Global Equity Funds in Concentrated / AI-Driven Markets
Updated: Jun 9
Global equity fund selection has become more difficult in a market where a small number of mega-cap, AI-linked companies have carried a large share of benchmark returns. For allocators, the issue is no longer simply whether active global equity can outperform passive exposure. The more useful question is whether each fund has a clear portfolio role, a credible source of differentiation and evidence that its active risk is intentional rather than accidental.
This piece explores how concentrated market leadership changes the governance challenge for global equity fund selection. It looks at the distinction between skill and benchmark participation, why underperformance is not always failure, where active funds may duplicate existing exposure, and what investment committees may need to monitor if market leadership broadens or reverses.
Active value or expensive mega-cap beta?
Global equity fund selection has become a more awkward governance exercise.
Not because global equity is new. Not because active versus passive is a new debate. And not because allocators have forgotten how to assess a manager.
The issue is more specific.
A small number of mega-cap companies have become unusually important to global equity returns. Many are linked, directly or indirectly, to artificial intelligence, cloud infrastructure, semiconductors, digital advertising, platform economics or the broader capital-spending cycle around technology. That does not make them poor investments, nor does it make them automatically attractive. It does, however, make the fund-selection question harder to answer cleanly.
When a global equity fund has performed well, how much came from manager skill and how much came from owning the same mega-cap winners as the benchmark?
When a fund has lagged, is that evidence of manager failure, or evidence that the manager is genuinely doing something different?
And when a supposedly active fund carries a materially higher cost than passive exposure but behaves in a similar way to the index, what is the governance case for retaining it?
The useful question is not simply whether active global equity can work. It is whether each global equity fund in a portfolio has a clearly defined role, a credible source of differentiation and a monitoring framework that reflects the market environment we are actually in.
The passive hurdle has changed
The hurdle for active global equity managers has always been demanding. Broad global indices are cheap, liquid, transparent and difficult to beat consistently. That is not new.
What has changed is the shape of the benchmark.
In a more concentrated market, passive global equity exposure is no longer just broad exposure to global corporate earnings. It is increasingly shaped by a relatively small group of dominant companies, many of which share overlapping sensitivities: US large-cap growth, technology infrastructure, AI capital expenditure, platform scale, advertising cycles, semiconductor demand and valuation sensitivity to long-duration earnings.
This gives the benchmark a more distinctive risk profile than many investors instinctively assume.
For an allocator, the passive option is not neutral. It carries a particular set of exposures. The active fund has to be judged against that reality, not against a theoretical version of global equity that is evenly spread across countries, sectors and styles.
A global equity manager who avoids the largest AI-linked winners may look poor against the index for a period. That does not automatically mean the manager is wrong. It may mean the fund is performing the diversifying role it was selected to perform.
Equally, a manager who owns the same dominant names as the benchmark may look strong. That does not automatically prove stock-picking edge. It may simply show participation in the same market leadership that passive exposure already provided at a lower cost.
This is where active global equity research has to move beyond headline performance.
Start with the role, not the return
A global equity fund cannot be assessed properly without first defining what job it is meant to do.
That sounds obvious, but it is often where fund lists become blurred. Many global equity funds are selected because they are “good funds” rather than because they perform a specific portfolio function.
The role could be a core compounder: a fund designed to provide broad global equity exposure through high-quality companies with resilient earnings, strong balance sheets and disciplined capital allocation.
It could be benchmark-aware active exposure: a fund that accepts the broad structure of the index but seeks incremental value through stock selection, valuation discipline and risk control.
It could be a differentiated stock-selection engine: a fund that is expected to look materially different from the index, with a higher tolerance for tracking error and periods of discomfort.
It could be a value diversifier: a strategy deliberately designed to reduce dependence on mega-cap growth leadership and provide exposure to companies whose valuation, cyclicality or recovery profile sits outside the dominant market narrative.
It could be a quality growth allocation, a thematic growth sleeve, a global small and mid-cap complement, or a more defensive equity strategy with downside-awareness built into the process.
None of these roles is inherently better. The point is whether the role is explicit, evidenced and monitored consistently.
A fund intended to act as a differentiated value diversifier should not be judged in the same way as a benchmark-aware global equity fund. A concentrated quality growth strategy should not be expected to behave like a low-tracking-error global core fund. A thematic AI beneficiary fund should not be treated as generic global equity exposure.
The governance problem is not underperformance by itself. It is unclear expectations.
Concentration changes the meaning of “active”
Active share still has a place in fund research, but it is not enough.
A fund can have high active share and still carry concentrated exposure to the same broad risk drivers as the benchmark. It may own different companies, but remain exposed to the same macro and factor sensitivities: US growth, technology earnings, AI capex, long-duration cash flows or premium valuations.
