Software Manifest Destiny: Why Vertical Software Companies Will Lead the AI Revolution

In the 19th century, "Manifest Destiny" described the inevitable expansion of pioneers across a continent. Today, a similar inevitability is unfolding in technology: mission-critical software companies are destined to expand their domains with artificial intelligence. At Wingman Growth Partners, we have witnessed how vertical market software businesses – the system-of-record providers that run core operations in specific industries – hold an unfair advantage in the AI era. These companies have all the data, business and workflow knowledge, and distribution moats to capture the benefits of AI. It is effectively their Software Manifest Destiny to do so. But manifest destiny is not a passive fate; it’s an opportunity that must be seized. Those incumbents that leverage their advantages will dominate their markets, and those that don’t risk being left behind.

System-of-Record Companies: The Ultimate AI Launchpad

Every industry has its system-of-record software – the mission-critical platforms that businesses can’t live without. They manage patient records in hospitals, track aircraft maintenance in aviation, process core banking transactions, handle insurance claims, automate regulatory reporting, and so on. These software providers are often deeply embedded in workflows and have been gathering rich, domain-specific data for years or decades. This unique position gives them an unfair competitive advantage when it comes to layering on new technologies like agentic AI. Key advantages include:

• Proprietary Data & Domain Knowledge: Vertical software incumbents sit atop troves of industry-specific data and process knowledge. Their applications encode the business rules, workflows, and best practices of their vertical. This means any AI applied can be trained or fine-tuned on high-quality, relevant data that newcomers simply don’t have. Furthermore, incumbents understand their customers and their pain points, giving a product development advantage to create solutions customers want (which code-gen tools help them do even faster!).
• Embedded Distribution & Customer Trust: System-of-record providers are already integrated into the daily operations of their customers. They are trusted vendors with established relationships across the entire industry and serve workflows that cannot have “down time”. This distribution advantage means when they roll out a new AI-driven feature, it can be instantly deployed to thousands of users through a simple update – no new sales cycle required. Customers are also more likely to adopt an AI enhancement from a software partner they already trust, rather than a brand-new solution. In enterprise software, incumbency is powerful: these products are sticky control points with inherently low churn. As one venture investor put it, vertical SaaS leaders enjoy “account and workflow gravity” – customers prefer one integrated solution that already works, instead of stitching together multiple new tools.
• Contextual AI Integration: Because these incumbents own the system of record, they can embed AI directly into existing workflows. The AI isn’t operating in a vacuum; it has direct, secure access to the underlying data, documents, and real-time transactions of the platform – domain-specific, proprietary data that takes years to accumulate and generate insights from. This context-rich integration dramatically increases the impact of AI. In other words, an AI embedded in a trusted vertical app can immediately answer industry-specific questions or automate tasks using the customer’s own data, rather than some generic model detached from the business.

Vertical software companies have a wide moat as AI accelerators. They own the critical data, they’re wired into the industry’s distribution channels, and they understand the nuances of their domain. An upstart AI vendor might boast cutting-edge algorithms, but without the proprietary data or a way into the customer’s workflow, it’s fighting uphill. The incumbents hold the high ground – if they choose to take advantage of it.

Manifest Destiny in Action: How Incumbents Are Embracing AI

Many forward-thinking system-of-record providers are beginning to fulfill their manifest destiny by launching AI and analytics features that build on their core systems. A few examples across industries:

