The discussion around AI in investment research is gaining serious momentum. Some expect disruption; others, incremental change. My view is more balanced: AI will fundamentally alter how research is produced — but not necessarily how we pick the next outperformer. 🚀
AI’s true value lies in speed, structure and scale. It can process vast datasets in seconds, uncover subtle patterns and deliver consistent analytical outputs. This reshapes the workflow, even if human interpretation remains crucial.
The future is moving towards more mathematical, transparent and data-driven reasoning.
Fundamental data will continue to anchor decision-making because it is methodologically solid and regulator-friendly. As more firms adopt similar datasets and AI-supported pipelines, research opinions will naturally converge.
In this environment, the traditional “gut feeling” loses influence. Not because intuition has no value, but because it cannot be justified as clearly as transparent, data-based logic. AI accelerates this shift by making analytical steps repeatable, comparable and measurable. 💡
And this is where a major opportunity emerges:
Independent wealth managers — who historically lacked the manpower to build deep research capabilities — can now compete at a level that was previously unreachable. With proper data access and AI-powered tools, they can analyse markets with the depth and speed once reserved for large banks with extensive research departments. This is not just technological progress; it is a structural levelling of the playing field.
The future of investment research will not be about AI predicting winners. It will be about leveraging AI to enhance clarity, speed and analytical strength, regardless of firm size.
So the real question becomes: Who will make the shift first — and fastest? 👇
