By Bas Kooijman, CEO and Asset Manager, DHF Capital S.A
Artificial intelligence is no longer a peripheral experiment in asset management. The industry has moved steadily toward more systemic integration of AI, not as a novelty but as a means of redefining performance, control, and scale. This transition is being driven by mounting pressure on firms to differentiate in increasingly efficient markets, manage ever-larger volumes of data, and respond more swiftly to client expectations. AI’s role has expanded from tactical deployments to firmwide strategic infrastructure.
On the investment front, AI is becoming increasingly instrumental in generating alpha. Managers are deploying advanced analytics and real-time modelling to detect patterns across large datasets, from macroeconomic indicators to sentiment feeds. Generative AI adds an additional dimension to investing and trading, enabling scenario simulations that support more tailored portfolio construction. These approaches move beyond the constraints of traditional factor models, capturing non-linear relationships and improving decision-making in volatile or complex market environments. The capacity to continuously refine exposures strengthens both execution quality and risk-adjusted returns.
The operational rationale is equally compelling. Process automation has cut the cost and complexity of routine tasks such as regulatory checks, reporting, and reconciliation. AI is lifting operational efficiency. Fraud detection, asset tracking, and predictive maintenance have also benefited from AI-enabled systems, reducing error rates and compliance costs. With global data volumes increasing non-stop, firms are now recognising that AI is not merely a technological option but a structural requirement for continuity, growth, and relevance in a fundamentally data-driven industry.