The JSE has delivered one of the best dollar returns in global equity markets this year, yet headlines stay focused on US mega-cap AI stocks. Do South African investors stick with a local market, finally rewarding patience, or pay up for the global AI leaders and risk buying into a bubble?
That’s the wrong question. AI is a technological revolution, but for investors it remains a classic capital cycle: the real question is which parts of the AI value chain you back, and at what price.
The capital cycle is straightforward. Strong returns attract capital. Capital funds new capacity. Excess capacity crushes returns. Capacity is written off or consolidated. Survivors eventually earn decent returns again.
Bubbles are that cycle on fast-forward. Narratives outrun information. Capital chases stories faster than data can catch up. Three questions position AI in this cycle.
Some cycles are driven by real technological change: steam, electricity, rail, semiconductors, the internet — and, plausibly, AI. Others are driven mainly by re-rating existing assets: think Japanese land in the 1980s or US housing in the 2000s. Plenty of leverage; not much new productivity.
Evolving picture
AI sits closer to genuine technological change than to a credit boom — but we still have to ask how much of today’s price reflects future cash flows, and how much reflects a story about those cash flows.
Funding structure matters. When banks and households lever up to chase a boom, the hangover is long and ugly. Equity-funded bubbles are brutal for shareholders but usually leave the financial system intact.
Today’s AI build-out is still driven mainly by large, profitable tech firms deploying their own balance sheets and by equity investors. On the surface that makes this cycle less systemically dangerous than 2008.
But the picture is evolving. Big tech has shifted from sitting on oversized cash piles to issuing significant debt to fund capex. The hyperscalers are now spending between 21% and 35% of revenue on capital expenditure — higher than utilities and exceeding what AT&T spent at the height of the telecom bubble.
More concerning, late-cycle warning signs are appearing. Meta secured $27bn in financing with Blue Owl Capital for its Hyperion AI data centre — the largest private-credit deal ever. And circular deals are emerging, where infrastructure providers invest in customers who then spend heavily on their chips and cloud. These are clear late-cycle signs.
The final question: if this all goes wrong, what remains? The telecom capex boom of the late 1990s left fibre networks that outlived the companies that built them and underpinned future innovative business models. By contrast, the dot.com equity bubble left far less. The pattern is clear: infrastructure-heavy bubbles funded by debt may leave reusable assets. Narrative-driven equity bubbles often leave only painful lessons.
What will endure?
AI today looks more like dot.com equity than telecom debt: equity-funded, story-driven, with an asset base that is overwhelmingly intangible and hard to measure. Data centres age quickly; chips will be obsolete within a few years. What will endure is harder to value: organisational learning, regulatory frameworks, a workforce comfortable using AI tools, and new business models born of experimentation. Participants cannot know in real time whether they are funding the future or funding a mirage.
Viewed through the capital cycle, AI looks like a classic boom, just bigger and faster. We have moved past scarce compute and simple demos. We are deep into a capex surge: heavy investment in data centres, chips and AI talent. The narrative has shifted from “this might matter” to “you’re dead if you’re not all-in”, while many industries are still only experimenting at the edges. So we have late-cycle rhetoric on top of early-cycle adoption.
Valuations tell a similar story. Big tech trades at a premium to the market, but below prior bubble extremes. This looks more like an extended capex wave with growing use of debt than a full-blown mania — for now.
History is not kind to companies that sprint up the capex curve. Across thousands of stocks over six decades, firms aggressively expanding capital expenditures underperformed their conservative peers by more than 8% annually. The effect appears across sectors and regions — even in asset-light industries such as healthcare and consumer staples. For retirement savers, that means the biggest capex spenders are usually the worst long-term compounders to own.
The mechanism is straightforward: aggressive capex attracts competition, creates excess capacity and erodes pricing power. Even when the underlying technology proves transformative, the investors who funded the infrastructure rarely capture the value.
For investors, the AI boom is still, at heart, a capital-cycle story. For long-term investors, the goal is not to predict the day the music stops but to ensure you are not standing closest to the speakers when it does.
Apply the principles
For those stewarding South Africans’ retirement savings under Regulation 28, balancing local and offshore, growth and capital preservation, several principles follow.
First, don’t turn a capital cycle into a prediction contest. Accept that we are in an AI investment boom. Global indices are unusually concentrated in a handful of AI leaders, so a passive offshore allocation is effectively a leveraged bet on that narrow story. Assume some overbuild and a shake-out are likely. Tilt portfolios away from obvious AI proxies at peak valuations and towards businesses using AI to grow revenues, cut costs and widen margins.
Second, remember that the opportunity set is far wider than US mega-cap AI. A narrow segment can behave like a bubble while the rest trades at reasonable or attractive valuations. For a South African allocator, that includes smaller companies, value shares, and selected non-US markets left behind in the AI narrative but not in fundamentals.
For most South African retirement savers the 45% offshore allocation is the main route to AI exposure, but it is also the access point to all those other opportunities. The disciplined response is not to abandon offshore equity but to shift how you access it: moving from purely passive global trackers to more active strategies that can underweight the capex race and overweight the deployment beneficiaries and the unloved but reasonably valued parts of the market — accepting some tracking error as the cost of avoiding concentration risk.
For South African investors the AI story is also a currency story: AI booms and busts both have a habit of strengthening the dollar, and that can either soften or amplify the impact of offshore equity swings in rand terms.
A simple rule of thumb is this: we want AI to show up in the income statement, not just in the capex line or the valuation multiple. And we want portfolios where AI is a cheap embedded option on top of an already robust business, not the sole justification for the share price.
This is not an argument for chasing the latest theme or for sitting out the future. It is an argument for treating every boom as a capital-cycle problem rather than a prediction contest; for asking hard questions about capacity, returns, balance sheets and industry structure even when the story is intoxicating; and for staying humble about timing while uncompromising on business quality, cash flows and valuations.
The AI boom is another turn of an old wheel: capital rushing to fund a new promise, overshooting, then quietly laying the foundations of the next era.
The fundamental question — do AI investments generate cash returns that justify today’s valuations — is about to be tested. The capital cycle is turning from speculative capex toward the harder work of monetisation and deployment. The portfolios that recognise it will be the ones still compounding when the foam blows away — capturing the gains that show up in the income statement without paying bubble prices.
• Salaam is chief investment officer at Vunani Fund Managers.
Would you like to comment on this article?
Sign up (it's quick and free) or sign in now.
Please read our Comment Policy before commenting.