Moat Durability in the AI Era

What We Bought and Why

The Jensen Quality Growth Strategy added to three businesses during the quarter: Verisk Analytics, Broadridge Financial Solutions, and Veeva Systems. All three cases share certain key attributes, including proprietary data, regulatory lock-in, and workflow embeddedness as sources of competitive advantage, where we believe AI amplifies rather than erodes the moat. AI models are only as capable as the data they draw upon. That makes non-replicable, proprietary data more valuable in the AI era, not less, while regulatory and workflow lock-in enhance financial and procedural switching costs.

Portfolio Actions at a Glance

Verisk Analytics (VRSK) holds what is arguably one of the most structurally defensible positions in our coverage universe. Its Insurance Services business operates on a contributory “give-to-get” model, where insurance carriers supply premium and claims data to Verisk in exchange for access to an industry-wide loss pool that anchors actuarial models, rate filings, and catastrophe pricing, helping insurers better understand and price risk. Exit from this contributory model is theoretically possible but practically untenable, since an insurer that stops contributing to Verisk’s database loses access to the broadest repository of P&C loss experience that exists, thereby putting their underwriting at a structural disadvantage to peers who continue their mutually beneficial relationship with Verisk.

This lock-in operates on two levels. The contributory data pool creates competitive lock-in, while Verisk’s ISO standardized forms and rating frameworks, incorporated into state regulatory processes, create legal and administrative embeddedness that no amount of capital can replicate quickly.

Verisk, acting as a centralized partner that connects stakeholders throughout the insurance industry, should be well positioned to take advantage of AI rather than falling victim. Cleaner, more robust data sets from insurers create an opportunity to expand Verisk’s insurance consortium beyond its traditional reach, into areas like Excess and Surplus, Life, and international insurance markets. Catastrophe modeling is among the most data-intensive applications of machine learning that exist. Verisk’s over 50 years of longitudinal data in underrepresented perils like wildfire, flood, and convective storm further enhances its value as climate risk reshapes loss distributions. And regulatory frameworks for AI in insurance rely on Verisk’s input to protect its clients’ data and ensure safe and ethical use, offering another example of how embedded Verisk is into insurance industry workflow.

Given Verisk’s inclusion in the software-related selloff, we opportunistically added to the position during the quarter.

Broadridge Financial Solutions (BR), in our view, is a business that is broadly classified as a professional services firm, a categorization that seems to be contributing to recent mispricing, since unlike Broadridge, we do see many professional services businesses facing genuine AI disruption risk, representing a potential “baby out with the bathwater” situation in Broadridge’s case.

We view Broadridge as a regulated financial infrastructure and software platform, operating as the system of record and authoritative source of record that the financial system depends upon for proxy voting, investor communications, and post-trade settlement across most U.S. broker-dealers and asset managers. Its Investor Communications segment, which accounts for approximately 70% of consolidated revenues, is legally mandated and subject to continuous regulatory audit.

Management recently indicated that “99% accuracy would put us out of business,” a concise explanation of why AI disintermediation risk here is structurally limited. Increased AI usage across the financial system is likely to increase — rather than diminish — the need for a trusted, auditable intermediary. In our view, Broadridge is in a unique position to serve that role.

“Increased AI usage across the financial system is likely to increase — rather than diminish — the need for a trusted, auditable intermediary.”

The primary uncertainty relates to the future of tokenization, or the issuance and transfer of securities on blockchain-based infrastructure, which remains largely theoretical today and not yet meaningfully implemented at scale, yet offering a wide range of potential outcomes. The SEC’s stance that even tokenized securities are still securities and subject to existing regulatory frameworks likely preserves Broadridge’s role as the authoritative source of record for the financial system broadly, but it’s an area worth monitoring closely as use cases evolve.

We took advantage of weakness in its share price to add to Broadridge given its robust and underappreciated strengths.

Veeva Systems (VEEV) is the leading provider of cloud software to the global life sciences industry, offering specialized applications across commercial, clinical, regulatory, and quality functions. Built originally on Salesforce and now operating on its own platform, Veeva has achieved deep vertical penetration among top biopharma companies in mission-critical areas like regulatory and clinical trial software.

Veeva has been perhaps the clearest example of short-term price weakness dislocating from long-term fundamentals, as investor attention appears to be focused on two primary concerns: Salesforce competing in life sciences CRM following the two companies’ separation agreement, and AI-related software concerns relating to Veeva’s future growth.

