HSBC's "Contrarian View": Software Will Devour AI; Now Is a Good Time to Buy the Dip

Can AI coding disrupt SaaS? HSBC's answer is quite the opposite.

According to Wind Chasing Trading Desk, on February 24th, Stephen Bersey, Head of U.S. Technology Research at HSBC, and his team released a report titled "Software Will Eat AI Stocks," putting forth a contrarian perspective.

In an era of "AI disruption and panic trading," HSBC explicitly pointed out that not only will software not fade away, it is actually the key pathway for the world’s largest enterprises to "leverage AI in a controlled way."

HSBC summarized its judgment with a highly contrasting statement: "Hardware/semiconductors are already strong, but software will be better." Their logic is: what enterprises really need is not a "talking model," but controllable, auditable, and repeatable operational capabilities, which are the strengths of software platforms.

Enterprise software will not be threatened by AI; on the contrary, AI will be embedded into software platforms.Enterprise software vendors have already completed heavy tasks such as design, intuitive programming, and embedded agent testing.The valuation level of the software sector is at historic lows, despite the industry gearing up for a massive expansion.

The "Innate Deficiencies" of Large Models and Enterprise-Level Barriers

The biggest current concern in the market is that AI’s own code writing (Vibe-coding) will significantly lower the threshold for software development, allowing startups to easily disrupt existing SaaS giants.

HSBC firmly refuted this. The report pointed out, from a technical perspective, foundational AI models have “innate deficiencies.” AI is fundamentally non-deterministic, and may give different answers or even make mistakes when faced with the same problem.

This is fatal for enterprise applications. "The world is used to software platforms that are repeatable, auditable, and error-free in daily operations, whereas foundational models lack these qualities." HSBC emphasized that, for high-fidelity enterprise platforms, relying on AI for "wholesale migration and replacement" is unrealistic.

Moreover, enterprise-grade software has reached extremely high throughput and reliability after decades of evolution. Behind this lies vast amounts of critical, private intellectual property (IP), data that cannot be publicly trained by AI on the open internet. HSBC frankly said: "If you don’t know what code you’re writing, vibe-coding is almost useless."

It's like a pharmaceutical company wouldn’t design chips or refine steel just for its own use. Enterprises abandoned writing their own core IT systems decades ago because it defies basic economic principles.

These companies quickly realized that internally developing and maintaining these systems, and staffing them, is very costly; spending huge sums to write massive platforms but only spreading costs across a single use case (i.e., for themselves) is extremely uneconomical. Instead, buying products from software vendors with expertise in development, maintenance, and staffing is much more economical, as these costs are spread across thousands of customers.

Who Will Write the Best AI Software? Traditional Software Giants

Since startups and large model suppliers lack experience in building "enterprise-grade" complex architectures, who is best suited to use AI to generate better software?

HSBC gave a highly definitive answer: "Of course, the software vendors themselves."

The logic is clear: established software giants like Salesforce, Oracle, ServiceNow, and Microsoft have deep domain expertise, strong sales channels, and customer trust. More importantly, they've been using the same AI coding tools to embed refined agents in their broader platforms.

AI's role is "down-leveled" and "domesticated." HSBC drew a vivid analogy: AI creatively analyzes and produces intelligent data, but this data must be handled, stored, checked, and executed by deterministic software stacks.

"The vast majority of enterprise software won’t be threatened by AI; on the contrary, AI will be domesticated in application technology stacks through agents and create significant value in the process."

2026: The First Year of Software Monetization, Valuations at Historic Lows

From an investor’s perspective, technical logic must ultimately translate into performance guidance and market space.

HSBC provided a clear timeline: major software giants began the heavy work of designing and beta testing embedded AI agents in 2024, with the technology now mature and starting to be rolled out globally to large customers.

"We believe 2026 will be the kick-off for software monetization," HSBC said, noting this will be the major mechanism through which the world’s largest enterprises consume AI, driving exponential growth in AI inference demand.

For market investment rhythm, HSBC delivered a firm conclusion: "As good as hardware and semiconductor industries have performed, software will be better."

HSBC believes AI is a technology, but "enterprises rarely buy technology; they buy solutions to business problems," and these solutions can only come from infinitely flexible software technology stacks. In this ecosystem, which produces over $100 trillion in global GDP, traditional software giants are the core beneficiaries of AI’s value potential.

Currently, the total addressable market (TAM) for the software industry is on the eve of a massive expansion cycle of 5-10 years. However, cognitive misalignment in the market has led to the software sector’s valuation being at historic lows. HSBC suggests that before valuation re-rating, now is the right time to build or expand positions in the software sector.

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The above exciting content was sourced from Wind Chasing Trading Desk.

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