AI is already reshaping financial markets, but how are fund managers actually using it today, and where is adoption heading next?
To answer that question, AIMA’s Research Committee has commissioned a new, highly targeted industry survey to establish fresh benchmarking data for members on Generative AI adoption across the alternatives sector.
The survey explores:
To answer that question, AIMA’s Research Committee has commissioned a new, highly targeted industry survey to establish fresh benchmarking data for members on Generative AI adoption across the alternatives sector.
The survey explores:
- The most common and effective Generative AI use cases
- How AI may reshape the fund manager business model
- The impact on talent, hiring, and workforce structure
- AI’s role in investment decision-making
- Barriers to broader adoption
- Compliance, governance, and operational considerations
Participants will receive early access to high-level findings, along with the opportunity to engage directly with AIMA for additional benchmarking insights ahead of the full report publication.
Definition of generative AI:
Generative AI refers to a type of artificial intelligence that is designed to create or generate content that is novel and coherent, often mimicking aspects of human creativity. It involves algorithms and models that can produce data, such as text, images, audio, and even video, without direct human input for every element of the output. These models learn patterns and structures from existing data and then use that knowledge to generate new, similar content.
Generative AI refers to a type of artificial intelligence that is designed to create or generate content that is novel and coherent, often mimicking aspects of human creativity. It involves algorithms and models that can produce data, such as text, images, audio, and even video, without direct human input for every element of the output. These models learn patterns and structures from existing data and then use that knowledge to generate new, similar content.
