Analyst warns of AI bubble and backs these 5 SaaS stocks as alternatives

Benchmark's Bill Gurley says AI infrastructure spending may be in bubble territory and recommends SaaS stocks instead. Five major SaaS companies are down 25-35% this year despite steady revenue growth and expanding AI tools.

Categorized in: AI News Finance
Published on: Mar 22, 2026
Analyst warns of AI bubble and backs these 5 SaaS stocks as alternatives

Wall Street Analyst Warns of AI Bubble, Recommends Shift to SaaS Stocks

Benchmark general partner Bill Gurley warned investors this month that artificial intelligence infrastructure spending may be approaching bubble territory. In a CNBC interview, he recommended moving money into software-as-a-service stocks that have fallen sharply in recent months. NYU Professor Scott Galloway made a similar case, saying fears about SaaS valuations are overblown.

The recommendation comes as five major SaaS companies trade down 25% to 35% year to date, despite maintaining revenue growth and expanding into AI-powered tools. Here's what each company does and where valuations stand.

ServiceNow

ServiceNow handles workflow management for IT, human resources, and customer service across large organizations. Its software becomes embedded in customer operations, making it difficult to replace. The company grew revenue more than 20% last quarter and is developing Tower, a new product designed to orchestrate AI agents.

The stock trades at 7.5 times forward sales and 28 times forward earnings. It's down nearly 25% year to date.

Salesforce

Salesforce leads in customer relationship management software and has expanded into data integration. Its Data 360 product pulls information from cloud providers and data warehouses. The company's acquisition of Informatica added the ability to connect legacy systems, positioning Salesforce as a central data hub for AI agents to work from.

The company expects revenue to grow above 10% annually through 2030. The stock trades at less than 4 times forward sales and below 15 times forward earnings, down more than 25% year to date.

Workday

Workday dominates human resources and finance data software. It recently introduced 12 role-based AI agents and saw annual contract value for AI solutions double to $100 million last quarter. Revenue is expected to grow in the mid-teens this year.

The stock trades at below 3.5 times forward sales and below 13 times forward earnings-the lowest valuation of the group. It's down more than 35% year to date.

UiPath

UiPath builds robotic process automation software and has developed an AI orchestration platform called Maestro. The system can assign work to either traditional software bots or AI agents depending on which is more cost-effective. The company saw annual recurring revenue growth accelerate last quarter for the first time in several years.

The stock trades at just above 3.5 times forward sales and 15 times forward earnings, down more than 25% year to date.

Adobe

Adobe remains the standard software for creative professionals and has maintained low double-digit revenue growth. Its AI annual recurring revenue more than tripled last quarter, driven by increased use of generative credits. The company shows no signs of disruption from AI competitors.

The stock trades at 4 times forward sales and below 11 times forward earnings, down more than 25% year to date.

What This Means for Finance Teams

These valuations reflect investor skepticism about SaaS growth prospects. If Gurley's thesis holds-that AI infrastructure spending is overheated while enterprise software remains undervalued-these stocks may offer returns for investors with a longer time horizon. Finance professionals evaluating technology investments should consider whether their organizations are already locked into these platforms, which could affect vendor strategy and cost negotiations.

For those managing portfolios or evaluating AI spending across their organizations, understanding the difference between infrastructure plays and software platforms matters. AI for Finance Courses and AI Learning Path for CFOs can help finance leaders make these distinctions clearer.


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