Feeling Disrupted?

Two reinforcing seismic shifts appear to be underway: the transition of artificial intelligence from narrative to measurable economic impact and the reshoring of manufacturing and strategic capacity back to the United States. From our perspective, these forces are not operating in isolation – they are reinforcing one another and reshaping capital allocation, competitive dynamics, and the structure of market leadership itself.

The first shift is AI moving from narrative to real-world disruption. Productivity gains are becoming measurable, with software as ground zero and labor-intensive service industries close behind. AI is expanding labor productivity, redesigning workflows, and challenging competitive moats built on informational asymmetry and proprietary code. Unlike the prior software-driven era – defined by asset-light models, relatively minimal reinvestment needs, and extraordinary incremental margins – AI is inherently capital-intensive. Delivering its capabilities at scale requires massive investment in compute, data centers, custom silicon, networking, cooling systems, and critically, power generation. Value creation is migrating down the stack toward hardware and infrastructure, fundamentally altering the economics of growth and requiring broader industrial participation to deliver results.

The second shift is the move away from peak globalization toward trade rebalancing and U.S. reshoring. After decades of optimizing cost efficiency, corporations and policymakers are prioritizing resilience, supply chain security, and domestic capacity. Rebuilding manufacturing and strategic industries at home demands sustained investment in factories, automation, energy infrastructure, electrical systems, transportation networks, and skilled labor. This reshoring cycle reinforces AI’s infrastructure demands, creating what could be a multi-year capital expenditure cycle centered on tangible assets rather than intangible scale.

The investment implications, in our view, are significant. Many traditional ‘quality investing’ frameworks — emphasizing high historical margins, strong returns on incremental capital, and durable competitive moats — disproportionately benefited from the software-dominated, globalization era. If AI compresses service-sector advantages and increases capital intensity across technology leaders, backward-looking profitability metrics may become less predictive for a not-insignificant period of time. The so-called MAG-7, long beneficiaries of asset-light scalability, may face a different operating environment marked by heavier capital investment and structurally higher reinvestment needs – dynamics that may not be fully reflected in current valuations.

Meanwhile, the rise of passive investing and market-cap-weighted allocation algorithms has amplified concentration and valuation premiums over the past two decades. As capital cycles shift toward infrastructure, energy, industrials, and other real-asset exposures, participation may widen beyond a narrow group of mega-cap leaders. The next phase may reward adaptability and capital discipline over historical measures of scale and margin dominance.

In periods of structural transition like this, momentum and trend-following investing frameworks can provide a valuable complement to traditional growth and quality exposures. When leadership is shifting and valuation/fundamental anchors become less reliable, price trends often reflect underlying business improvement and shifting fundamentals before backward-looking metrics. A disciplined momentum approach does not require predicting which sectors “should” win – it responds to where capital is actually moving.

In an environment defined by regime change rather than incremental evolution, systematic exposure to strength and avoidance of persistent weakness can help investors navigate uncertainty while the new market structure reveals itself.

Travis Prentice
Chief Investment Officer, Portfolio Manager

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