I previously stressed that artificial intelligence is not a tooling problem for asset managers, but an operating model problem and that strategy in the age of AI increasingly manifests itself through operating architecture rather than ambition alone. These perspectives inevitably lead to a more difficult and practical question: how does such a transformation actually unfold in a non-AI-native organisation?

I previously argued that artificial intelligence is not primarily a tooling problem for asset managers, but an operating model problem. The significance of AI lies in its impact on how organisations learn, scale decisions, and embed responsibility.

This article is the first in a short series on AI and operating models in asset management. It sets the context for the current AI wave and examines its implications for the industry. The second article will address data and AI strategy, while the final article will examine implementation from the perspective of an incumbent asset manager.