With the investment landscape becoming more competitive, efficiently scaling
deal sourcing and improving deal insights have become a dominant strategy for
funds. While funds are already spending significant efforts on these two tasks,
they cannot be scaled with traditional approaches; hence, there is a surge in
automating them. Many third party software providers have emerged recently to
address this need with productivity solutions, but they fail due to a lack of
personalization for the fund, privacy constraints, and natural limits of
software use cases. Therefore, most major funds and many smaller funds have
started developing their in-house AI platforms: a game changer for the
industry. These platforms grow smarter by direct interactions with the fund and
can be used to provide personalized use cases. Recent developments in large
language models, e.g. ChatGPT, have provided an opportunity for other funds to
also develop their own AI platforms. While not having an AI platform now is not
a competitive disadvantage, it will be in two years. Funds require a practical
plan and corresponding risk assessments for such AI platforms.

投资领域的发展变得愈发竞争，对于基金来说，高效扩展交易资源和提升交易洞察力已成为一种主导策略。这些任务无法通过传统方式进行扩展，因此自动化的需求也随之上升。许多第三方软件服务提供商应运而生，但他们由于缺乏对基金的个性化支持、隐私限制以及软件应用场景的局限性而未能成功。因此，大多数主要基金和许多较小的基金已经开始开发自己的人工智能平台，这对行业来说是一场变革。这些平台通过与基金直接互动变得越来越智能化，并可用于提供个性化的应用案例。最近大型语言模型的发展，例如 ChatGPT，为其他基金开发自己的人工智能平台提供了机会。虽然现在没有 AI 平台不会造成竞争劣势，但两年后将会有变。基金需要一个实际可行的计划以及对这种 AI 平台的风险评估。