The growing influence of artificial intelligence (AI) across global equity markets is making portfolio diversification increasingly difficult, prompting investors to reconsider how they manage concentration risk and identify differentiated sources of returns.

According to Nelson Yu, senior vice president and head of equities at AllianceBernstein (AB), the combination of AI-driven market disruption and persistently higher interest rates is strengthening the case for quality companies, value stocks and regional diversification.

Global equities gained 1.6% in the third quarter of 2026, as measured by the MSCI All Country World Index, with Japanese equities and US large-caps leading the advance. Market leadership also broadened beyond technology – the same index rose 3.8% during the quarter and 16.1% year to date, supported by strong performance from energy, healthcare and materials stocks.

However, beneath these gains, AI is fundamentally changing how different stocks and sectors behave.

AI reshapes correlations

Yu believes enthusiasm over AI infrastructure spending is increasingly shifting towards greater scrutiny over whether those investments can generate sustainable profits.

“The distinction between investment speculation and tangible productivity benefits will be critical for identifying business models that can create durable value from AI,” he said.

AB’s research highlights how AI-related companies are becoming more interconnected, potentially undermining traditional approaches to diversification.

For example, its analysis identified 68 stocks across 15 industries exhibiting similar trading patterns in December 2023. Since then, the cluster has expanded, with AI-linked stocks now displaying more than twice the volatility of the broader market.

Yet not all AI-related companies behave alike. Software businesses, Asian semiconductor producers and large consumer technology platforms have developed different trading patterns.

“These patterns suggest AI exposure now encompasses several distinct investment drivers, creating both concentration risks and opportunities to diversify globally,” Yu added.

Opportunities beyond the AI trade

AB’s research suggests US and emerging Asian equities have become increasingly correlated with AI-related stocks over the past two years.

In contrast, European, Japanese and other emerging market equities exhibit lower correlations, potentially offering alternative sources of returns. Value stocks also present opportunities in industries relatively insulated from AI disruption, including agriculture and aircraft manufacturing.

Meanwhile, smaller companies could benefit from AI-driven productivity improvements without assuming the same concentration risks as large technology businesses.

Yu also identifies opportunities in European industrials and financials, alongside healthcare, energy and chemicals.

Higher rates favour quality

Rising borrowing costs are adding another dimension to equity selection.

Global government bond yields approached 4% by quarter-end, their highest level since 2007, increasing pressure on corporate valuations and future earnings.

AB believes that type of environment favours businesses with strong balance sheets, recurring revenues and sustainable free cash flow. Such companies have greater flexibility to invest, reward shareholders and withstand economic uncertainty.

The asset manager also advocates combining higher-risk AI beneficiaries with defensive equity strategies to manage volatility.

“We believe long-term investment success now hinges on finding attractively valued companies that can benefit from developments in AI while staying relatively insulated from crowded and risky AI trades,” said Yu. “Diversification may be getting harder to find, but that only makes it more valuable.”