Goldman Sachs' latest "Top of Mind" report signals a significant inflection point for the software industry as agentic artificial intelligence - systems that can autonomously write and modify software - intensifies pressure on longstanding business models. The report highlights investor concerns that AI could "eat" the software sector that spawned much of the modern digital economy, prompting a steep re-pricing of many software stocks.
That stark assessment has prompted a range of reactions from market participants. While the possibility of deep disruption is taken seriously, a prevailing view among analysts is that legacy vendors are not defenseless. Several characteristics of incumbent firms are identified as protective features - or "moats" - that can provide critical breathing room as business models evolve.
Those defensive attributes include the tight embedding of established software into corporate processes, extensive proprietary datasets useful for training models, and enduring customer relationships that underpin recurring revenue. Gabriela Borges of Goldman Sachs framed this dynamic succinctly: "Legacy software companies aren’t standing still," she said. "They are innovating as fast followers... That, combined with their moats, could ultimately leave incumbents in a better place from a soup-to-nuts platform perspective." The implication is that incumbents may be able to fold AI capabilities into existing offerings and capture value without ceding significant market share to emergent startups.
Still, observers caution that protective moats are not a guarantee of future competitiveness. Rick Sherlund of Sherlund Partners noted that "moats buy incumbents time to adapt, as seen in prior software disruption cycles," while posing the salience of a follow-up question: "how radical a transformation must they undergo to remain competitive." That question remains open and central to assessments of individual companies.
For investors, the immediate practical challenge is stabilizing equity valuations through demonstrable and repeatable earnings. Goldman Sachs strategists emphasize that "what it will take to stabilize share prices is earnings stability and a clear path to AI monetization." Market appetite, according to the report, is shifting away from broad software exposure toward businesses that can show concrete productivity improvements tied to AI integration.
On the credit side, Goldman analysts argue that while equity markets have experienced a sharp re-rating, stress emanating from software-exposed credit markets is unlikely at this juncture to catalyze a broader turn in the credit default cycle. They state that "whether stress in software-exposed credit can catalyze a turn in the credit default cycle is unlikely at this stage, despite the sharp re-rating in equity valuations."
The report's overarching message to investors is to exercise selectivity. The emergence of agentic AI is producing a bifurcated market in which companies that fail to rework their cost bases and product suites risk being marginalized. As automation compresses the cost of software development, the report contends that the locus of value may shift from raw code to the intelligence and services layered on top of platforms.
Finally, the note touches on investor tools and valuation questions raised by the market's turbulence. One example cited in the report is ongoing interest in assessing whether major platform companies represent value opportunities amid the evolving competitive landscape. The report underscores the need for clear monetization trajectories tied to AI capabilities if share-price stability is to be achieved.
Key takeaway: Agentic AI presents a material challenge to the software industry, but incumbent vendors possess structural advantages that may allow them to adapt and integrate AI into existing platforms; earnings stability and a credible path to monetizing AI are central to restoring investor confidence.