A general-purpose CRM vendor and a vendor of management software for pharmaceutical laboratories no longer have much in common. The former sees its basic features—contact management, sales pipelines, dashboards—reproduced within weeks by AI agents. The latter, rooted in FDA regulatory requirements and molecular traceability workflows, strengthens its competitive moat every quarter. This shift is far from incidental. According to Gartner, the global vertical SaaS market reached $157 billion in 2025, or 35% of the total SaaS market—and its growth outpaces horizontal solutions by 50%. Far from making everything uniform, generative AI is widening the gap between generic software and highly specialized business solutions.
TL;DR — AI commoditizes generic software functions (basic CRM, reporting, task management), eroding the value of horizontal vendors. Vendors that capitalize on deep industry expertise—proprietary business data, regulatory workflows, niche integrations—capture a lasting valuation premium. Industry specialization is no longer a positioning choice: it is a condition of survival.
The accelerating commoditization of generic software functions
What AI makes trivial within months
Five years ago, building a project management module integrated into an ERP took six months of development and an eight-person team. Today, a senior developer equipped with AI agents generates a working prototype in two weeks. “Horizontal” software building blocks—contact management, task scheduling, analytical reporting, approval workflows—have become technical commodities.
McKinsey identifies this phenomenon in its report on AI disruption in software: software categories centered on data access and synthesis are the first to be affected by commoditization, with churn rates potentially rising by one to three percentage points. The reason: the growing ease of software development is pushing more businesses from “buy” to “build” for their generic tools.
The horizontal mid-market trap
Vendors positioned around cross-functional capabilities without industry differentiation are being squeezed. On one side, the giants (Microsoft, Google, Salesforce) are integrating AI extensively into their suites, making their basic features almost free. On the other, companies are building internal tools themselves using LLMs and AI agent frameworks.
According to Andreessen Horowitz (a16z), 76% of enterprise AI use cases now involve buying rather than in-house development—but this statistic hides a crucial nuance: companies buy specialized vertical solutions and build the generic tools they need internally. The horizontal AI market (general-purpose copilots) is worth $8.4 billion, but just three players control 86% of it (ChatGPT Enterprise, Claude for Work, Microsoft Copilot). There is no room for a fourth general-purpose entrant.
Three warning signs for horizontal vendors
Does your software have at least two of these characteristics? Commoditization poses a direct threat:
- Features reproducible through a prompt: your main features can be described in natural language and generated by an LLM within hours.
- Nonproprietary data: your software does not generate unique industry data that competitors cannot reproduce.
- Standard integrations: your API connectors are the same as every competitor's (Zapier, Make, conventional REST APIs).
Why industry specialization creates a lasting advantage
The domain-knowledge moat
Vertical software is more than horizontal software “reskinned” with industry terminology. The difference operates at three structural levels:
1. Embedded regulatory workflows. Management software for a clinical laboratory natively incorporates ISO 15189 requirements, sample traceability protocols, and ANSM compliance forms. These business rules, codified by domain experts over several years, cannot be generated with a GPT-4 prompt.
2. Industry-specific data models. An ERP for construction structures its data around work packages, construction works, progress payment statements, and retention amounts—concepts absent from every general-purpose ERP. This data schema, validated by hundreds of real construction projects, constitutes functional intellectual property.
3. Niche integrations. A management platform for law firms connects to RPVA (France's private virtual network for lawyers), Télérecours for administrative litigation, and case-law databases. No general-purpose vendor is interested in these connectors.
Figures that validate the vertical premium
Market data confirms the structural advantage of industry specialization:
| Indicator | Vertical SaaS | Horizontal SaaS | Difference |
|---|---|---|---|
| Annual growth (CAGR) | 18–22% | 12–15% | +50% |
| Net revenue retention | 120–140% | 110–120% | +15–20 pts |
| Share of new software unicorns (2025) | 43% | 57% | × 2.4 vs. 2020 (18%) |
| Valuation premium (at equal revenue) | +35% | Baseline | — |
| EBITDA margin (industry leaders) | 30–40% | 20–25% | +10–15 pts |
Sources: Gartner, Business Research Insights, SaaSworthy (2025)
Net revenue retention is the most telling indicator. A rate of 120–140% means existing customers spend 20–40% more each year—evidence that the software becomes more critical to their business over time, not less.
