Die Zukunft des SaaS: How the Stack Fallacy Influences GenAI Ambitions – The Disruption Dilemma (Part 1)

The Stack Fallacy, originally popularized by my friend Anshu Sharma, reveals a critical flaw in business strategy: companies often overestimate their ability to climb “up” the technology or business stack to create successful products at higher layers, hindered by a lack of deep customer empathy. As Generative AI (GenAI) transforms the Software-as-a-Service (SaaS) landscape, this fallacy provides a powerful lens to understand why some firms—particularly those rooted in lower stack layers like cloud infrastructure or foundational AI models—struggle to compete in customer-facing SaaS markets, while others thrive by mastering domain-specific needs. In this first of a two-part series, we dissect the mechanics of the Stack Fallacy, explore how GenAI threatens to disrupt the SaaS industry, and highlight the risks it poses to incumbents. Stay tuned for Part 2, where we’ll uncover how enterprise giants like Salesforce, ServiceNow, SAP, Microsoft, Oracle, Workday, Pega, Adobe, and Blue Yonder navigate these challenges to lead in the GenAI era.

The Stack Fallacy: A Strategic Pitfall

The Stack Fallacy describes the mistaken belief that expertise in one layer of the technology or business stack—like infrastructure or databases—translates seamlessly to success in higher layers, such as customer-facing applications. The “stack” is a hierarchy of components, from raw infrastructure (e.g., cloud computing) to platforms (e.g., APIs) to applications (e.g., CRM or ERP software). For example, a database company may excel in managing data storage but struggle to build enterprise applications like CRM because its engineers lack direct insight into the workflows of sales teams or supply chain managers. Conversely, moving “down” the stack—say, a software company building its own servers to support its platform—is often easier since firms understand their own lower-layer needs.

This concept aligns with Clayton Christensen’s The Innovator’s Dilemma (1997), which argues that incumbents miss disruptive innovations by focusing on existing customers and high-margin products. The Stack Fallacy adds a structural dimension: success at one stack layer doesn’t guarantee success at another, especially without deep customer understanding. A 2023 McKinsey study on digital transformation found that 70% of failures stem from misaligned customer understanding, underscoring the Stack Fallacy’s relevance in today’s tech landscape. In the GenAI era, the Stack Fallacy is more critical than ever. Companies at lower layers, like cloud providers or AI model developers, may assume their technical expertise equips them to conquer SaaS markets. As we’ll explore, this assumption often leads to strategic missteps.

The GenAI Stack: A New Competitive Landscape

The GenAI era redefines the technology stack, creating distinct layers that amplify the Stack Fallacy’s risks:

Lower Layers: Cloud infrastructure (e.g., AWS, Azure, Google Cloud), foundational AI models (e.g., GPT-4, Llama), and data platforms provide the raw computing power and AI capabilities for GenAI applications.

Middle Layers: AI platforms and APIs, such as xAI’s API or Hugging Face, enable developers to integrate GenAI into applicatio>

Higher Layers: Customer-facing SaaS applications—think CRM, IT service management, ERP, HR, marketing, or supply chain tools—deliver specific business value by embedding GenAI.

The Stack Fallacy suggests that lower-layer players, like those developing foundational AI models, may struggle to build SaaS applications that resonate with enterprise users. For instance, a general-purpose conversational AI model excels in broad tasks but lacks the tailored workflows needed for HR analytics or supply chain optimization without significant customization. This gap in customer empathy at higher layers is where the Stack Fallacy creates vulnerabilities.

GenAI’s Disruptive Threat to SaaS

Disruption from Below the Stack

GenAI empowers startups to challenge established SaaS players by leveraging foundational models to create niche applications. This mirrors Christensen’s disruptive innovation model, where new entrants target underserved markets with simpler, cheaper solutions that improve over time (The Innovator’s Dilemma, 1997). For example, a startup using xAI’s API (https://x.ai/api) could build a low-cost, GenAI-powered customer support tool to rival ServiceNow, targeting small businesses or “non-consumers” priced out of traditional SaaS. Gartner’s 2024 Critical Capabilities for IT Service Management Tools highlights that such tools are gaining traction by offering streamlined, AI-driven alternatives. However, lower-layer players like those providing foundational models or cloud platforms face Stack Fallacy risks. A cloud provider’s AI platform may offer powerful models but struggle to deliver the industry-specific workflows that ServiceNow’s IT service management tools provide, as it lacks direct customer insight at the application layer.

Commoditization of SaaS Features

GenAI can replicate features that once differentiated SaaS platforms, such as predictive analytics, content generation, or data visualization. A marketing SaaS platform’s unique analytics dashboard, for instance, could be mimicked by a GenAI model generating real-time insights from raw data, eroding its competitive edge.The Stack Fallacy exacerbates this threat. SaaS incumbents relying on proprietary algorithms risk disruption if they don’t integrate GenAI to maintain differentiation. Meanwhile, lower-layer providers attempting to move up the stack may offer generic AI features that fail to address specific needs, such as compliance in healthcare or logistics in supply chain management.

Shifting Customer Expectations

GenAI’s ability to deliver hyper-personalized, conversational, and automated experiences is raising the bar for SaaS providers. Users now expect natural language interfaces, real-time insights, and seamless automation. Deloitte’s 2025 AI in Enterprise Software Trends study found that 80% of enterprise buyers prioritize AI-driven personalization in SaaS solutions. A CRM platform without a GenAI-powered chatbot, for example, may lose customers to a startup offering conversational sales assistants.The Stack Fallacy trips up lower-layer players here. A cloud provider’s AI platform may offer robust GenAI capabilities but struggle to create SaaS applications that meet industry-specific needs, such as GDPR compliance for European ERP users, due to limited customer empathy at the application layer.

The High Stakes of GenAI and the Stack Fallacy

The Stack Fallacy’s relevance in the GenAI era stems from the technology’s transformative potential. Lower-layer providers, armed with powerful AI models and cloud infrastructure, may be tempted to enter SaaS markets, assuming technical expertise is enough. Yet, success at higher layers requires deep customer understanding, not just technical prowess, as Christensen’s work suggests. The SaaS industry’s massive growth potential makes it a prime target for GenAI-driven disruption. Startups can rapidly prototype solutions, while customers demand AI-enhanced experiences, creating a perfect storm for incumbents who fail to adapt.

But as we’ll explore in Part 2, enterprise giants are not standing still. Companies like Salesforce, ServiceNow, SAP, Microsoft, Oracle, Workday, Pega, Adobe, and Blue Yonder are leveraging their customer-centric strengths to integrate GenAI and maintain dominance. Part 2 will reveal how these titans avoid the Stack Fallacy, balancing customer empathy with technological innovation to shape the future of SaaS.The Stack Fallacy exposes why lower-layer players struggle to conquer SaaS markets, but how do industry leaders like Salesforce, Microsoft, and SAP sidestep this trap to thrive in the GenAI age? In Part 2, we’ll dive into their strategies—from AI-powered platforms to ecosystem-driven innovation—and explore how they shape Die Zukunft des SaaS. Join us to uncover the art of surviving and thriving in a GenAI-driven world.

Labels: Enterprise Software, GenAI, SaaS, Stack Fallacy