If the competitive advantage of AI shifts from information gathering to information processing, the race for alpha – and thus for investor money – could also change fundamentally.
In recent days, there has been a lot of discussion about whether the Chinese AI model Kimi K3 is the next “DeepSeek moment”. The debate revolved around one question in particular: Will China succeed in catching up with the USA in the race for the most powerful artificial intelligence?
However, China seems to be pursuing a different strategy – at least for the time being. While the U.S. is investing enormous sums in increasingly powerful models, data centers and chips, China seems to be focusing more on integrating artificial intelligence into the everyday lives of companies and people as quickly and cost-effectively as possible.
Interesting conclusions can be drawn from the observation that this is an economically different strategy to make AI not only more powerful, but also as widely usable as possible. After all, the idea that diffusion could ultimately be more important than innovation may not only change economies – but also our industry.
In real asset management, competition has traditionally been explained by information advantages. Better research. Exclusive networks. Early access to transactions. Off-market deals. The implicit assumption is that those who have better information or find the better objects will achieve alpha in the long term.
But what happens if almost every market participant has access to powerful AI systems in the future? How much do competitors differ at all if one has 100 percent of the relevant information and the other 80 percent? The more similar the level of information becomes, the more likely it is that the decisive competitive advantage may no longer arise from the information itself, but from its processing in the investment process.
The following figure outlines this possible shift in competition.
AI could not devalue information. Rather, it could shift its source of value creation. The decisive competitive advantage would then no longer be primarily in having better information, but in translating existing information into decisions faster, more consistently and more intelligently.
This is a fundamentally different perspective on information. It demystifies the myth of the ingenious deal sourcer and makes it clear that in the future competition will no longer be decided primarily between objects, but within the organization.
The decisive question is then no longer who will find the better object. But who can most efficiently link due diligence, asset management, financing, ESG, risk management and fund management. Those who process information faster and translate it more consistently into decisions will achieve better results more often, even if they are at a slight information disadvantage.
This also includes recognizing risks earlier. AI can automatically transfer insights from one area to the next, making the entire investment process more robust and consistent.
It would not make the individual asset more intelligent as a result.
But the organization behind it.
This may also shift the source of the alpha. Not because AI identifies more spectacular investments. But because it reduces errors across thousands of decisions, makes risks visible earlier and makes existing information usable more consistently.
The race for alpha – and ultimately for investor money – could thus shift without us noticing.
📌 Result:
From China’s race for the fastest spread of AI, insights can be gained for the future of institutional real asset funds:
- It is not the competition for the best information that is likely to change the investment industry (information advantage).
- But the competition to translate information into the better investment process (diffusion advantage).
Then the real AI revolution will take place in the investment process.
