From earnings acceleration to earnings durability
Rosie Malcolm, portfolio manager, Fidelity International, comments: “After an exceptional AI-driven earnings cycle in 2026, the investment debate is shifting to the sustainability of returns, the durability of demand and the economics of AI. Are the returns sufficient given the investment required, and where across the value chain will profits ultimately accrue?
“Global equities returned around 13% year to date to the end of September. While next-12-month consensus earnings estimates rose approximately 30%, the market multiple compressed from around 19 times to 16 times. Much of that earnings acceleration has been driven by the AI cycle.
“The speed of change in market leadership illustrates just how non-linear the AI cycle has been. Micron, Samsung Electronics and SK Hynix have all moved into the top ten contributors to global index returns in 2026, yet some of these businesses were generating negative gross margins as recently as 2023. As a result, they would not have appeared in many conventional investment screens before their recent moves, leaving a number of equity strategies offside as the cycle turned. In our view, in a rapidly evolving market, the ability to identify inflection points, rather than simply extrapolate history, is increasingly valuable. This is an environment in which we believe fundamental research becomes more important, as detailed analyst insights can help identify those inflection points and challenge the assumptions embedded in market expectations.
“An important component of the earnings-driven growth we’ve seen is that it has been driven in part by a transfer of cash from hyperscaler balance sheets and free cash flow into the earnings of AI hardware companies, particularly memory. The lower market multiple we now see suggests investors recognise that this balance sheet transfer is unlikely to be sustainable over the long term. The question from here is how durable those earnings prove to be and how sustainable the sources of funding behind them are.
“We remain constructive on global equities into 2027, but the risks around earnings expectations are higher than they were a year ago. The market continues to expect above-cycle earnings growth, but interest rates are higher, inflation remains above target for many central banks, geopolitical uncertainty persists and US consumer sentiment is at multi-decade lows. At the same time, the largest companies are starting from a less flexible balance-sheet and free-cash-flow position following significant investment and greater use of both equity and debt markets.
“We do not see those funding sources as exhausted, and importantly, the evidence on AI adoption remains positive. The next phase of the AI cycle, however, increasingly needs to be supported by monetisation. The market is watching recurring revenues at private AI companies and hyperscaler cloud growth, while companies more broadly are increasingly identifying new applications across areas including pharmaceutical and biotech research and cybersecurity. So far, the signals remain encouraging, but ultimately the scale of investment needs to be matched by growing adoption from enterprises and consumers.
“As we move into 2027 and look for confirmation of the durability of earnings, the market is going to be looking for evidence about 2028. Many companies, particularly across the AI supply chain, have already sold their 2027 capacity, which means the potential for earnings beats on the scale seen in 2026 is lower. The more interesting question is therefore likely to be one of duration: can companies demonstrate that this cycle extends into 2028 and beyond? Further evidence of that durability could support a rerating in valuations even if the rate of earnings-per-share growth begins to moderate for some of the current beneficiaries.
“One of the other major investment questions is where the profits ultimately lie as the AI value chain evolves. We are looking across the whole market, including hardware, large language models, cloud providers, the industrial companies building data centres and providing their power and cooling, software, cybersecurity and the consultants helping enterprises build AI capabilities.
“Technology delivery itself is also evolving because we keep crashing into the laws of physics. This is forcing a rethink of how data centres are constructed, with the move towards optical technology as one example. Solving those constraints is itself creating new investment opportunities.
“At the same time, we do not think we are close to understanding all of AI’s use cases, and we have barely begun optimising the AI stack. Greater efficiency could ultimately change how much infrastructure is required.
“Against this backdrop, managing investments through this dynamic environment comes back to balancing return and risk, while positioning for a range of potential outcomes. For instance, if the returns do not justify the spending, we would expect to see hyperscalers pull back on capital expenditure. In that case, they could experience a significant increase in free cash flow as they begin leveraging the investments already made. Highly leveraged neoclouds could face a much more difficult outcome. We are also asking where the credit exposure sits if the AI cycle were to unravel, and where capital would rotate in that scenario. This is one reason we continue to value attractive opportunities that are not dependent on AI.”
