Why These Software Segments Struggle To Produce Billion-Dollar Outcomes

In today's software market—particularly during the current AI cycle—capital is flowing into an unusually broad set of categories. Many of them are being funded, scaled and valued as if they can produce billion-dollar outcomes.

But a recurring pattern suggests otherwise.

There are entire segments of the software market that, structurally, are unlikely to generate outlier outcomes regardless of execution quality. The challenge is not identifying these markets in hindsight. It is recognizing them early enough, when they still look indistinguishable from genuinely large opportunities.

This distinction is becoming increasingly relevant today. The private software ecosystem has accumulated hundreds of billions of dollars in enterprise value, while AI has dramatically expanded the perceived opportunity set across almost every software category. As capital has become more abundant, the number of companies being valued as future category leaders has grown accordingly.

Yet many of these companies ultimately encounter growth ceilings that have little to do with execution. Instead, the limitation stems from the structure of the markets they serve.

How Big Is The Problem?

The issue is not that these companies fail.

Many become successful businesses. They build valuable products, achieve strong customer retention and generate meaningful revenue. The problem is that venture capital economics require exceptional outcomes.

A company valued at $2 billion today may need to become a $10 billion or $20 billion company to generate attractive returns for investors. That assumption implicitly requires a large market, strong pricing power and a long runway for expansion.

Yet many software companies operate in markets that are fundamentally constrained.

Consider a software company that raises capital at a $2 billion valuation based on the expectation that it will eventually reach $300 million in annual recurring revenue. If the underlying market ultimately supports only $75 million to $100 million of ARR, the company may continue growing and serving customers successfully while still falling dramatically short of investor expectations.

This dynamic helps explain why software investing periodically produces large numbers of companies that are operationally successful but financially disappointing. The business works. The market simply wasn't large enough to support the outcome embedded in the valuation.

The challenge is that these limitations are often invisible during the company's early years.

When Early Signals Mislead

In the first phase of a software company's life, most categories behave similarly. Companies show strong growth, high retention and clear product-market fit. Investors understandably extrapolate from these signals.

However, early traction primarily reflects the strength of the product—not the size or quality of the underlying market.

Over the past decade, numerous companies built software around compliance, governance, reporting and internal audit workflows. Products serving these functions often scaled efficiently to tens of millions of dollars in revenue, supported by retention rates that benefited from regulatory requirements and recurring usage.

From the outside, they looked like high-quality SaaS businesses.

But over time, growth frequently slowed. Budgets were defensive, owned by non-strategic buyers and continuously scrutinized. The software was necessary, but not central to value creation. Expansion opportunities were limited, and the market ceiling became visible only after significant scale had already been achieved.

This pattern is not specific to compliance software. It reflects a broader dynamic: software sold into cost centers rarely compounds into large platforms.

The Limits Of Vertical And Fragmented Markets

A similar effect can be observed in parts of the vertical SaaS ecosystem, one of the most heavily funded software categories of the last decade.

Many vertical software companies have built exceptional businesses. Companies such as Procore in construction, ServiceTitan in home services and Toast in restaurants have demonstrated that software can achieve strong penetration and substantial value within a specific industry.

However, these examples also illustrate an important reality: even category leaders often encounter structural limits.

Many vertical markets contain a finite number of potential customers. Pricing power is constrained by the economics of the underlying industry, and expansion into adjacent verticals is often far more difficult than investors initially assume. Different industries require different workflows, integrations, compliance requirements and go-to-market motions.

As a result, what appears to be category leadership is sometimes leadership within a bounded market rather than the foundation of a massive horizontal platform.

The distinction matters because venture-scale outcomes depend not only on winning a market but also on the size of the market being won.

The Fragility of Non-Core AI Tools

The current AI cycle has amplified another category of structurally constrained opportunities: tools that improve workflows without owning them.

Examples include meeting intelligence platforms, AI note-taking tools, AI-powered analytics layers and workflow assistants that sit on top of existing systems of record.

These products often grow rapidly because they are easy to deploy and can demonstrate immediate value.

However, their position in the technology stack is inherently fragile.

Platform owners—including CRM, ERP, productivity and collaboration vendors—have strong incentives to incorporate these capabilities directly into their existing products. At the same time, the widespread availability of AI models and infrastructure has reduced the barriers to replicating functionality.

As a result, differentiation can compress quickly. Products that initially appear to represent standalone categories can ultimately become features embedded within larger platforms.

History provides many examples of this phenomenon. The challenge for investors is determining whether a product owns a workflow or merely enhances one.

When Value Creation Doesn't Translate Into Value Capture

Another recurring pattern involves companies that create meaningful operational value but struggle to capture that value economically.

This frequently occurs in productivity, collaboration and efficiency-focused software.

Organizations may derive significant benefits from these tools, but the value is often dispersed across teams and difficult to attribute to a single budget owner. As a result, pricing power remains limited even when adoption is widespread.

The company may create substantial value for customers while capturing only a small portion of that value itself.

These businesses can become successful and durable. They simply struggle to achieve the economics necessary to support the largest venture outcomes.

Valuation, TAM and The Assumptions In Between

One of the clearest indicators of this tension emerges in how software companies are valued.

In private markets, valuations are often based not on current market size but on assumptions about future market expansion. Investors may believe a company will enter adjacent categories, redefine an industry or capture an unusually large share of the value chain.

Sometimes those assumptions prove correct.

Companies such as Salesforce, Shopify and ServiceNow ultimately expanded far beyond the markets originally envisioned by investors. Their early TAM estimates understated the eventual opportunity.

However, not every company follows that path.

When a market is already well-defined and there is no credible mechanism for expansion, investors should carefully examine the assumptions embedded in the valuation. In many cases, the valuation only works if the company achieves extraordinary levels of market share, pricing power or profitability that are rarely observed in practice.

The key question is not whether a valuation exceeds today's TAM.

The key question is what must be true for that valuation to be justified—and whether those assumptions are realistically achievable.

Why The Pattern Persists

Despite these recurring outcomes, capital continues to flow into structurally constrained markets.

Part of the reason is that early-stage metrics do not reveal market limitations. Growth rates, retention figures and customer enthusiasm can look nearly identical across both large and small opportunities.

At the same time, AI has made many markets appear larger than they actually are. The belief that new technology will fundamentally reshape market boundaries is sometimes correct. But it is also frequently overapplied.

There is another force at work as well.

For investors, the cost of missing a truly exceptional company is far greater than the cost of investing in a market that ultimately proves constrained. That asymmetry naturally encourages more false positives.

As a result, capital repeatedly flows toward categories where product quality is obvious but market limitations are harder to see.

Market Selection As The Primary Lever

Ultimately, the difference between good outcomes and exceptional ones in software is often determined at the level of market selection.

The largest outcomes tend to emerge in markets tied directly to revenue generation, where software can own core workflows, expand naturally over time and capture a meaningful share of the value it creates.

In contrast, markets constrained by buyer type, limited customer populations, weak pricing power or a vulnerable position in the technology stack often produce strong businesses—but not outliers.

The challenge is that, in the early stages, both types of markets can look remarkably similar.

That is why this pattern continues to repeat.

And why, in software investing, the most important question is often not whether a company is good—but whether the market it operates in is capable of supporting the outcome investors expect.