March 12 - Top software executives are rebutting the idea that AI-powered automation will end the need for established software companies. Oracle executive Mike Sicilia addressed analysts on Tuesday, rejecting the notion that fast-moving startups using AI to write code will bring about the "death of SaaS (software as a service)."
"You’ve all heard ... that new companies coding quickly using AI will spell the death of SaaS (software as a service)," Sicilia told analysts. He added plainly: "I don’t agree with that at all. I do think that AI tools and their coding capabilities would be a threat if we weren’t adopting them, but we are, and very rapidly."
Sicilia’s remarks came amid growing unease on Wall Street that AI tools can now handle tasks many traditional software products were designed to do - organizing customer records, guiding users through business workflows and even automating portions of application development. Those concerns contributed to a market shock last month when software stocks collectively slid, with losses approaching nearly $1 trillion after the AI startup Anthropic released AI plugins for its Claude Cowork agent, a digital assistant positioned to automate such processes.
In response, executives from established software firms have used their post-earnings calls as platforms to counter the narrative. Sicilia emphasized Oracle’s strategy of building AI into new products and automating complete business processes, rather than merely bolting AI features onto existing offerings. He framed that approach as a key distinction between Oracle and some smaller rivals.
Salesforce, for its part, has made its own case. CEO Marc Benioff told analysts last month that Salesforce will survive any so-called "SaaS-pocalypse" - a phrase used to describe last month’s sharp selloff in software-as-a-service equities. Benioff brought customers into the discussion to present Salesforce as an enterprise platform that not only creates but also deploys and governs AI agents, leveraging the company’s large stores of proprietary customer and sales-process data.
Even Jensen Huang, CEO of chipmaker Nvidia and a prominent figure in AI technology, dismissed concerns that AI will supplant software and related tools, calling the premise "illogical."
Data as a defensive asset
Analysts and company spokespeople say one of the strongest defenses against AI-driven disruption is exclusive access to long‑standing, proprietary enterprise data. Oracle said on Tuesday that it expects the AI wave to fuel revenue growth for several upcoming quarters, a forecast that helped lift its shares by 10% on Wednesday. The company’s holdings of enterprise data spanning finance, supply chain and human resources are difficult for external AI models to replicate, supporters contend.
Rebecca Wettemann, CEO of technology research firm Valoir, highlighted Oracle’s flexibility in cloud deployment and database portability. She said that ability to run on any major cloud and offer cost-effective systems provides customers choice - a valuable position as the AI ecosystem develops.
Several analysts surveyed by market observers echoed that view, suggesting that owners of long-running, exclusive datasets in areas such as finance, legal, design or technical operations enjoy meaningful protection. "Proprietary data is the deepest moat by far," said James St. Aubin, chief investment officer at Ocean Park Asset Management.
Salesforce’s data position is frequently cited as an example. While startups are chipping away at parts of the customer-relationship management market, Salesforce remains deeply embedded in many corporations. Its real-time data platform is reported to manage more than 50 trillion records, and the company is pushing to reframe itself as an AI-agent builder with its Agentforce service - though that offering remains a relatively small business today.
Madhav Thattai, executive vice president of Salesforce AI, said the company’s end-to-end system differentiates it from simple point solutions and that Salesforce benefits from decades of enterprise experience. Those factors, he argued, help the company stand out while businesses test isolated AI tools.
Oracle did not return emails seeking comment for this story.
Limits to the protection conferred by data
Despite the emphasis on proprietary datasets, analysts warn that not all data creates equal barriers to competition. Workday, a provider of employee data and payroll systems, holds substantial data but much of it adheres to standardized, industry-wide formats. That standardization can make it easier for AI developers to learn from and replicate solutions built on such datasets.
Workday recently reinstated its founder, Aneel Bhusri, as CEO to guide the company through "the rapidly evolving AI era." Still, the company’s shares have dropped by more than a third this year, and last month they hit what was described as a more-than-five-year low following a weak sales forecast.
On a post-earnings call, Bhusri argued that Workday’s systems encapsulate two decades of business processes that AI cannot duplicate. He cautioned about AI’s current technical limits: "AI, for all of its incredible capabilities, is probabilistic by nature," he told analysts. "It reasons, predicts and recommends based on patterns and likelihoods. Maybe it will eventually become a state machine - a system that follows the same steps and gets the same result, every time - but it is not there today." When asked for comment for this article, a Workday spokesperson referred to Bhusri’s remarks during the earnings discussion.
Outlook: resilience and reinvention
Some market watchers say current valuations may understate the enterprise software sector’s resilience. They suggest that if AI raises productivity, companies could respond by expanding hiring and pursuing growth, providing an avenue for established software vendors to reinvent themselves around AI capabilities rather than being displaced by them.
"I would not write the obituary for some of these companies just yet because there is an opportunity for them to reinvent themselves with AI," said Ocean Park’s Aubin, reflecting a view among several analysts that incumbents can adapt by integrating AI into products and services.
For now, the debate continues. Executives highlight rapid AI adoption and exclusive datasets to argue that software companies remain relevant; critics point to standardization in some data domains and the lowering of technical barriers as reasons for caution. Investors and customers will be watching closely to see whether established vendors can convert their data and platform positions into sustainable AI-driven growth.