英文_Bernstein_资产管理中的生成式人工智能-投资用例以及我们技术未来会议的关键要点_18页_3mb

报告摘要

Approach Strategies: Adopted by firms in different ways. BlackRock favors a bottom-up method, where investment teams drive use cases, while Maybank blends top-down and bottom-up approaches. Top-down programs are structured but may slow implementation.
Build vs. Buy Solutions: Most AI solutions are internally built (e.g., BlackRock and Maybank), but discretionary funds often prefer buying ready-made vendor solutions like AlphaSense to avoid development costs and keep up with rapid Gen AI advancements.
Data Capture Importance: Systematic collection of internal data (emails, memos, etc.) is crucial for effective AI use. Funds are improving data sharing through knowledge bases and regular sessions to enhance insights.
Job Impact: Gen AI is a tool to augment, not replace, investment roles. It increases efficiency, allowing time for more productive work. Junior roles may see reduced data gathering tasks, but overall hiring could decrease due to improved efficiency.
Common Use Cases: Examples include summarization, RFP responses, earnings analysis, idea generation, and content creation. BlackRock and Maybank highlighted specific applications in their operations.
Vendor Landscape: Popular vendors like AlphaSense provide platforms for AI efficiency, with considerations on cost and training data. Many funds are exploring various Gen AI uses across research and investment workflows.