AWS CEO Matt Garman has pushed back against fears of AI undermining traditional software companies, describing market fears as “overblown.”
This rebuttal comes as the broader market wrestles with a narrative suggesting that generative AI will displace the traditional Software-as-a-Service (SaaS) model. Garman addressed the AI-driven sell-off in software stocks as analysts increasingly refer to the downturn as a potential “SaaS apocalypse.”
The anxiety in the market is visible in recent performance metrics. The iShares Expanded Tech-Software Sector ETF has fallen 24 percent year-to-date in 2026, putting it on track for its worst annual performance since 2022. This follows the rollout of AI-powered tools from companies including OpenAI and Anthropic, which have fuelled concerns that traditional software providers could see slowing growth.
Despite volatility across the software sector, AWS reported stronger-than-expected fourth-quarter results. Revenue from its cloud infrastructure division increased 24 percent year over year to $35.6 billion, while operating margins reached 35 percent, slightly improving on the previous quarter. The performance suggests continued enterprise demand for cloud infrastructure even as investors reassess software valuations.
Integration over replacement
The technical argument against the displacement theory rests on data gravity and workflow complexity. Large enterprises rely on established systems of record to manage governance, compliance, and structured data.
Jason Kurtz, CEO of Basware, commented: “The idea that AI will replace software is simply not accurate. Some even say AI will ‘eat software,’ but AI can’t replace something that isn’t dying. Instead, AI has to be embedded within software. AI depends on workflow, user experience, clean data, and context, all of which live inside enterprise software systems.”
This perspective aligns with the challenges platform engineers face when deploying LLMs in production. Standalone models lack the contextual grounding required for complex enterprise tasks. To function effectively, these models require integration into the existing “plumbing” of business operations—the very SaaS platforms investors are currently doubting.
Garman reinforced this view, suggesting that incumbents possess a structural advantage.
“There’s a huge disruption,” Garman said. “AI is absolutely a disruptive force that’s going to change how software is consumed and how it’s built. And I would argue that the systems of record, as you call them, the SaaS providers and the large players of today have an inside track to winning that business.”
However, the AWS executive noted that incumbency does not guarantee safety without adaptation. “Now, they have to innovate, just like the rest of the world. They can’t stand still. If they stand still, they’re absolutely going to be disrupted.”
The rise of agentic AI workflows in software development
For developers, the focus is narrowing on agentic AI systems that are capable of executing multi-step workflows rather than simply retrieving information. This evolution requires tight coupling between the AI model and the application layer.
Basware’s latest research highlights that ROI on AI investments in finance has nearly doubled in the past year, from 35 percent to 67 percent, and for agentic AI, it’s even higher, at 80 percent.
Kurtz noted that when AI agents are embedded inside operational software, they don’t just predict outcomes, they execute work securely, at scale. “That’s where measurable ROI happens,” he said.
This distinction between predictive generation and executive action is central to the architectural decisions facing engineering teams today. High ROI implementations appear to be those that leverage existing APIs and security frameworks within established software, rather than those attempting to bypass them.
Infrastructure demand persists
AWS’ strategy appears to cover both sides of this potential market split. The cloud provider continues to generate revenue from major enterprise software companies including Adobe, Intuit, and Zillow, while also expanding its footprint with AI model developers.
This dual approach mitigates risk for the infrastructure provider. If SaaS companies retain their dominance by embedding AI, AWS profits from their compute usage. If new AI-native entities capture market share, they are likely building on AWS infrastructure regardless.
In November, AWS announced a $38 billion cloud spending commitment from OpenAI, underlining its growing role in supporting AI infrastructure.
While AI is reshaping the broader software ecosystem, AWS’ leadership remains confident in long-term growth, maintaining that customers will continue to increase their consumption of compute and infrastructure, whether through SaaS vendors, in-house development, or AI-powered platforms.
For engineering leads, the takeaway is that the fundamental requirements for secure and scalable systems remain unchanged. The most effective path forward involves evaluating how current toolchains can host agentic workflows, rather than anticipating the obsolescence of the toolchains themselves.
See also: Developers adopt high-performance Java to support production AI
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