Regarding the first concern, Veeva announced in December 2022 and then formalized in September 2025 its separation agreement with Salesforce. We think the strategic rationale for the separation was sound, as remaining on a competitor’s infrastructure could constrain product velocity and limit platform control. Therefore, we view it as a sensible long-term risk mitigation strategy while maintaining strategic flexibility, with some customer churn worth it over the long run.

While commercial CRM competition has garnered much investor attention, and it is an important consideration, it distracts from the real crux of the long-term investment thesis for the company. Specifically, we view Veeva as more of a critical infrastructure provider than a software company, where its Vault R&D platform orchestrates mission-critical workflows as the de facto operating system for the industry, reported within Veeva’s R&D Solutions segment.

Chart 2

Veeva Systems Revenue by Segment 2017-2026 ($MM)

Source: Bloomberg; data as of April 24, 2026.

Veeva’s R&D Solutions segment was only $103 million in revenue in 2017, representing less than 20% of total sales. Over the past nine years, R&D Solutions has grown to represent over 54.7% of total revenues, whereas CRM, a component of Total Commercial Solutions, is estimated at 20% of total sales. Importantly, R&D Solutions remains Veeva’s core growth and profit engine, where it holds not only its strongest competitive advantages but also carries higher growth potential and margin profile than Commercial Solutions. Investors’ focus on the CRM side of the business, while rational, may be obfuscating the favorable long-term prospects for R&D Solutions in particular and the company overall.

On the second point, we view Veeva’s AI positioning as structurally superior to most software companies due to unique proprietary data serving as the input to AI, including 20 years of longitudinal life sciences-specific workflow data spanning clinical trial records, regulatory submissions, quality documentation, and adverse event reports that provide a context layer no foundation model can replicate without Veeva’s cooperation. This data, coupled with embedded regulatory validation and audit trails existing within workflows, result in high switching costs and may enable Veeva to serve as a key enabler for AI tools and functionality for the life sciences industry.

As of Q1 quarter-end, Veeva traded at under 20x forward earnings and 16x trailing EV/FCF, both below the S&P 500’s average multiple despite Veeva’s superior quality profile, a business with free cash flow margins above 40%, no gross debt, over $5 billion in net cash, and a dominant moat in a non-discretionary end market.

This is precisely the kind of investment opportunity our demanding ROE threshold and rigorous investment process is designed to identify — a business with a durable and improving competitive position whose stock has been caught in a sentiment-driven selloff that can be exploited by long-term investors.

We increased our exposure to Veeva in the quarter at a steep discount to our estimate of intrinsic value.

Microsoft: A Likely AI Winner Caught in the Selloff

Microsoft (MSFT) remains one of our largest portfolio positions and since our initial investment in 2005 it has been one of the largest contributors to performance. However, Microsoft declined roughly in-line with the broader software selloff during the first quarter, which warrants further review.

In our view, the selloff in Microsoft alongside the broader software universe reflects a fundamental misinterpretation of its AI positioning. Instead of being directly threatened by AI, we believe Microsoft remains one of the best businesses positioned to benefit from AI at scale.

While perhaps obvious, it’s worth highlighting that Microsoft’s Copilot is not a standalone AI product competing for new customers. Rather, it is an AI capability embedded into the Microsoft 365 ecosystem already used and integrated into existing workflows by Microsoft’s enterprise customers. In addition to the technological challenge of producing viable competing offerings to Microsoft’s suite of services, a new competitor faces the entrenched habits, compliance infrastructure, and IT governance structures of potential enterprise customers. As AI becomes more capable, Copilot’s entrenched position strengthens, potentially adding to already robust switching costs. Microsoft’s most recent quarterly results delivered revenue growth of 15% year-over-year alongside continued Azure expansion — results consistent with AI amplifying rather than threatening the core franchise.

Instead of being directly threatened by AI, we believe Microsoft remains one of the best businesses positioned to benefit from AI at scale.”

The salient near-term question for Microsoft is not whether its moat is durable, but whether the transition from seat-based to consumption-based pricing — which AI is accelerating across enterprise software — introduces revenue volatility even as the long-term outlook strengthens. We believe it does, which helped inform the decision to trim the position during the period, while remaining one of our largest positions at quarter end.

Microsoft has navigated comparable business model transitions before, including the shift from perpetual licenses to cloud subscriptions. Near-term pricing model uncertainty is not the same as long-term franchise risk. We trimmed while our long-term conviction remains very much intact.