2024人工智能在投资管理中的应用研究报告

AI Integration in Investment Management

Introduction

• Objective: Assess the current scope and planned applications of AI in investment strategies, investment opportunities, and operational impacts.
• Methodology: Conducted a global manager survey from December 2023 to mid-January 2024, involving 150 asset management managers.

Key Findings

• Current and Planned Applications of AI:

  • Role Distribution: 51% of respondents are from both investment management and technology/business development teams.
  • Use of AI: 71% of managers are currently using or plan to use AI in their investment strategies or asset-class research.
  • Core Capabilities: Generative AI (gen AI), Large Language Models (LLMs), Natural Language Processing (NLP), and Machine Learning (ML) models are the primary AI tools used.

• Current Use of AI:

  • Augmentation: AI is primarily used to augment existing capabilities through expanded data sets and analysis/idea generation.
  • Human Intervention: A significant portion of current AI processes still require human oversight, indicating AI as a supportive tool rather than a direct replacement.
  • Decision-Making: Over half of AI-integrated teams report that AI analysis informs rather than determines final investment decisions. A fifth report that AI proposes decisions, which teams can override.

Future Impact of AI on Markets and Strategies

• Economic Benefits: Managers expect AI to contribute to a $14 trillion boost to the global economy by 2030, with a 9% increase in global GDP over the same period.
• Market Efficiency: AI is expected to increase market efficiency while also increasing market concentration.
• Barriers to Full Potential: Data quality and availability, integration and compatibility, and ethical/legal considerations are cited as major barriers.
• Regulatory Concerns: Divergent AI regulation is seen as a significant risk factor by nearly half of managers.

Operational Impacts of AI Integration

• Ramp-Up: AI integration has increased over the past year, but many managers have been working on it for more than three years.
• Priority Areas: ML, NLP, and gen AI are the top priorities for operational investment.
• Commercial Impacts: While productivity gains are expected, the impact on assets under management (AUM) and firm-wide revenues is uncertain.
• Headcount: Managers expect AI to have a limited impact on headcount over the next five years.

Conclusion

This survey highlights the growing use of AI in investment management, emphasizing its role in augmenting existing capabilities and providing insights into the challenges and opportunities associated with AI integration.