Five verticals where the specialization premium is highest
Vertical SaaS is not a homogeneous category. Some sectors capture most of the value:
| Vertical | Market size (2025) | “Lock-in” factors |
|---|---|---|
| Healthcare IT | $52 billion | Regulation (HIPAA, HDS), HL7/FHIR interoperability, sensitive patient data |
| Construction tech | $18 billion | BIM integration, DTU technical standards, real-time management across work packages |
| Legal tech | $12 billion | Legal connectors (RPVA, Télérecours), case-law databases, enhanced GDPR compliance |
| Restaurants / hospitality | $11 billion | Integrated POS, HACCP management, delivery interfaces across platforms |
| Real estate tech | $10 billion | Agency mandates, mandatory property surveys, listing portals, Hoguet law regulation |
Source: Tech Insider, industry compilation (2025)
AI as an accelerator of specialization, not uniformity
The generative AI paradox for vendors
The prevailing intuition suggests that AI, by democratizing software development, should favor general-purpose solutions. The reality is the opposite. AI amplifies specialists' advantage for three structural reasons.
Reason 1: industry-specific training data is scarce. A general-purpose LLM performs well on cross-functional tasks (writing, coding, analysis). But diagnosing an anomaly on a food production line or predicting a delivery delay on a civil engineering project requires industry training data that only vertical vendors have accumulated over years. These datasets form a defensive “moat” that AI strengthens rather than closes.
Reason 2: vertical AI agents outperform generic agents. Gartner predicts that 40% of enterprise applications will incorporate task-specific AI agents by the end of 2026, compared with less than 5% in 2025. These agents are not generic chatbots: they are autonomous systems capable of executing complete business workflows—checking compliance in a credit application, orchestrating a clinical protocol, managing a public procurement process. Their performance depends directly on the industry depth of the vendor designing them.
Reason 3: the “service-as-software” model favors specialists. McKinsey identifies an emerging model in which vendors no longer sell a tool, but a business outcome: platform + AI agents + automation + industry expertise, packaged as an integrated solution. This “service-as-software” model requires intimate domain knowledge—exactly what vertical vendors possess and generalists cannot acquire quickly.
AI adoption among vertical vendors: unprecedented acceleration
The figure is striking: 68% of vertical SaaS vendors now integrate AI capabilities into their products, compared with just 22% in 2023. In two years, AI has moved from an “experimental feature” to a “structural component” of the vertical offering.
The momentum is similar in France. According to the Numeum/EY 2025 survey of French software vendors, 83% place AI among their top three technology priorities (+9 points compared with 2023), and 61% have already integrated generative AI features into their offerings. French vendors' worldwide software publishing revenue reached €23.1 billion in 2024, and the most dynamic players combine industry roots with AI integration.
Winning strategies for vendors: pivot toward depth
Strategy 1—Capitalize on proprietary industry data
AI commoditization has a direct corollary: in a world where models are increasingly interchangeable, data becomes the primary source of competitive differentiation. Vertical vendors that structure, enrich, and extract value from exclusive industry data build a cumulative advantage.
Veeva Systems illustrates this logic. Specializing in life sciences, Veeva has accumulated data on regulatory processes, clinical trials, and physician–pharmaceutical industry interactions for more than ten years. The result: a $35 billion market capitalization and an almost unassailable position in its niche. No general-purpose vendor, even armed with the best LLMs, can reproduce that depth of data within a few quarters.
Strategy 2—Build business AI agents, not chatbots
The temptation for a vendor is to add an AI chatbot to its existing interface and tick the “AI integrated” box. This superficial approach creates no lasting value. Vendors that differentiate themselves build AI agents capable of executing complete business processes:
- In construction: an agent that automatically analyzes a CCTP (project-specific technical specifications), identifies deviations from applicable DTU technical standards, and generates a compliance report.
