The three questions all investors should be able to answer: Why this strategy? Why now? Why pick it over its peers?
The recent sell-off in the technology sector has created “a very interesting entry point” for investors in the big data megatrend, believes Xiadong Bao, co-lead on the EDRF Big Data strategy at Edmond de Rothschild.
“People say the human interface between an end-user and software will potentially change because, eventually, we don’t need software,” he says in the above WealthWhys video. “Well, that may be partially true but mostly these are misunderstandings – and that has created a lot of interesting buying opportunities within the software sector.”
Software is about more than human interface, argues Bao, who continues: “There is logic, there is data beneath that. Yet the market right now is treating the threats from AI agents as kind of an existential risk for all the software players, which creates a lot of misunderstanding – and a sell-off with not that strong a rationale.
Big data has never been a better thematic in history than right now – especially with 2026 being the year of the AI agent.”
“So we think the correction makes a very interesting entry point – especially for ‘verticalised’ software. I mean, we are not talking about CRM, aftersales – you know, Microsoft, these kind of ‘horizontal’ guys. We are talking about verticalised, specialised guys that know you so well, have held your data since the very beginning of your business and have a very high entry barrier.
“And their algorithm has already been baked into the nature of your business – so, in that way, AI can help them eventually to increase efficiency and then reiterate different versions of software. But that will all make software stronger. So, from that point of view, we think big data has never been a better thematic in history than right now – especially with 2026 being the year of the AI agent.”
Three pillars
Asked later what sets the strategy he runs with Edmond de Rothschild co-head of equities Jacques-Aurélien Marcireau apart from its peers, Bao focuses on diversification. “When we talk of big data, there are three pillars,” he explains. “There is data infrastructure, there is data analytics and there are data-users.”
For Bao, the last of these is the most important in ensuring an extra level of diversification. “We have exposure to data-users with our portfolio, not only because they can diversify us throughout other sectors – be it healthcare, industrial, financial or even energy – but, at same time, they actually create more value for shareholders because they apply big data strategy much better than their peer group.
“In that way, we have a portfolio that is very well diversified but, at the same time, captures the big data megatrend throughout the years. That is really our differentiating point versus the others – especially with the long-term horizon of investment, which is part of our DNA at Edmond de Rothschild.”
WealthWhys – with Xiadong Bao,
co-lead on the EDRF Big Data strategy at Edmond de Rothschild
A full transcript of this interview can be found after this box while you can view the whole video by clicking on the picture above. To jump to a specific question, just click on the relevant timecode:
00.00: Why invest in big data?
01.50: Why should investors consider buying into big data now?
04.56: Why should people invest with this strategy rather than any of its peers?
Why invest in big data?
Well, first of all, big data is the foundation of everything today. Especially now people talk quite a lot about artificial intelligence – you know, without data, artificial intelligence is just boring algorithms.
So we have doing been this for 10 years. At the very beginning … I mean, we have not been so talkative about artificial intelligence. We talked a little bit about algorithms, machine-learning – and then you got robotics, you got preventive medicine. But all these actually share one common layer, which is foundational to us – and that is big data.
As an investor, if you invest in the long run, you are not investing on a one or two-year small cycle – you should really invest into a megatrend, long cycle. And, in that way, big data is the best because it fits into a lot of, you know, innovations along the road.
So, like I said, we have done that for 10 years and we think we have sufficient expertise to go through different cycles. We know the ups, we know the downs, we know different types of market conditions and we think we can be a really good choice for investors who think a company with a clear big data strategy can win over another company that maybe lacks a big data strategy.
Eventually, you always invest into the most competitive companies throughout the cycle. So I guess, if I were to put it in a really concise way, that is our philosophy as to why you really need to invest into big data.
Why should investors consider buying into big data now?
Well, maybe you have already seen the volatility that has happened recently on the market in terms of the software sell-off. It is really due to AI agent-related concerns. People say the human interface between an end-user and software will potentially change because, eventually, we don’t need software.
Well, for me, that is partially true but mostly these are misunderstandings – and that has created a lot of interesting buying opportunities within the software sector. Because if you look at AI agents, they are very powerful. Everybody right now, we already use the chatbots – ask all sorts of questions – and increase by maybe 10 times, 100 times, your productivity.
I don’t know if you have already used AI or not, but obviously we are doing this talk in person – it is not AI-generated. But, if you look at the software, software is not only a human interface. There is logic, there is data beneath that. And the market right now is trying to treat the threats from AI agents as kind of an existential risk for all the software players, which creates a lot of misunderstanding – and a sell-off with not that strong a rationale.
So we think the correction makes a very interesting entry point – especially for ‘verticalised’ software. I mean, we are not talking about CRM, aftersales – you know, Microsoft, these kind of ‘horizontal’ guys. We are talking about verticalised, specialised guys that know you so well, have held your data since the very beginning of your business and have a very high entry barrier.
And their algorithm has already been baked into the nature of your business – so, in that way, AI can help them to increase, eventually, efficiency and then reiterate different versions of software. But that will all make software stronger. So, from that point of view, we think big data has never been a better thematic in history than right now – especially with 2026 being the year of the AI agent.
So we think more and more people will share their personal data and more and more companies will share their domain expertise data with an AI agent, or a couple of AI agents, and eventually maybe change the interface of software.
But in the end, the target is very simple: a personal AI agent will make us more productive and we will have more time for entertainment; while a team of AI agents for enterprise will make the enterprise more competitive, get more market share and create more value for shareholders – for investors like us.
Why should people invest with this strategy rather than any of its peers?
That is a very good question – because we are very different. Most of the funds you see on the market – be it a thematic technology fund or a sectoral technology fund – most of them are not as diversified as us.
Because, when we talk of big data, there are three pillars: there is data infrastructure, there is data analytics and there are data-users. So let me just oversimplify it a bit. Everything we talk about data infrastructure is just like hardware. So semiconductors, sensors, data centres, cables – these tangible pieces are really data infrastructure.
Data analytics, to oversimplify, is just software – algorithms, machine-learning, everything that is intangible – but it is very important. Like large platforms put more value into real-format data and resell that to their end-user.
And then most important here is the data-user. So we have that with our portfolio, not only because they can diversify us throughout other sectors – be it healthcare, industrial, financial or even energy – but, at same time, they actually create more value for shareholders because they apply big data strategy much better than their peer group.
So in that way, we have a portfolio that is very well diversified but, at the same time, captures the big data megatrend throughout the years. I think that is really our differentiating point versus the others – especially with the long-term horizon of investment, which is part of our DNA at Edmond de Rothschild.
