that lands multiyear contracts with the U.S. federal government and its allies. Gotham handles data collection and analysis, as well as plays a critical role in military mission planning and execution. America’s robust defense spending has led to pretty consistent growth. In the March-ended quarter, U.S. government revenue soared by 45% from the prior-year period.

Foundry hasn’t been a slouch, either. This relatively newer platform leans on AI and machine learning to help businesses make sense of their data and streamline their operations. U.S. commercial revenue surged a whopping 71% during the first quarter, which is an indication that Palantir is just scratching the surface with this segment, as well as earning subscriptions from larger companies.

Another reason Palantir has excelled is its push to recurring profitability, which occurred well before anyone on Wall Street had expected. Profits help to validate Palantir’s dual-platform approach, and its sustained double-digit sales growth rate has clearly excited the investing community.

Lastly, Palantir closed out March with $5.43 billion in cash, cash equivalents, and marketable securities, which represents about a $200 million boost from where it ended 2024. Having a lot of cash and no debt means CEO Alex Karp and his team can aggressively reinvest in its AI-powered platforms, as well as undertake shareholder-friendly actions at times, such as share buybacks.

Image source: Getty Images.

Palantir’s operating results confirm it’s, arguably, Wall Street’s biggest bubble stock

Considering the uncertainty surrounding President Donald Trump’s tariff policy, as well as the possibility of the U.S. federal government reducing defense spending, investors were particularly interested in Palantir’s forward-looking sales and adjusted free cash flow (FCF) guidance for the recently completed quarter.

In early February, Palantir guided for $3.741 billion to $3.757 billion in full-year sales, with $1.5 billion to $1.7 billion in full-year adjusted FCF. On Monday, May 5, it upped its 2025 sales guide to $3.89 billion to $3.902 billion — an increase of $147 million at the midpoint — as well as lifted the high and low end of its adjusted FCF by $100 million to $1.6 billion to $1.8 billion.

While Palantir increasing the midpoint of its sales guidance by 3.92% might sound impressive, it comes on the heels of its stock tipping the scales at north of 100 times trailing-12-month sales entering this week.

Based on the midpoint of the company’s now-dated 2025 sales guidance ($3.749 billion), Palantir would have been valued at a price-to-sales (P/S) ratio of roughly 78 come February 2026 (i.e., when it reports its fourth-quarter operating results). Updating for the new guidance, which calls for a midpoint of $3.896 billion in full-year revenue, lowers its projected year-end P/S ratio to (drum roll) 75.2! It hardly makes a dent.

To put into context just how unbelievably expensive Palantir stock is relative to sales, take a closer look at how other market-leading businesses performed prior to bubble-bursting events.

MSFT PS Ratio data by YCharts.

Before the dot-com bubble burst, Microsoft, Amazon, and Cisco Systems all peaked at respective P/S ratios ranging from roughly 31 to 43. I added Nvidia to this chart, as well, which topped out at a P/S ratio of just over 42 last summer. Though there are other public companies with P/S ratios north of 100, what we don’t see is market-leading megacap businesses valued at P/S ratios north of 40 for any extended period — let alone a P/S ratio that’s camped out at more than 100!

To add fuel to the fire, every next-big-thing innovation for more than 30 years has navigated its way through a bubble-bursting event early in its expansion. Investors have persistently overestimated how quickly a new technology will be utilized and adopted, which eventually leads to outsized expectations not being met.

While a company like Nvidia would almost immediately feel the pain associated with an AI bubble-bursting event, Palantir Technologies would be partially insulated by its multiyear government contracts and Foundry subscription revenue. But “partially insulated” doesn’t mean immune. Palantir’s unjustifiable valuation premium would almost certainly come under fire if the AI bubble bursts, which history suggests will eventually happen.

Rarely are stock-specific bubbles this easy to recognize. Though I do believe Palantir is worthy of some level of premium due to its sustainable moat and recurring revenue, no market leader has been able to sustain a P/S ratio of 30, let alone 75 or 100. Palantir is, in my view, Wall Street’s biggest bubble stock.