- In healthcare: an agent that prepopulates a patient record from unstructured medical reports, following the ASIP Santé framework.
- In legal services: an agent that automatically classifies documents in a litigation file, identifies applicable legal arguments, and prepares draft submissions.
Gartner estimates that agentic AI could account for 30% of enterprise software revenue by 2035, or more than $450 billion. This market will be captured almost exclusively by vendors capable of translating AI into concrete business value.
Strategy 3—Adopt the “service-as-software” model
The move from “software-as-a-service” to “service-as-software” marks a break in vendors' business model. Instead of charging for access to a tool, the vendor charges for an outcome:
| Dimension | Traditional SaaS | Service-as-Software |
|---|---|---|
| What is sold | Access to a platform | Guaranteed business outcome |
| Pricing model | Per seat / per month | Per outcome / per transaction |
| AI's role | Additional feature | Core execution engine |
| Industry expertise required | Low | Critical |
| Barrier to entry | Technical | Technical + domain expertise + data |
This model naturally favors vertical vendors. A vendor that intimately understands an industry's processes can guarantee an outcome (“your healthcare GDPR compliance will be audited and corrected within 48 hours”) where a generalist can only provide a tool (“here is a compliance management module”).
The French case: an ecosystem ready for specialization
A dense vendor landscape that is still too horizontal
France has a dynamic software vendor ecosystem—the Numeum survey identifies a Top 250 whose combined revenue increases each year. But a significant share of these vendors remains positioned in cross-functional segments (sales management, HR, accounting) where competitive pressure is intensifying.
The French vendors standing out are those that chose a vertical early: Cegid in fashion and retail, Planisware in industrial project portfolio management, Oodrive in secure document management for regulated sectors. Their common feature: domain knowledge that cannot be copied in six months.
Why the French context favors specialization
Three factors make the French market particularly favorable to industry specialization among vendors:
The regulatory burden. France layers European regulations (GDPR, DSA, DMA, AI Act) with national rules (labor law, sector-specific regulation), creating complexity that only specialized vendors master. French payroll software bears no resemblance to American payroll software—and this complexity provides a defense against commoditization.
The structure of the economy. With 5,600 mid-market companies and 148,000 SMEs according to INSEE, France has a pool of businesses large enough to invest in industry-specific software, but not large enough to develop it internally. This segment is the natural territory of vertical vendors.
The developing AI ecosystem. France is investing heavily in AI (national AI plan, Bpifrance, competitiveness clusters), creating a pool of talent and technologies available to vendors with the industry vision to deploy them usefully.
The trap to avoid: false specialization
When “vertical” is just marketing packaging
Not every vendor claiming to be “specialized” really is. The difference between an authentically vertical vendor and a “disguised” horizontal vendor can be measured against specific criteria:
| Criterion | Authentically vertical vendor | “Disguised” horizontal vendor |
|---|---|---|
| Data model | Designed around the industry's business entities | Generic model with customizable fields |
| Product team | Includes industry domain experts | 100% generalist developers |
| Integrations | Native connectors to industry tools | Generic APIs (REST, webhooks) |
| Compliance | Industry certifications and labels | General compliance (GDPR, ISO 27001) |
| AI data | Trained on proprietary industry datasets | General-purpose LLM with customized prompts |
| Product roadmap | Driven by regulatory and business developments | Driven by the most requested features across all industries |
A CIO or business leader evaluating “specialized” software should raise these questions in the first meeting. A vendor that answers, “We can adapt to your industry,” instead of, “We know your industry,” is not truly vertical.
Five questions to ask a vendor claiming to be “specialized”
- What percentage of your revenue comes from our industry? (expected answer: > 70%)
- How many domain experts (non-developers) are on your product team? (expected answer: at least 2–3 people from the industry)
- Which industry certifications or labels does your software hold? (expected answer: specific certifications, not just ISO 27001)
- What industry data are your AI features trained on? (expected answer: proprietary datasets, not just public LLMs)
- Can you name three regulatory changes in our industry incorporated into your roadmap over the last 12 months? (expected answer: concrete, dated examples)
What this means for businesses buying software
Rethinking the vendor evaluation criteria
For CIOs, business unit directors, and company leaders, the commoditization of generic functions radically changes vendor selection criteria. Traditional evaluation grids—feature count, interface usability, price per seat—become secondary to three new deciding factors.