• Aviation: CAMP Systems, the longtime system-of-record for aircraft maintenance and inventory management, recently introduced AI-driven pricing and quoting tools integrated into its platform. By leveraging decades of maintenance and parts data, CAMP’s new features address inefficiencies in how aviation parts are quoted and priced, enhancing profitability for parts suppliers. In short, CAMP took a process that was manual and opaque, and infused it with intelligence – all within the familiar software its customers already use daily. The result is better, faster decision-making for users, and a stickier, higher-value product for CAMP.
• Life Sciences: Veeva Systems has become a poster child for vertical SaaS by dominating the life-sciences software space. Now Veeva is doubling down on AI. In April 2025, it announced a sweeping initiative to embed AI throughout its product suite – from clinical trial management to sales force automation. Because Veeva’s applications already manage critical functions (like clinical data capture, regulated content, and pharma sales outreach), adding AI yields immediate benefits. Imagine a pharma sales rep’s CRM that can suggest the next best action based on learned doctor preferences, or a quality management app that can auto-summarize an adverse event report. Veeva’s AI can do this in context, pulling from the customer’s own data in Vault, which multiplies its effectiveness. Veeva’s CEO, Peter Gassner, aptly noted that core systems provide the structured data and workflow, while “GenAI brings the human-like ability to derive answers and insights… Core applications and GenAI working seamlessly together will bring significant productivity gains.” Veeva is effectively ensuring it captures the AI opportunity within life sciences rather than ceding ground to newcomers.
• Insurance: In the property & casualty insurance sector, Guidewire Software – the system-of-record platform used by many insurers – has launched AI-powered applications to improve underwriting and claims. In its latest release, Guidewire introduced AI-driven “Claims Intelligence” features that analyze years of claims data to predict things like injury severity, litigation risk, or likely payout. These capabilities turn the unstructured data in claims notes and documents into actionable risk scores and next-step recommendations for adjusters. Critically, they are delivered within Guidewire’s core software that insurers already use, meaning adjusters see AI insights right in their workflow. By harnessing its massive dataset (aggregating over $200B of premiums worth of industry data) and deep integration, Guidewire is helping insurers operate faster and more accurately – and in doing so, solidifying its own position at the heart of the insurance process.‍
• Other Vertical Leaders: Across the board, top vertical SaaS players are moving quickly to bake in intelligence. Procore, which makes construction management software, has integrated AI to help project managers predict delays and cost overruns. Legal tech platforms like Clio are adding AI assistants to draft documents by leveraging case data. Even electronic health record providers like Epic are exploring AI enhancements to help doctors with decision support. The pattern is clear: those who control the system-of-record in a niche are using their scale, data, and engineering might to set the pace in AI adoption. They are not waiting around for startups to disrupt them – they are preemptively integrating the best of AI into their offerings.

These examples highlight the core thesis of Software Manifest Destiny: the incumbents that own the “land” (data + workflow) are best positioned to capitalize on the new “gold” (AI-driven intelligence). Each new AI feature further increases the customer lock-in and value of the platform, creating a virtuous cycle. An aircraft maintenance system that also optimizes pricing, or an insurance system that also predicts claim outcomes, becomes indispensable to its users. And because the AI is tailored to the specific vertical, it outperforms generic tools that lack industry context.

The Window of Opportunity – And the Cost of Inaction

While the deck is stacked in favor of system-of-record providers, destiny still favors the bold. These companies must actively leverage their advantages; otherwise, they leave an opening for competitors. The current moment feels akin to a land rush in tech: On one side, incumbent software firms have woken up to the AI opportunity and are re-prioritizing roadmaps to inject AI into their products. Even large, publicly-traded vertical SaaS companies have shown surprising agility in pivoting toward generative AI. They understand that massive customer value is at stake and are reallocating resources accordingly. On the other side, AI-native startups are cropping up in every vertical. Many are well-funded by venture capital and laser-focused on one narrow AI application. They boast modern UX and buzzworthy AI capabilities, hoping to either dislodge a piece of the incumbents’ business or force an acquisition. In some cases, VCs have poured tens or hundreds of millions into tiny AI startups aiming to challenge incumbents. This influx of cash can temporarily distort the market – driving up customer expectations and pressuring incumbents to respond. Founders of established software firms should act like a startup again, evangelizing their AI vision to customers with the same excitement as the upstarts.

The good news for incumbents is that they don’t need to cede ground if they move quickly. They have the data and customer base that AI startups desperately want. If a system-of-record provider introduces a compelling AI feature today, many clients will prefer to get it from their existing vendor rather than try an unknown startup. After all, enterprise customers tend to be risk-averse and resource-constrained – they’d rather extend a tool they already use than implement and integrate an entirely new solution that they may not trust. This dynamic buys incumbents precious time and leverage.

However, complacency can be fatal. If an incumbent drags its feet, it runs the risk that:

1. Customers Experiment Elsewhere: Business units might start adopting niche AI tools on their own (so-called shadow IT) if their primary software isn’t delivering the innovation they want. Over time, those tools could gain a foothold.

2. Talent and Mindshare Shift: The best product and engineering talent may prefer joining companies doing cutting-edge AI work. If incumbents aren’t visibly pushing boundaries, they may struggle to attract the skills needed to compete – or even lose parts of their existing teams to AI ventures.

