Artificial intelligence has long since established itself as a strategic topic for the future in asset management. All firms surveyed for our study "Current state of AI im Asset Management" rate AI as strategically important; three-quarters even regard it as critical or vital to their competitiveness. deutliche Lücke. Unsere Studie zeigt, woran das liegt und was erfolgreiche Häuser anders machen. Grundlage sind Experteninterviews mit Verantwortlichen aus dem COO-Ressort von Asset Managern, Servicing-Anbietern und Verwahrstellen, aus denen mehr als 640 Einzelbewertungen ausgewertet wurden.

However, there remains a significant gap between this aspiration and the measurable benefits. Our study shows why this is the case and what successful firms do differently. It is based on expert interviews with senior executives from the COO departments of asset managers, servicing providers and custodians, from which more than 640 individual assessments were analysed.

Download now: Current State of AI im Asset Management (in German only)

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Artificial Intelligence in German Asset Management: From a Use-Case Portfolio to Value Design

There is widespread investment in artificial intelligence projects within the asset management sector. However, only a small minority are able to achieve measurable economic benefits. Based on expert interviews and more than 640 assessments, the study highlights why this is the case and identifies the factors that distinguish successful AI initiatives from those that are less successful.

This is the state of the industry today:

75% view AI as critical or vital to their competitiveness.
63% are still in the testing or proof-of-concept phases.
12% are already successfully scaling up AI and achieving a measurable return on investment.

What makes the difference

Measurable added value is not created by having as many use cases as possible. Successful organisations embed AI throughout their value chains and manage it via business objectives and business KPIs rather than usage figures. The deeper AI is integrated into the value chain, the higher the ROI (return on investment) will be. The crucial question is therefore not how many AI applications a company uses, but the logic behind their deployment. The leap that determines success leads from the use-case portfolio to value design.

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