The better question is: active against what risk?
A genuinely active global equity fund should be assessed not only by how many names differ from the benchmark, but by the type of risk it is taking. Is the fund underweight mega-cap technology because the manager has a valuation discipline, a different opportunity set, or a structural blind spot? Is it overweight AI beneficiaries because the manager has a differentiated understanding of the earnings pathway, or because benchmark pressure has pulled the portfolio closer to consensus? Is the fund’s tracking error coming from stock selection, style, sector positioning, factor exposure, country weightings or a small number of high-conviction names?
This distinction is important because active risk can be useful or accidental.
Useful active risk is intentional, explainable and connected to the manager’s stated edge. Accidental active risk is harder to defend. It can arise when a manager drifts into exposures that were not part of the original selection rationale, or when a fund’s portfolio construction changes quietly because the market environment has become uncomfortable.
For investment committees, the question is not simply whether a fund is active. It is whether the active risk is the risk the committee thought it was taking.
Underperformance is not always failure
In concentrated markets, some active managers will lag for defensible reasons.
A valuation-disciplined global equity manager may avoid companies where the share price appears to discount a very demanding earnings path. A quality manager may hold strong businesses but not the highest-momentum names. A value manager may own companies whose fundamentals are improving but whose share prices remain unfashionable. A genuinely benchmark-agnostic stock picker may be structurally underweight the largest index constituents because the best ideas are found elsewhere.
That kind of underperformance can be uncomfortable, but it may still be consistent with the mandate.
The issue is evidence.
If a fund is underperforming because it is staying true to a clearly articulated process, the research question becomes whether the process remains credible, whether the portfolio is behaving as expected, and whether the original role still makes sense in the wider portfolio.
If a fund is underperforming because the manager has misread fundamentals, failed to control downside risk, drifted away from the stated philosophy, or become trapped in stale positions, the conclusion may be different.
The distinction matters.
Fund research should not reward managers for looking different regardless of outcome. Nor should it punish every period of underperformance as if markets always validate skill quickly. The better approach is to test whether the performance pattern makes sense.
Does the underperformance align with stated style exposure?
Has the manager explained the drivers clearly?
Are stock-level decisions consistent with the process?
Has the team added to, trimmed or exited positions in a way that demonstrates discipline?
Is the portfolio still doing the job it was selected to do?
Underperformance is not automatically a reason to lose confidence. But unexplained underperformance, process inconsistency and weak decision evidence are different matters.
Outperformance is not always skill
The reverse is equally important.
In an AI-driven, mega-cap-led market, a global equity fund can outperform for reasons that are less impressive than the headline suggests.
It may have owned a small number of dominant benchmark names. It may have benefited from multiple expansion in companies already heavily represented in passive global equity. It may have carried more growth, momentum or technology exposure than the fund label suggested. It may have drifted into a narrower opportunity set because that is where near-term performance pressure was strongest.
The return still matters. But the attribution work matters more.
A strong period of performance should be broken down into its components.
Was the outcome driven by stock selection across a broad range of holdings, or by a small number of mega-cap winners?
Was it achieved with lower, similar or higher concentration than the benchmark?
Did the manager add value outside the obvious AI beneficiaries?
Did the fund preserve its sell discipline as valuations rose?
Did it remain consistent with the stated process, or did the process become more flexible at precisely the point when discipline was most needed?
For global equity funds, the most dangerous phrase may be “it has worked”.
Worked how?
Because of what?
At what valuation?
With what overlap to existing exposure?
And what would make the outcome less repeatable from here?
That is not scepticism for its own sake. It is basic governance in a market where the same narrow set of companies can explain a large share of benchmark and active fund returns.
Where a global equity fund may not fit
A global equity fund may be credible in isolation and still be a poor fit for a particular portfolio structure.
The most obvious issue is duplication. Many portfolios already have substantial exposure to global developed equity, US equity, growth equity, technology, passive index funds, or multi-asset funds with embedded mega-cap holdings. Adding another global equity fund that owns similar companies for similar reasons may not improve diversification. It may simply add another layer of cost and complexity.
Another issue is expensive beta. A fund that hugs the benchmark, owns many of the same top names, generates limited differentiated stock selection and charges materially more than passive exposure may face a high governance hurdle. That does not mean benchmark-aware funds have no role. It means the evidence for active value has to be clear.
There is also the problem of hidden thematic exposure. Some global equity funds may not be labelled as AI funds, technology funds or growth funds, but their return pattern may be increasingly tied to the same underlying drivers. That can be acceptable where it is intentional and understood. It is harder to defend where the exposure is discovered only after a drawdown.
