Artificial Intelligence: Perspectives from Across the Market

Written By: Peter Mustian, MBA and Brooklyn Seymour

Artificial intelligence (AI) has quickly become one of the most influential themes shaping global markets. Investment dollars are flowing rapidly, expectations are high, and claims about productivity and growth are widespread. For investors, this creates a familiar challenge: distinguishing a durable opportunity from near-term enthusiasm. To better understand how AI is being evaluated today, Innovest’s research team engaged in discussions with a group of best-in-class asset managers across strategies and asset classes. Through these discussions and ongoing conversations, we explored how managers are assessing AI’s impact on fundamentals, valuation, adoption, and risk. What follows is a summary of their perspectives and where views tend to converge or diverge. The overarching takeaway is clear: AI represents a meaningful structural force, but outcomes are likely to vary widely across companies, sectors, and market cycles.

From Infrastructure Spending to Economic Results

Across investment styles, managers consistently described the current phase of the AI cycle as one defined by heavy infrastructure investment. This includes substantial spending on semiconductors, data centers, cloud capacity, and supporting energy and networking assets. The scale of this build-out is real and unprecedented in many respects.

Where opinions begin to diverge is around the durability of returns on that investment. Several managers cautioned that capital intensity alone does not create value. If capacity grows faster than profitable demand, pricing pressure can emerge, and returns on capital may decline. As a result, enthusiasm around spending is being increasingly balanced by scrutiny of outcomes.

Managers emphasized a shift from “projects to process.” Early pilots, demonstrations, and announcements are no longer sufficient. Instead, they are looking for evidence that AI is being embedded into core business operations. The most important signals include sustained margin improvement, operating leverage, and improving returns on invested capital across multiple reporting periods. When AI adoption appears shallow or disconnected from economics, particularly if spending continues without measurable results, managers grow more cautious. As one noted, “markets are now demanding outcomes rather than announcements”.

Valuation Discipline Comes to the Forefront

Valuation discipline was one of the most consistent themes across our conversations. While nearly all managers view AI as a long-term growth driver, many believe parts of the market already reflect optimistic adoption assumptions. In those cases, the margin for error is thin. Any slowdown in execution or guidance can lead to multiple compressions.

In contrast, managers expressed greater confidence in companies where AI supports existing competitive advantages rather than serving as the sole investment thesis. These businesses often trade at more reasonable valuations and show clearer paths from technology investment to cash flow. Managers generally prefer this combination of innovation and valuation support to companies priced for near-perfect execution.

Looking ahead, managers expect greater dispersion across markets. Early enthusiasm lifted a broad group of AI-related companies, but the next phase is likely to separate exposure from execution. Clear winners should emerge among firms that translate AI spending into sustainable cash flow. At the same time, laggards may struggle as complexity, cost, and competition increase faster than returns.

This dispersion is expected to extend beyond equities. Managers see implications for credit markets through funding needs and spreads, for convertible securities as flexible capital for AI investment, for mergers and acquisitions as firms acquire capabilities rather than build them internally, and for volatility as correlations shift when expectations meet financial reality.

Risk Management and Patience

Despite differences in style, managers shared a common emphasis on risk control and patience. Most are avoiding binary positioning and instead taking a measured approach to participation. Rather than betting on narratives, they are monitoring clear, testable indicators such as AI-related returns on capital, margin and cash flow trends, and evidence that adoption is moving from pilot programs into core operations.

Diversification also remains central. Managers cautioned against allowing a single theme, no matter how compelling, to dominate portfolio risk. The prevailing mindset is not “all-in” or “all-out,” but thoughtful engagement guided by evidence and continuous reassessment.

A Balanced View of the Opportunity

Taken together, the perspectives we gathered suggest that AI is neither a speculative sideshow nor a guaranteed windfall. It is a structural force whose benefits will accrue unevenly and overtime. The key differentiator will not be who talks most convincingly about AI, but who converts investment into durable earnings at reasonable prices.

This reframes the core investor question. The issue is no longer whether AI will influence markets (it already has) but how those changes will be monetized, financed, and valued through the cycle. Markets will ultimately reconcile ambition with outcomes and narrative with numbers.

Consistent with the views shared by the managers we met with, the most effective approach favors evidence over slogans, patience over speed, and balance over concentration. In past technological shifts, the enduring winners were not those who resisted change nor those who embraced it blindly, but those who approached the shift with discipline. AI appears set to follow a similar path, rewarding investors who respect both its promise and its limits.