What the study tour made me think about AI, diversification and investment discipline.
Amie Baker | Founder & Financial Adviser | Rekab Advice | September 2026
There is a lot of discussion at the moment about whether AI is a bubble. After spending time in Silicon Valley and New York as part of the CFS Empower Her Limitless Study Tour, I came home thinking we may be asking the wrong question. Can individual AI companies become overvalued? Absolutely. Can enormous amounts of capital chase an exciting theme and push valuations beyond what the fundamentals justify? Of course. And are today’s winners guaranteed to still be the winners in ten years? History tells us to be very careful making that assumption. But that is very different from asking whether AI itself is simply a bubble.
One of the benefits of the study tour was seeing AI from several very different perspectives. At Snowflake, we talked about the data foundations required for businesses to use AI effectively. At OpenAI, we saw the extraordinary pace at which AI is moving into everyday life and decision-making. At Tesla, we saw AI moving beyond something we interact with on a screen and into the physical world. Then at Amazon Web Services, the conversation reinforced just how much technology now sits underneath the businesses and services we use every day. Together, those experiences made me think differently about what we actually mean when we talk about “technology” as an investment exposure.
Technology isn’t necessarily one homogenous bet. AI touches cloud computing, data and information, semiconductors, data centres, physical infrastructure and energy. Then there are businesses across virtually every other sector that can use that technology to become more productive. A healthcare company may use AI to improve diagnostics. An industrial business may increase output or efficiency. A financial-services company may dramatically reduce the time and cost involved in administration. Logistics businesses can optimise their operations, while professional-services firms may be able to deliver work faster and more efficiently. At the same time, the enormous computing requirements behind AI create their own demands for energy and infrastructure.
This is where I think the investment conversation becomes much more interesting. The obvious AI investment story has centred around the companies building the technology, but where will the economic value created by AI ultimately land? Some of it will undoubtedly remain within technology, but some of the greatest beneficiaries may ultimately be businesses we wouldn’t currently describe as technology companies at all. If AI allows a business to improve its productivity, capacity, systems, decision-making or margins, that has the potential to change the economics of that business.
We saw another side of this when we moved from technology companies into conversations with investment managers. At Franklin Templeton, AI was being considered not only as an investment opportunity, but as a technology capable of changing the way the business itself operates. At T. Rowe Price, we saw examples of AI already being incorporated into investment workflows, including assisting with research, identifying patterns and key takeaways, reviewing portfolio performance, producing trading commentary and supporting tactical asset-allocation decisions. One of the applications presented to us was estimated to save between 80 and 160 hours each quarter.
That caught my attention because AI isn’t simply creating companies for investment managers to analyse; it is beginning to change the way investment managers themselves research, analyse and make decisions. We are seeing the same principle within our own business. At Rekab, we are already using AI to help remove repetitive administration, capture meeting notes, find information, review files and correspondence, and improve our systems and processes. The objective isn’t AI for the sake of AI. It is increased capacity and what we can ultimately do with that capacity.
I think there is an important parallel here for investors. The objective shouldn’t be simply to say we have “AI exposure” in a portfolio. It should be to understand where genuine economic value is being created. And despite all the excitement around this technology, the questions we ask as investors really shouldn’t change. What does the business actually do? How does it make money? Does it have good management and a sustainable competitive advantage? Can it generate cash flow? What are we paying for it? What could go wrong? And what role does it play within the broader portfolio?
AI may allow a business to dramatically improve its capacity, management systems, processes and productivity, but we still need to determine whether those improvements create a better business and, importantly, whether that better business represents a good investment at the price we are being asked to pay. That’s why I don’t think the emergence of AI means abandoning traditional investment thinking. Quite the opposite. It makes research, valuation, risk management and diversification even more important.
The comparison I keep coming back to is the internet. The internet didn’t disappear when the dot-com bubble burst. What changed was which businesses survived, which business models proved sustainable and where the economic value ultimately landed. AI may prove similar. We don’t need to predict every winner, and we certainly don’t need to chase every company associated with the theme. Some of today’s leaders may continue to dominate, others may not, and some of the biggest beneficiaries may emerge in places we haven’t yet considered.
In many ways, what I saw in the US didn’t change my investment philosophy; it reinforced it. AI may transform industries, create entirely new opportunities and significantly improve the productivity of businesses we already invest in. But our job as investors remains remarkably consistent: understand the businesses we invest in, understand how they create value, remain disciplined about what we are prepared to pay, manage risk and build diversified portfolios that don’t depend on us correctly predicting every winner. Technology may change extraordinarily quickly. Good investment discipline shouldn’t.
But the experience did leave me asking another question: are we looking broadly enough at where the investment opportunities of the future may lie? That’s what I’ll explore in my next article.
Rekab Advice
This article contains information that is general in nature and does not take into account the objectives, financial situation or needs of any particular person. Rekab Advice is the trading name of Rekab Enterprises Pty Ltd, a Corporate Authorised Representative of LFG Financial Services Limited AFSL No. 227096.