Investors Urged to Balance AI Exposure Against Reversal
Liontrust's Mark Hawtin argues the AI trade, which drives about 42% of global market value, needs balanced portfolios for when it turns.
Updated on Nov. 3, 2026 in Artificial Intelligence
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Mark Hawtin, head of the Liontrust global equities team, recommends a barbell approach to investing in artificial intelligence, balancing AI exposure against holdings outside the trade. The views are analytical commentary on current market concentration, not a shipped product or a forecast with a fixed date.
Why it matters
Market value is concentrated in a small set of large technology companies, with the largest tech firms accounting for around 42% of global market value. Hawtin argues the AI capital spending cycle is strong enough to override other market cross-currents, which is why portfolio construction now hinges on how exposure to that cycle is balanced.
The evidence is market-composition data cited by an investment analyst, comparing today's concentration of value in the largest tech companies (around 42% of global market value) with Japan's 44% weight in 1989, the TMT sector's 41% in 2000, and the Nifty Fifty's 40% in the early 1970s. Hawtin's analysis does not resolve how long the current concentration will last or what will trigger a reversal.
The players
Liontrust
A UK-based investment manager whose global equities team Mark Hawtin leads.
Mark Hawtin
Head of the Liontrust global equities team, who recommends a barbell approach to AI investing.
The details
Hawtin recommends owning undervalued companies in healthcare and industrials outside AI, and businesses that use AI to gain productivity rather than those building it. He identifies four indicators for monitoring the AI trade: hyperscaler capital spending guidance, lead times and pricing at supply bottlenecks, financing conditions for AI-related debt, and monetization of the AI application layer. He also cautions that a sector label is not diversification, since many industrials and utilities act as proxies for AI capital spending.
Timeline
November 3, 2026: The core event date for Hawtin's barbell recommendation.
The Tech Race
Current market concentration in large technology companies, at around 42% of global value, sits alongside earlier episodes in which a narrow group of firms or sectors dominated: the Nifty Fifty at 40% in the early 1970s and the TMT sector at 41% in 2000. Hawtin's barbell argument positions investors to respond to a possible reversal of that pattern rather than to predict its timing.
Investors holding broad index exposure are directly affected, since concentration in large tech firms shapes index returns. Hawtin's suggestions point to healthcare and industrial holdings and to the S&P 500 Equal Weight, non-US equities, and mid and small caps as alternatives if the AI trade pauses; no timeline for such a shift is given.
The takeaway
Watch the four indicators Hawtin names: hyperscaler capital spending guidance, pricing and lead times at supply bottlenecks, financing conditions for AI debt, and monetization of AI applications. Each is a measurable signal of whether the AI capital cycle is strengthening or flattening.
Further reading
For broader context on where AI investment and capability are heading, see the Artificial Intelligence section.
Source note: This article includes information reported by Portfolio Adviser.
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