Enterprise Software & AI: A Balanced View for Long-Term Allocators
Sonu Chawla, CFA
Portfolio Manager & Analyst
Software & Technology Services
“These risks are real, but overstated.”
Artificial intelligence introduces meaningful uncertainty into the long-term outlook for enterprise software, particularly around competitive dynamics, pricing durability, and terminal value assumptions. While these risks warrant close monitoring, we believe the market is extrapolating worst-case outcomes that are inconsistent with historical precedent and current enterprise behavior.
The prevailing concerns can be grouped into three areas:
1. Potential for Increased DIY Development and Churn
There is a growing perception that LLMs (large language models) will enable enterprises to develop internal software solutions or custom extensions more easily, reducing reliance on third-party vendors and increasing customer churn over time.
2. Heightened Competitive Intensity and Pricing Risk
AI may lower development costs and blur traditional software category boundaries:
- Startups may reach functional parity more quickly using AI-assisted development
- Incumbents may expand into adjacent markets, increasing overlap
- LLM providers are introducing agentic layers that sit atop existing platforms
3. Structural Headwinds to Seat-Based Growth
Many application software business models remain tied to seat count. If AI meaningfully automates white-collar workflows, seat expansion could slow or plateau in certain end markets.
Our Perspective: These Risks Are Real, but Overstated
Enterprise Behavior Favors Stability Over Experimentation
While LLMs improve internal development productivity, we believe wholesale displacement of core third-party platforms is unlikely. Over multiple technology cycles, enterprises have consistently chosen to outsource non-core software functions to specialized vendors to reduce operational, security, and execution risk.
Historical parallels — including the rise of open-source software — suggest that lower perceived development costs do not translate into mass adoption of internally maintained systems at scale. Free or internally built solutions often carry hidden costs in maintenance, security, and accountability. Importantly, CIOs and CTOs remain highly sensitive to career and business risk associated with major platform transitions, particularly for mission-critical systems.
Software is a Small Budget Line and a High ROI One
Enterprise software typically represents a modest share of overall cost structures, particularly relative to labor. In periods of cost scrutiny, enterprises have historically prioritized headcount rationalization and operational efficiency over removing core software platforms that underpin business processes. This limits the economic incentive to aggressively displace incumbent vendors.
Incumbents Are Actively Adapting to the AI Shift
Unlike prior platform transitions (e.g., client-server to cloud), AI adoption does not require a full architectural rewrite or a disruptive change to revenue recognition models. As a result, incumbent vendors have shown limited hesitation in embedding AI capabilities into existing products.
Pricing Models Are Likely to Evolve
Seat-based pricing may face pressure in certain use cases, particularly where automation reduces incremental user counts. However, enterprise software has historically been priced on value delivered rather than strict unit measures. We expect a gradual shift toward consumption-based or outcome-oriented pricing models, with less disruption to aggregate monetization than current market narratives imply.
Investment Implication
AI has widened the range of outcomes for enterprise software. While incumbent platforms retain structural advantages that may support long-term durability, uncertainty around terminal value and competitive dynamics is unlikely to be resolved in the near term and may continue to weigh on the sector.
From a portfolio perspective, software can appear tactically oversold at times. However, the medium-term overhang from unresolved AI-related debates remains, and downside risk is meaningfully higher than in prior cycles. This reinforces the importance of selectivity, a focus on proven platforms, and disciplined valuation rather than broad exposure.
Disclosures
This material is for your private information and is provided for educational purposes only. The views expressed are the views of TimesSquare Capital Management, LLC only through the period ending February 2026 and are subject to change based on market and other conditions. The opinions expressed may differ from those with different investment philosophies. The information we provide does not constitute investment advice and it should not be relied on as such. It should not be considered an offer or solicitation to buy or an offer to sell a security. It does not consider any investor’s particular investment objectives, strategies, tax status or investment horizon. We encourage you to consult your tax or financial advisor. All material has been obtained from sources believed to be reliable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy of, nor liability for, decisions based on such information.
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