There is a growing debate in Silicon Valley, which last month cost the software sector almost a trillion dollars in market valuation. The question is fundamental: will generative artificial intelligence, capable of writing code and automating processes on its own, make traditional SaaS platforms redundant? Industry leaders, from Oracle to Salesforce, have moved to counterattack, arguing that their greatest asset is not the code itself, but the unique data on which they operate.
Oracle’s Mike Sicilia and Salesforce’s Marc Benioff reject the vision of a ‘software apocalypse’ with one voice. In recent meetings with analysts, both stressed that AI is not an existential threat, but a turbocharger for existing systems. Oracle, whose shares rose 10% after optimistic forecasts, is betting on flexibility and deep embedding in financial and logistical processes. According to analysts, it is the possession of ‘proprietary data’ that provides the most effective moat against new players such as Anthropic.
Despite the confidence of the giants, the market remains sceptical of companies whose data is easier to replace. An example is Workday, whose share price has been hit hard. Although the company manages a huge amount of HR information, critics note that HR data is often subject to rigid, standardised formats. This makes them more susceptible to replication by agile AI models.
However, Aneel Bhusri, returning CEO of Workday, raises a compelling technical argument: today’s artificial intelligence is probabilistic – based on probabilities and patterns. Meanwhile, critical corporate systems need to be deterministic; they need to deliver the same precise result every time, especially in the area of payroll or accounting.
Instead of obituaries, market observers suggest evolution. Salesforce is promoting its Agentforce platform, and Oracle is integrating AI into its entire technology stack, from database to end-user applications. The advantage of the traditional players comes from switching costs – companies have spent decades building operations around these tools. While AI lowers the barrier to creating new software, it will not so easily replace decades of experience in managing complex business processes.
