AI Talks

What Is Vertical Software?

Before examining the threats, it’s important to define the battlefield. Unlike horizontal software (e.g., Microsoft Office) that serves a wide variety of industries, vertical software provides specialized, mission-critical solutions tailored to the unique needs of a particular niche, such as software for managing dental practices, public transit systems, or construction logistics. Its value comes from being deeply embedded in the core operational workflows of its customers, creating high switching costs and a competitive moat.

From Systems of Record to Systems of Action

At the heart of this disruption is a redefinition of what software does. Historically, enterprise software has functioned as a “system of record”—a robust platform designed to store and manage critical business data. In this model, value is rooted in data centralization and workflow enforcement, with the human user as the primary active agent.

The advent of agentic AI inverts this relationship, transforming software into a “system of action.” An agentic system accepts high-level objectives and then autonomously perceives its environment, reasons, formulates multi-step plans, and executes them across other systems. In this new paradigm, the software is no longer a passive tool but a proactive digital worker capable of taking initiative to achieve business outcomes. This qualitative leap in automation sets a new benchmark for utility and performance.

Lower Barriers to Entry

This technological shift has dramatically lowered the barriers to entry for new players. The combination of powerful, widely available AI models and scalable cloud infrastructure allows even small startups to develop and deploy sophisticated enterprise software with unprecedented capital efficiency.

These new entrants are not just creating better “systems of record”; they are building “systems of action” from the ground up. Such AI-native products can deliver a step-change in efficiency over incumbent systems, offering enough value to overcome even traditionally high switching costs. Unburdened by legacy technology and entrenched revenue models, these startups enjoy a structural advantage over established competitors.

Commoditization and Pricing Pressure

The rise of agentic AI also drives the commoditization of underlying software and the erosion of pricing power. If an intelligent agent layer can orchestrate tasks seamlessly across multiple platforms, the underlying software risks being reduced to an invisible, commoditized data store.

In this scenario, value migrates from the provider of the backend “system of record” to the provider of the intelligent “system of action” at the front end. Customers, no longer interacting directly with the traditional software, will likely resist historical price increases for what they now perceive as a utility. This dynamic undermines established revenue models and erodes the competitive moats many software companies have long relied upon.

The Data Paradox

This leads to a critical paradox. While the software interface is at risk of being commoditized, the incumbent’s underlying proprietary dataset is also its single greatest asset for defense. A generic AI model cannot compete with a specialized model trained on decades of unique, industry-specific data. The threat, therefore, is not just being commoditized, but failing to activate this data advantage. Incumbents are sitting on the fuel needed to power a superior AI engine but risk losing if a competitor builds that engine first.

Shrinking Software Lifecycles

The rapid pace of AI innovation is accelerating technological obsolescence. Software assets once expected to generate stable cash flows for decades may now become outdated within just a few years.

A business built on the assumption of long-term product durability may find itself displaced quickly as more intelligent, automated competitors capture its market. This dynamic challenges the financial underpinnings of many software valuations and “hold forever” strategies. Companies must now adapt to an environment where technological relevance can evaporate in record time.

Foundational Models as Direct Competitors

Perhaps the most disruptive force comes from foundational AI models. Advanced models, like OpenAI’s GPT-5, are not only more capable than their predecessors but also more efficient.

Critically, these models have shifted from enablers to outright competitors. They can generate functional, polished applications without human developers, ushering in an era of “BYO AI” (“bring your own AI”). For small and mid-sized businesses (SMBs), the economics are compelling: a general-purpose AI subscription can replace costly, specialized software suites. This poses the greatest risk to entry-level enterprise vendors, particularly in categories like website builders, project management, and marketing tools.

Conclusion

AI represents a clear inflection point for the software industry, especially for incumbents in vertical markets. The shift from passive “systems of record” to proactive “systems of action”—combined with the forces of commoditization, accelerated obsolescence, and direct competition from foundational models—requires a fundamental strategic pivot. Survival will depend not only on radical innovation but on the urgent need to leverage unique data assets to build a defensible AI-driven future.

References

Bordetsky, A., Luck, T., & Kaplan, J. (n.d.). Tomorrow’s Titans: Vertical AI. NEA.
Brodetskyi, A. (2025, April 16). The Next Trillion-Dollar Opportunity: Why Vertical AI is the Future of SaaS. Medium.
Clifford, S. (2025, July 15). Agentic AI vs Traditional AI: What Sets AI Agents Apart. FullStack Labs.
Google. (2023). What is agentic AI? Google Cloud Blog.
Lango, L. (2025, August 13). Why ChatGPT-5’s Stunning Launch Is Bad News for Many AI Stocks. InvestorPlace.
LEK Consulting. (2025, March 31). The Future Role of Generative AI in SaaS Pricing. LEK.
Shah, B. (2025, August 16). Can vertical SaaS transform niche industries with artificial intelligence? The Economic Times.

This post was researched and written with the assistance of various AI-based tools.