Where does the real investment opportunity in AI sit?
For many investors, the answer starts with a few familiar names. Nvidia. OpenAI. The companies building the models and chips everyone is talking about. EasyAssetManagement Chief Investment Officer Shaun Krom sees a much wider picture
His team looks across the full chain behind AI, from data centres and power systems to networking, specialist manufacturing and the businesses beginning to use the technology in ways that improve costs, speed and revenue.
In a conversation with Carel Nolte, Shaun explained where EasyAssetManagement is finding opportunities, how those ideas make it into a portfolio and what investors should watch as the AI market develops.
Before an AI tool can answer a question, a long chain of infrastructure needs to exist.
Someone has to build the data centre. Someone has to supply the power, install the cooling systems, connect the processors and move information between them quickly enough for the system to work.
That creates opportunities across:
EasyAssetManagement has invested across several parts of this chain, including companies involved in data-centre construction and advanced networking.
This is how the team approaches thematic investing. It starts by asking where money is likely to flow, then looks for the businesses best placed to receive it.
AI is currently a significant part of the Global Portfolio, alongside technology-enabled defence, industrialisation and financial services. These themes often overlap.
The same specialist manufacturer may supply parts for an AI data centre, a defence system or a space programme. The same power infrastructure may support factories, military facilities and large computing projects.
The opportunity rarely sits in one neat category.
Finding a growing industry is only the start.
Once the team identifies a theme worth exploring, it studies the individual businesses within it. That means looking at their balance sheets, margins, revenue growth, competitive advantages, management teams and position in the wider supply chain.
Two companies can be exposed to the same AI trend and produce completely different results.
One may have stronger margins. Another may carry too much debt. One could operate in a part of the supply chain where demand is rising quickly, while another faces tougher competition or falling prices.
Management matters too, especially when a share comes under pressure. A proven leadership team can give investors more confidence that the original investment case still holds when the market turns against it.
That is why EasyAssetManagement does not simply buy every company linked to AI. The team is trying to find where the strongest economics sit.
A good investment idea can still have little effect on a portfolio when the position is too small.
Portfolio managers must decide how much conviction each idea deserves.
EasyAssetManagement’s funds operate within regulatory and product limits. Within those limits, the team decides whether a company receives a small allocation, a larger allocation or no allocation at all.
Shaun believes the team’s streamlined structure helps it move faster and avoid some of the groupthink that can emerge in large investment committees.
That can produce a portfolio that looks different from the wider market. It creates room for stronger returns when the team is right, while making mistakes more expensive when it is wrong.
This is one reason an actively managed AI portfolio may look more concentrated than a broad AI basket. The aim is to give the strongest ideas enough weight to matter.
So far, much of the money spent on AI has flowed towards the businesses supplying the infrastructure.
Companies have bought chips, built data centres and increased their spending on computing. The suppliers receiving that money have often seen the clearest benefit.
The next stage is about the companies paying for the technology.
Can they use AI to reduce costs, work faster, improve margins or create new revenue?
The early phase involved plenty of experimentation. Shaun described it as “token maxing”, where businesses spent heavily before identifying which uses were worth paying for.
That is beginning to change.
One logistics business discussed in the webinar used to take several days to prepare a customer quote. Employees had to check vehicle availability, work through spreadsheets and confirm whether the job could be completed profitably.
AI reduced that process to seconds.
That kind of result is easier to measure. The value appears in faster service, lower operating costs and the ability to handle more business without adding the same number of people.
For investors, this may be one of the most useful parts of the AI story to watch.
AI-related shares rose strongly before coming under pressure.
Shaun pointed to several reasons:
He does not see the sell-off as proof that the wider AI investment case has ended.
Cheaper models could hurt some developers. They could also make AI available to more businesses.
When technology becomes cheaper, usage often increases. That could support continued demand for chips, data centres, networking and electricity, even if the companies capturing the largest share of the value change.
The opportunity may remain while moving from one part of the AI chain to another.
That is why investors need to understand what a company actually does within the system, rather than relying on an AI label.
EasyAssetManagement’s AI exposure does not sit in isolation.
The portfolio also invests in technology-enabled defence and industrialisation, where many of the same capabilities matter.
Modern defence systems require advanced computing, lasers, drones, batteries, specialist materials and precise manufacturing. The rebuilding of manufacturing capacity in the United States also creates demand for infrastructure, power, construction and finance.
Someone still needs to fund those projects. This helps explain the portfolio’s exposure to financial businesses such as Goldman Sachs.
The common thread is capital flowing towards new infrastructure and technology.
AI may be one of the strongest forces behind that spending, but it forms part of a wider shift in how countries build, produce and protect what they need.
Shaun sees South Africa as a difficult market, particularly because fewer local companies sit directly inside the global AI and industrial technology chain.
There are still areas where South African businesses could benefit.
Resources remain one of them. More data centres, power infrastructure and manufacturing require metals and materials. South African producers could help supply that demand.
Shaun also highlighted local companies growing through strong execution:
These businesses operate in different sectors, but the question behind them is the same: can this company grow under the conditions it faces today?
That matters more than waiting for the entire South African economy to improve.
The webinar offers a practical way to think about AI and other investment themes.
Start with the wider change, then move closer to the company.
Ask:
These questions help separate an exciting story from a considered investment case.
AI may continue to reshape industries, but the companies benefiting most could change as the technology matures. The useful work is understanding where the value sits now, where it may move next and what evidence would change your mind. If you would like to learn more about the EasyETFs under EasyAssetManagement, click here.
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