A fresh take on AI investing is hitting the JSE.

As the AI space matures, the real question isn’t whether to invest in AI,  it’s how to do it intelligently.

In a recent conversation, Ivy Asset Management CEO Bruce Main offered a more structured way to think about this. And beyond the launch itself, several ideas stood out as particularly useful for investors.

Here are 6 key takeaways from the webinar. 

1. Treat AI as an entire ecosystem

“AI is an ecosystem… that includes energy, data, software, security, and hardware.”

A central theme from the discussion was the idea that AI should not be viewed as a single sector.

The conversation recognises AI as a deep, interconnected system - where applications rely on infrastructure, and innovation depends on everything working together behind the scenes.

For investors, that means moving beyond picking a few obvious names and towards understanding how value flows across the entire AI stack.

2. It focuses on where AI is actually driving potential profits

“We’ve gone to what we call the sixth dimension — companies using AI to improve margins and (potential) profitability.”

The webinar also highlighted a distinction between companies building AI and those applying it.

The conversation also includes businesses that are using AI to improve efficiency and profitability.

That distinction matters. Because over time, the biggest winners may not just be those building AI, but those applying it best in the real economy.

3. AI exposure can't be ignored

“Whether you’re conservative or aggressive… to not hold this asset class is a major mistake.”

• More aggressive portfolios might allocate 10–15%
• More conservative portfolios might hold closer to 2.5%

So the debate isn’t whether to include AI - it’s how much exposure is appropriate for your risk profile.

4. In a fast-moving space, static exposure can become outdated quickly

While not stated as a single line, this idea underpins the case for active management throughout the conversation.

AI is evolving at a pace where:

• New leaders emerge quickly
• Bottlenecks shift across the value chain
• Early winners don’t always stay dominant

A traditional index-tracking approach may struggle to keep up.

In this context, an actively managed structure allows for adjustments over time -  both in terms of company selection and where exposure is concentrated within the broader ecosystem.

5. Invest in parts of AI most people aren’t even thinking about yet

“The bottlenecks… are coming into energy, security, and other areas that there’s not that much knowledge about.”

Some of the most interesting opportunities in AI aren’t the most obvious ones.

Behind the scenes, the growth of AI depends heavily on:

• Energy capacity
• Data infrastructure
• Cybersecurity
• Emerging tech like photonics

These aren’t always headline-grabbing sectors, but they’re essential to making AI work at scale. And that’s exactly where this ETF is also looking.

 A Broader Way to Think About AI 

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