Finally, there is the risk of style confusion. A fund selected as a quality compounder may become more valuation-insensitive. A value fund may drift into lower-quality cyclicality. A growth fund may become dependent on a narrow group of mega-cap names. A core fund may become a closet thematic allocation.
The label is not the control. The portfolio is.
Failure points to monitor
For committees and fund selectors, the key failure points are not difficult to name. They are difficult to monitor consistently.
The first is benchmark creep. This occurs when a manager gradually moves closer to the index, often in response to performance pressure. It can reduce career risk for the manager, but it weakens the case for paying active fees.
The second is valuation drift. This is particularly relevant in AI-driven markets. A manager may begin with a clear valuation discipline but become increasingly willing to accept demanding assumptions because the strongest companies keep performing. The question is not whether high-quality companies can justify premium valuations. Sometimes they can. The question is whether the valuation framework is still being applied with discipline.
The third is style inconsistency. A fund does not have to be rigid, but it does need a coherent philosophy. If the sources of return change materially over time, the monitoring framework has to recognise that.
The fourth is concentration without accountability. Concentrated funds can be attractive when the manager has genuine insight, strong research depth and disciplined position sizing. But concentration also raises the cost of being wrong. The research process should explain not only why the best ideas are owned, but how position sizes are governed, challenged and reviewed.
The fifth is weak attribution. In the current environment, broad explanations are not enough. “Stock selection was positive” is less useful than knowing which stocks mattered, why they mattered, whether the outcome was repeatable, and whether it came from the intended source of edge.
What to monitor when leadership changes
Global equity leadership will not remain static forever. It rarely does.
The next phase may still reward mega-cap AI beneficiaries. It may broaden into the wider supply chain. It may rotate toward companies using AI effectively rather than building the infrastructure. It may favour value, smaller companies, non-US markets, cyclicals, defensives or quality compounders with less demanding valuations. It may also involve more volatility if earnings expectations, capital spending assumptions or discount rates are challenged.
The aim is not to predict the rotation. It is to know what each fund is expected to do if leadership changes.
A benchmark-aware fund may be expected to participate but not fully protect. A value diversifier may continue to lag until leadership broadens. A quality growth fund may remain resilient if earnings delivery stays strong, but may be vulnerable if valuations compress. A thematic AI fund may require a more explicit view on the durability of the AI investment cycle. A concentrated stock picker may require deeper stock-level scrutiny because the range of outcomes can be wider.
Monitoring should therefore focus on role, exposure and behaviour.
What is the fund’s exposure to the largest index names?
How much of the return depends on AI-linked earnings assumptions?
What is the overlap with passive global equity and other portfolio holdings?
Is active risk intentional and consistent with the mandate?
Does the manager’s behaviour still match the stated philosophy?
What would have to happen for the original investment case to weaken?
These questions are more useful than asking whether active or passive is “better” in the abstract.
The allocator’s judgement
The case for active global equity has not disappeared. But the burden of proof has changed.
In a concentrated, AI-driven market, active managers have to earn their place through role clarity, differentiated insight, disciplined portfolio construction and evidence that their active risk is intentional. Passive exposure remains a powerful comparator, but it is not a neutral reference point. It brings its own concentration, style and valuation characteristics.
This is the central governance issue.
A global equity fund does not need to beat the benchmark every quarter to be useful. It does need a clear reason to exist in the portfolio. It should either provide credible active stock selection, a distinct exposure not already captured elsewhere, a better-controlled version of global equity risk, or a diversifying return pattern that the committee is prepared to tolerate when it is out of favour.
The weakest position is not owning an active fund that looks different and sometimes lags. The weakest position is owning an active fund without being able to explain what it is meant to do, what risk it is taking, why it costs more than passive exposure, and what evidence would change the view.
In concentrated markets, fund selection becomes less about finding the manager with the best recent performance and more about understanding the source of return.
That is where active global equity research still matters.
Not as a slogan.
Not as a defence of active management for its own sake.
But as a governance exercise: what role does the fund play, what evidence supports it, and is the portfolio better understood because it is there?
Suggested due-diligence questions
What role does the fund play versus passive global equity exposure?
How much of the portfolio is exposed to the largest index constituents and AI-linked beneficiaries?
Is active share supported by genuine active risk, or mainly by different names with similar factor exposure?
What has driven recent relative performance: stock selection, style, sector, country, valuation, concentration or benchmark positioning?
Where has the fund added value outside the dominant mega-cap technology complex?
How does the manager define valuation discipline in companies with unusually strong growth prospects?
What would cause the manager to reduce exposure to a winning position?
How has the fund behaved during periods when market leadership broadened or reversed?
What portfolio exposure would this fund duplicate if added alongside existing global, US, technology or multi-asset holdings?
What evidence would weaken confidence in the fund’s role, process or repeatability?
Professional-use and risk note
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