The vendor's industry depth. A vendor that understands your business constraints will reduce deployment costs by 40–60% compared with a generalist that needs to be configured, customized, and trained in your context.
The quality of the industry data feeding the AI. An AI agent trained on thousands of cases from your industry will be ten times more relevant than a general-purpose LLM. Ask to see the data, not just the demos.
The ability to evolve with regulation. Your industry changes. Your software must change at the same pace. A vertical vendor anticipates regulatory developments because it monitors the same sources as you—a generalist discovers them when you point them out.
Build, buy, or partner: the new three-part approach
Andreessen Horowitz's report on enterprise AI reveals that successful deployments are neither 100% bought nor 100% built: they are assembled. The optimal strategy combines three approaches:
- Buy for core business functions: choose a vertical vendor that masters your industry.
- Build for commoditized generic functions: develop the cross-functional tools you need internally (or commission custom development), using AI to reduce costs and timelines.
- Partner for integration and orchestration: work with a technical partner capable of connecting your purchased vertical components and your internally built tools.
This hybrid approach acknowledges a reality: value no longer lies in the software itself, but in intelligently assembling specialized components around your business processes.
FAQ
What does industry specialization mean for a software vendor? Industry specialization describes a vendor's strategy of focusing its product, data, and expertise on a specific industry (healthcare, construction, legal, etc.) rather than offering a cross-functional solution adaptable to every sector. This approach translates into a native business data model, industry integrations, and a roadmap driven by regulatory developments in the field.
Why does AI accelerate the commoditization of generic software? Generative AI makes it possible to reproduce in weeks features that once took months to develop: task management, reporting, basic CRM, approval workflows. According to McKinsey, this ease of development is pushing companies to build their own generic tools, increasing churn rates among horizontal vendors by one to three points.
Is vertical SaaS more profitable than horizontal SaaS? Market data confirms it. Leading vertical vendors report EBITDA margins of 30–40%, compared with 20–25% for horizontal vendors. Their net revenue retention reaches 120–140%, indicating that customers spend more each year. In 2025, vertical SaaS startups represented 43% of new software unicorns, with an average valuation 35% higher at equivalent revenue.
Which sectors benefit most from software specialization? Heavily regulated sectors with complex workflows benefit most from specialized software: Healthcare IT ($52 billion), construction tech ($18 billion), legal tech ($12 billion), restaurants/hospitality ($11 billion), and real estate tech ($10 billion). Their common feature: business constraints impossible to reproduce with a configured generic tool.
How can I assess whether a vendor is truly specialized in my industry? Check five criteria: the share of revenue from your industry (> 70%), the presence of domain experts on the product team, industry certifications held, the nature of the data feeding its AI features (proprietary versus generic), and its ability to cite recent regulatory changes incorporated into its roadmap.
Should you favor a vertical vendor or develop internally with AI? The optimal answer is hybrid. Buy vertical software for your core business functions (where industry depth is irreplaceable), build commoditized generic tools internally (where AI reduces costs), and work with a technical partner to orchestrate the whole. This “buy + build + partner” strategy is the one adopted by the best-performing companies, according to Andreessen Horowitz.
AI Coder Squad: building the custom components generic software no longer covers
AI's commoditization of generic software functions creates an opportunity for businesses: rapidly developing internal tools tailored to their specific processes, complementing their vertical business software. This is precisely where an AI-equipped senior team makes the difference—custom development that fills the gaps between your industry tools.
AI Coder Squad designs custom applications and AI agents for companies that want to move fast without sacrificing quality—with senior developers and an AI-powered approach.
→ Start your project and discover how AI Coder Squad can accelerate your next delivery.