3. Diminished Value Proposition: Most critically, if an incumbent fails to augment its offering with intelligence, its product could become commoditized. In a future where every platform has some level of built-in smarts, a pure workflow tool without AI will feel outdated. The historical record is unkind to software companies that miss major platform shifts (consider those that dismissed the cloud, or mobile, only to watch competitors leapfrog them).

In short, the time is now for system-of-record businesses to assert their manifest destiny. They hold strong cards, but they must play them. The next few years will likely define the winners and losers for the coming decade of AI-powered software.

From System of Record to System of Action: A Playbook

How can vertical software and fintech companies practically execute on this vision? Based on our experience, a few strategic steps can unlock outsized gains:

1. Layer Intelligence into Core Workflows: Look at every key process your software manages (e.g. invoice processing, scheduling, compliance checking) and every process your customers execute immediately before and after using your software and ask how AI can enhance or automate it. This could mean embedding a generative AI assistant in the UI (to answer user questions or compose content), adding predictive analytics under the hood (to flag anomalies or opportunities), or automating data entry and routine decisions. This could also mean using an agent to produce a document that your customers used to produce manually. Prioritize features that directly drive your customers’ KPIs – e.g., reducing their costs, increasing their revenue, or saving them time. Even a simple AI-driven recommendation engine within a familiar workflow can delight users and differentiate your product.
2. Monetize Your Unique Data: Your accumulated data is not just exhaust; it can become a valuable product in itself. Consider offering benchmarking analytics, industry reports, or data-driven add-ons that surface insights from aggregate trends. Many vertical SaaS firms have rolled out business intelligence modules for this reason – transforming siloed transactional data into dashboards and benchmarks that help customers make better decisions. With new AI capabilities, you can take this further: for example, provide predictive forecasts (e.g. a system that predicts inventory needs based on historical patterns) or prescriptive advice (e.g. an AI coach that advises a sales rep what to say next based on past successful interactions). Customers are often willing to pay for these high-value insights on top of the base software fee, boosting ARPU (average revenue per user).
3. Build (or Buy) AI Competence: Successfully integrating AI might require skills or tech assets that your team doesn’t currently have. Evaluate whether to build, partner, or acquire to accelerate the roadmap. Building in-house ensures the deepest integration of AI with your proprietary data – but it can be slow if you need to hire scarce AI talent. Partnerships (with AI model providers, or cloud AI services) can jump-start your capabilities, as Veeva did by creating an AI partner program for specialized solutions. Targeted acquisitions can also make sense: for instance, acquiring a small AI startup that has a great algorithm but lacks distribution could give you both the tech and the talent in one move. Whatever the path, invest in educating your product teams about AI possibilities, and perhaps create an internal “AI task force” to prototype ideas. The goal is to infuse an AI-forward mindset into your company culture, so that product managers and engineers naturally think about AI in every new feature.
4. Address Change Management and Trust: Keep in mind that your customers may need guidance to fully embrace new AI features. As you roll out intelligence in your software, invest in customer success and education. Provide clear documentation about how the AI works, its limitations (e.g. does it ever hallucinate or require human review?), and how it maintains data security/privacy. Consider offering the AI capabilities as opt-in at first, allowing users to pilot them. By being proactive about explainability and control – for example, showing the source of an AI-generated insight or allowing users to adjust its suggestions – you will build trust in the system. Remember, you’ve spent years earning your reputation as a reliable system-of-record; don’t squander it by deploying half-baked AI. Get it right, and your clients will reward you with deeper loyalty.

By following this kind of playbook, a vertical software company can transform from simply a system of record (a source of truth) into a system of intelligence and action (a source of insights and automation). You are essentially moving up the value chain: instead of just recording what the user does, your software is now guiding the user on what to do. That is a profound shift – one that justifies higher pricing, sticks customers closer to your platform, and widens the gap against any competitors.

About Wingman Growth Partners: Wingman Growth Partners is a private equity firm focused exclusively on majority investments in vertical market software, financial technology, and data businesses in the U.S. and Canada. We specialize in founder-led companies – meaning we provide significant capital and hands-on support to help you scale, while providing significant liquidity to existing shareholders. Our team has over 25 years of combined experience investing in and advising software companies through major growth transformations. We’ve been in the trenches with B2B software businesses as they’ve revamped product strategies, expanded go-to-market, and adopted new technologies. In short, we understand your world and speak your language. Learn more about Wingman Growth Partners at www.wingmangrowth.com