Our philosophy has not changed. The environment in which we execute it has.

For more than two decades, Marriott’s investment philosophy has been anchored in a simple principle: high-quality companies that can reliably grow dividends tend to deliver more predictable long-term outcomes. This remains the foundation of how we invest.

What has changed is the environment in which that philosophy must be executed. The volume of information, the speed of change, and the global breadth of markets have expanded considerably. At the same time, the technology available to process that information has fundamentally shifted. These two forces together created an opportunity: to take a tried and tested investment philosophy to another level.

Rebuilding research architecture from first principles

When we began exploring how AI could support our process, we chose not to retrofit the technology into old workflows. Instead, we returned to first principles and rebuilt the architecture from the ground up, not to modernise for its own sake, but to extend the consistency and reach with which our philosophy could be applied.

The organising principle was a simple inversion. In traditional research, analysts spend most of their time on routine analysis. Judgement is applied with whatever time remains. We reversed this. AI now handles structure, consistency, and monitoring. Analysts focus on interpretation, context, and decision-making. The result is not automation of judgement. It is elevation of it. The most significant gain was one of scale and depth. A focused team can now operate with an analytical reach and monitoring capability of a much larger global structure. With AI handling data processing, change monitoring, and routine financial statement analysis, our analysts now cover a far broader universe and spend more time on interpretation. This expands in-depth company coverage several-fold, strengthens early risk detection, and increases the comparative consistency of assessments over time.

For instance, analysis of a newly released set of financial statements, assessing fundamental changes across earnings quality, capital allocation, and dividend sustainability, previously took three days. It now takes three hours, with the areas of uncertainty clearly highlighted for further interrogation by the analyst. Similarly, a significant deterioration in cash flow quality or balance sheet strength is now flagged and escalated within minutes of results being released, rather than waiting days for manual review.

The structural shift across the investment industry

We recognised early that the forces reshaping our own process would reshape the entire industry. As the cost of processing information falls and analytical capability becomes increasingly accessible, the sources of competitive advantage are moving. Tasks that once required large teams can now be performed by AI at a fraction of the time and cost. What was once a competitive advantage is becoming basic investment infrastructure. The edge no longer lies in having analytical intelligence. It lies in how that intelligence is structured, governed, and applied over time. This is the shift we built for.

From information to architecture

A firm that bolts AI onto legacy workflows will gain efficiency but not differentiation. The real question is whether the investment process itself has been redesigned to compound AI’s strengths over time.

Our architecture is not a set of tools added to an existing process. By decomposing our income-focused investment process into clearly defined, granular components, each with its own analytical framework, and then deploying AI to execute within that structure, it is engineered to improve as AI improves. The result is an investment process that does not age. It compounds.

When information processing becomes commoditised, interpretation becomes more valuable. This is where boutique focus becomes a real structural advantage. A smaller, stable team with a shared philosophy and a deep understanding of the client promise brings something that scale cannot replicate: purposeful judgement refined over many years working together. Most of Marriott’s investment professionals have been with the business for more than a decade. AI does not dilute that. It amplifies it.

This is why we invested heavily in the human side of the architecture. A formal mechanism directs analyst attention to the decisions where judgement most improves outcomes, ensuring time is spent on what actually makes a difference. Boutique focus and global reach, once a difficult combination to achieve, are no longer in tension.

The final differentiator: trust

Clients and allocators will increasingly ask: how do you govern this? Can you explain it? Is it auditable? Firms that cannot answer clearly will struggle, regardless of how sophisticated their models are.

Marriott’s Investment Committee structure, in place for more than twenty years, provided the governance foundation into which this architecture was built. The culture of collective review, documented rationale, and structured challenge was already established. Most firms adopting AI must build oversight frameworks from scratch. Ours was already there.

That history matters. It means AI was introduced into a culture of accountability, not instead of one. Every decision remains human. Every override is documented. Every methodology change requires Investment Committee approval. The system is designed to be explained, examined, and trusted.

The game has changed

Scale no longer determines reach. Headcount no longer determines coverage. The advantages that once favoured large firms, breadth, consistency, monitoring depth, are now available to any team with the architecture to deploy them. Size, on its own, counts for very little anymore.

Firms that have not yet rethought their process are not simply late. They are building on foundations that are quietly eroding beneath them.

The winners in active management will not necessarily be the biggest. They will be the ones who understood this earliest and moved with conviction. Who rode the wave, rather than being swept away by it. Marriott has been running its AI-native process alongside traditional workflows for the past three months. The early results give us confidence that what we have built will deliver a step change in how our investment philosophy is executed for our clients.