The Bull Case for Global Small and Mid-Caps Remains Intact, but Risks Are Building
Maroun Younes, portfolio manager, Fidelity International, comments: “The foundation of the global equity bull market remains earnings growth. Corporate profitability has continued to expand and forward earnings expectations remain supportive across major markets. Importantly, a significant portion of recent equity appreciation has been accompanied by rising earnings rather than being driven exclusively by multiple expansion. As long as profits continue to compound, equities retain a fundamental anchor. The principal risk would therefore be a transition from slowing earnings growth to outright earnings deterioration; there is little evidence of that at present.
“The most important structural engine behind that earnings strength is AI and the increasingly broad physical ecosystem required to support it. This is no longer simply a semiconductor or software story. The build-out encompasses data centres, electrical generation and transmission, cooling systems, networking equipment, industrial infrastructure and the enormous quantities of capital required to finance them. AI investment has therefore become both an important contributor to corporate earnings and a meaningful source of real economic activity.
“The complication is inflation. Price pressures remain above central-bank objectives across much of the developed world, while higher energy prices, persistent fiscal deficits and elevated sovereign borrowing requirements all threaten to keep the nominal environment firmer than markets became accustomed to during the post-GFC era. Meanwhile, the sheer scale of AI-related investment is intensifying demand for electricity, infrastructure, equipment and capital.
“This makes interest rates the key macroeconomic risk to the bull market. Equities can perform well alongside elevated yields when nominal growth and earnings are sufficiently strong. The danger comes when restrictive rates begin to impair economic activity, weaken profits, increase refinancing stress and widen credit spreads. On that measure, the warning lights are not yet flashing red. US high-yield spreads remain consistent with relatively contained aggregate credit stress, while earnings expectations remain positive.
“A second vulnerability is narrow market leadership. Recent index gains have increasingly depended on a relatively small group of large companies, while participation underneath the headline indices has deteriorated. Historically, weakening breadth has often accompanied mature bull markets and major market peaks, making broader participation desirable for the durability of the advance.
“The bull market should therefore be regarded as maturing and displaying several late-cycle characteristics. Elevated concentration, greater sensitivity to bond yields, geopolitical and inflation uncertainty, and increasing dispersion between winners and losers all argue for more volatility and a less forgiving investment environment.
“The resulting investment regime is best described as constructive, but not indiscriminate. Equities can continue to perform while earnings remain supportive, but investors should expect greater volatility and choppier index-level returns as the cycle matures. In this environment, generating returns is likely to become less about broad market exposure and more about identifying businesses capable of delivering through a mixed macroeconomic backdrop. As the macro picture becomes less clear-cut, investors can no longer rely on economic tailwinds alone and should increasingly favour companies with demonstrable earnings delivery, strong free cash flow generation and robust balance sheets.
“We remain constructive on AI, particularly given the absence of any meaningful slowdown in associated activity. However, the market has become far more selective and is demanding greater certainty around funding, profitability and execution. The phase where virtually any AI-related exposure was rewarded appears to have passed. Importantly, the opportunity set extends well beyond semiconductors and software. The AI investment cycle continues to drive demand across power generation, grid infrastructure, industrial equipment, data-centre construction, cooling systems and financing, creating attractive opportunities throughout the broader value chain, often at more reasonable valuations than the most crowded areas of the market.
“At the same time, we are finding opportunities in areas that have been categorised as potential AI losers. In some cases, concerns around disruption are justified. In others, the market may be overstating the threat or underestimating the capacity of high-quality businesses to adapt and innovate. Not all business models will be impacted equally, and periods of disruption often create valuation dislocations that can be exploited selectively. Maintaining exposure to AI does not preclude identifying opportunities among businesses that the market may have prematurely written off.
“More broadly, we see increasing value in idiosyncratic opportunities where businesses can create shareholder value through company-specific drivers rather than simply benefiting from favourable macroeconomic conditions. Spin-offs, under-researched companies, businesses with strong balance sheets and attractive free cash flow characteristics, and companies benefiting from long-term structural themes can all offer compelling return potential independent of the broader economic cycle. This reinforces the importance of disciplined stock selection as markets become more differentiated.
“The critical signposts are now earnings breadth, market breadth, bond yields and credit spreads. So long as profits remain healthy and credit conditions remain orderly, the bull case survives. A deterioration across those indicators would represent a materially more serious warning that the cycle is approaching exhaustion. Until then, the regime remains constructive, but increasingly rewards selectivity, quality and disciplined stock picking over indiscriminate exposure.”
