Software continues to be one of the strongest drivers of value creation. In our recent article, “Why Software Investment Matters More Than Ever,” we highlighted how software has become a central theme for investors, powering digital transformation, operational efficiency, and entirely new business models. However, as the market evolves, new structural headwinds are emerging. These shifts introduce real risks and potential value traps, particularly for investors who focus solely on topline growth without examining the underlying fundamentals. Now, we turn to the other side of the equation, examining how investors can avoid these value traps and approach software investing with sharper discipline and more strategic rigor. Below we unpack each challenge and outline a more disciplined, risk-aware investment approach.
Competitive Pressure: AI-Native Entrants and the Squeeze on Incumbents
The arrival of generative AI and “agentic” software fundamentally changes competitive dynamics. Rather than large legacy suites sold seat-by-seat, new players are offering purpose-built, AI-powered tools delivered under usage- or output-based pricing models. These tools often address narrow but high-impact use cases, from code generation to content creation to automated workflows and can displace generalist platforms.
For example, media reports in 2025 noted that many publicly traded mid-market software firms are being “squeezed” between nimble AI-first startups and hyperscale cloud/AI platform competitors. The result: rising churn, weaker renewal rates, and deteriorating deal economics for incumbents.¹
For investors, this means that growth in top-line revenue may no longer signal defensibility or long-term sustainability. Instead, the focus must shift to whether a company’s architecture is flexible enough to incorporate model-based enhancements; whether its distribution and sales model can maintain customer lifetime value; and whether it has enough differentiation, in data, product, or workflow integration, to resist commoditization.
Commoditization: When Core Technical Differentiation Becomes a Hosted Commodity
The proliferation of open models, commoditized compute infrastructure, and widespread access to common AI building blocks is lowering entry barriers across many software use cases. In such an environment, core technical differentiation once a competitive moat becomes replicable by any well-funded challenger.
When the foundation of value is “access to a model + some integration,” rather than deeply embedded workflows or proprietary data, differentiation quickly erodes. In those circumstances, seat-based subscriptions tend to give way to usage- or outcome-based pricing: more variable, harder to underwrite, and often compressing margins. A growing number of analysts warn that these shifts are not yet fully reflected in public or private valuations.²
This dynamic is especially dangerous for horizontal, generalist software tools, whereas vertical-specific, workflow-centric tools or deeply embedded productivity platforms tend to retain pricing power longer.
Valuation & Execution Risk: Premium Multiples, Aggressive Growth Assumptions & Costly Transformation
Despite headwinds, investor appetite for software remains elevated. Many private-market participants continue to apply cross-sector premium multiples to software platforms often justified by optimistic assumptions of sustained revenue growth and margin expansion.
However, as growth in certain sub-segments slows and IT budgets tighten globally, the burden of delivering returns shifts to execution: delivering meaningful product improvements, transforming go-to-market motions, reducing churn, and possibly absorbing higher infrastructure or AI-computer costs. Bain’s Global Private Equity Report (2025) highlights that revenue growth drives most buyout returns for software, but many buyers under-estimate the investment needed to achieve the growth assumptions embedded in price. Without disciplined, well-funded plans, these transformation efforts may fail to deliver, leaving investors exposed to downside risk.
As an effect, paying a premium price for “software growth” today, without a realistic roadmap to realize that growth, is a classic value trap.
Emerging Evidence: Repricing, Deal Stratification, and Selectivity
Recent data and market analysis by Windsor Drake suggest that the software investment universe is already stratifying. Scaled, well-capitalized software companies with differentiated products, defensible workflows, and strong distribution continue to command premium valuations. By contrast, smaller or mid-market companies, especially those without deep defensibility are increasingly experiencing steeper valuation discounts or greater variability in deal outcomes.³
This divergence is a clear signal that investors are becoming more selective, and the bar for defensibility and long-term value is rising.
How Investors Should Navigate the New Reality
Given these headwinds, a more disciplined, risk-aware approach is required. Below are the key investment principles we advocate, especially when evaluating software (and AI-enabled software) opportunities going forward:
- Focus on defensible differentiation, not just features. Prioritize businesses with proprietary data, deeply embedded workflows, or vertical-specific value-adds that are hard to replicate.
- Underwrite under multiple pricing regimes. When building financial models, stress-test not only for seat-based SaaS but also for usage- or outcome-based models; include scenarios with ARR volatility, variable customer lifetime value, and shifting CAC payback profiles.
- Require realistic execution plans & dedicated budgets. If the investment case depends on AI integration, product overhaul, or go-to-market reinvention — insist on a clear plan, timeline, milestones, and committed capital.
- Prefer scale or aggregation strategies. Larger platforms or aggregated portfolios tend to have more stable economics and are better positioned to absorb disruption or reinvest in product differentiation.
- Strengthen governance — include technical and product oversight. As AI becomes central to value creation, investment committees and boards should include technical or product expertise to evaluate trade-offs around compute costs, model licensing, data governance, and long-term defensibility.
Why Software Still Matters, But With Perspective
The opportunities remain immense from enabling digital transformation across traditional industries, to unlocking operational leverage, to accelerating new business models. However, the rules of the game are shifting.
AI, commoditization, shifting pricing models, and execution risk mean that investors must be more selective, more disciplined, and more forward-looking than ever before. In today’s environment, success will no longer come merely from backing software but from backing software with real defendable moats, credible execution plans, and resilience against disruption.
For investors who apply this disciplined lens and operators willing to build for defensibility, software remains a powerful engine. But those who chase “growth at any price” risk falling into value traps.
