AI’s Double-Edged Sword: How Goldman Sachs Sees the Future of Software
The rapid ascent of artificial intelligence is forcing a reassessment of the software sector. Recent investor concerns about the impact of AI agents on traditional platforms have triggered a significant sell-off in tech stocks. However, according to analysts at Goldman Sachs, innovation doesn’t necessarily represent a widespread threat; instead, it could bolster certain companies, provided they are evaluated with a more selective approach.
The Sell-Off and Shifting Sentiment
The recent correction in software stocks reflects a swift change in investor sentiment, rather than a deterioration of fundamentals. The primary fear is that if AI agents become the primary interface for workers, traditional platforms risk becoming mere data repositories, losing pricing power and strategic importance.
Previously, sector valuations incorporated expectations of revenue growth of 15% to 20% over the medium term (by 2028). Following the recent reevaluation, multiples now imply a more modest estimated growth range of 5% to 10%. This repricing has increased volatility but could also create opportunities for companies with solid models and strong structural positioning.
AI: Threat or Accelerator?
According to the Goldman Sachs Research team led by Matthew Martino, there are “credible paths” through which AI can strengthen the long-term growth of software, rather than weaken it. The key, analysts explain, is to distinguish between companies vulnerable to disintermediation by agents and those that integrate AI into their products, improving efficiency, automation, and added value.
Investors are closely watching new agent orchestration platforms, which coordinate multiple AI systems in complex workflows. These developments have contributed to the strong reevaluation of some sector stocks but have also fueled fears of a radical transformation of the value chain.
The “AI Impact Framework”
To help assess the effect of innovation on individual companies, Goldman Sachs Research has developed an “AI impact framework” based on six key criteria:
- Orchestration Risk – the probability that AI agent layers can bypass the platform and become the primary value generator.
- Monetization Model – user-based models (more vulnerable) versus those based on data or proprietary assets (more resilient).
- System of Record Ownership – if the platform manages approvals, compliance, and execution, it is more difficult to replace.
- Data Moat & Integration – the presence of workflows dependent on structured data and proprietary signals integrated into the system.
- AI Execution – real and already implemented capabilities, not just theoretical roadmaps.
- Budget Alignment – whether AI adoption increases or reduces the strategic priority of the product.
Where AI Can Strengthen Software
For some lightweight applications monetized through per-user licenses, agent orchestration may alter how value is captured over time. However, at the platform and infrastructure level, the dynamics are different: agents tend to increase the need for data management, security, workload orchestration, and system resilience.
These functions, located below the user interface, are more difficult to bypass and could directly benefit from the expansion of AI. In other words, while some categories may face pressure, others may see increased demand and greater strategic relevance.
The Core Question for Investors
“The fundamental question isn’t whether agents will change software — they will,” observes Martino. Rather, it’s essential to analyze the entire technology stack to identify where AI will be a disintermediating element and where it will act as a catalyst for growth.
companies that own proprietary data, deep integration systems in business processes, and concrete AI implementation capabilities may be among the primary beneficiaries of the ongoing transformation.
AI, is not necessarily a uniformly negative factor for the software sector: for some operators, it may represent a competitive threat, while for others, it may be a structural opportunity for strengthening. The difference, according to analysts, will depend on the position along the value chain and the solidity of the business model.
Frequently Asked Questions
- Will AI completely replace traditional software platforms?
- What are the key factors to consider when evaluating software companies in the age of AI?
- Which areas of the software sector are most likely to benefit from AI?
Not necessarily. Goldman Sachs suggests AI will likely reshape the software landscape, benefiting companies that integrate it effectively rather than those solely reliant on traditional models.
The “AI impact framework” highlights orchestration risk, monetization models, data ownership, AI execution, and budget alignment as crucial factors.
Platform and infrastructure layers that support data management, security, and system resilience are expected to see increased demand.
Pro Tip: Investors should focus on companies with strong data moats and proven AI implementation capabilities for long-term success.
Did you know? Global stocks are projected to return 11% in the next 12 months, according to Goldman Sachs, with the US GDP expected to outperform forecasts in 2026.
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