{"id":8747,"date":"2024-06-04T14:22:17","date_gmt":"2024-06-04T22:22:17","guid":{"rendered":"https:\/\/www.indataipm.com\/?p=8747"},"modified":"2025-03-21T13:56:47","modified_gmt":"2025-03-21T21:56:47","slug":"how-is-ai-used-in-investment-management","status":"publish","type":"post","link":"https:\/\/www.indataipm.com\/how-is-ai-used-in-investment-management\/","title":{"rendered":"How Is AI Used in Investment Management?"},"content":{"rendered":"

Managing investments remains a very complex aspect of financial services. With so many factors having an impact, investment decisions must be fast and accurate to ensure a positive outcome. The volatility of the market itself affects the ability to implement changes to investment strategies. That is where having the necessary data available is <\/span>key<\/span> to the decision-making process. Leveraging and analyzing data to drive better outcomes is now possible to augment with artificial intelligence (AI). In this post, you\u2019ll learn how AI can be<\/span> applied to<\/span> investment management.<\/span><\/p>\n

Artificial Intelligence in Investment Management<\/span><\/h2>\n

Adopting AI as part of your investment management process can offer benefits. AI for investment has much promise and is somewhat at the beginning phases of adoption from an industry standpoint. Let\u2019s get familiar with the framework.<\/span><\/p>\n

What Is AI in Investment Management?<\/span><\/h3>\n

First, let\u2019s define AI investment management. AI technology can make use of available investment data to enhance outcomes when it comes to analyzing data used in the decision-making process.\u00a0 The goal is to analyze data faster and with the potential of gaining greater insights than the typical process where teams of analysts sift through data manually to reach the same results.\u00a0\u00a0<\/span><\/p>\n

AI can play a role in making sense of large volumes of data more rapidly to create insights in an automated fashion.<\/span><\/p>\n

AI functionality should be applied to a firm\u2019s <\/span>investment management software<\/span><\/a>. <\/span>AI data analytics<\/span><\/a> can be thought of as an additional module that can be used to deliver insights using such AI-based approaches as <\/span>natural language processing<\/span> (NLP) and machine learning (ML).<\/span><\/p>\n

The State of Artificial Intelligence Investment Management<\/span><\/h3>\n

There is significant value in adopting <\/span>AI-based<\/span> tools. Adoption has been somewhat slow in this segment of the market, even with <\/span>82% of wealth management firms<\/span><\/a> prioritizing AI initiatives. It’s worth noting that the market is growing, expected to reach <\/span>$13.4 billion<\/span><\/a> by 2027. The speed of adopting AI technology likely stems from the industry getting up to speed on the subject of AI itself and also on analyzing use cases among peers.<\/span><\/p>\n

The reality is that AI-based approaches within investment management have the potential to reduce costs and even have a multiplier effect for firms using them. The goal is to have AI work more as a supplement to human intelligence. Additionally, more investment professionals are pursuing AI skills, with <\/span>64% stating they are developing these capabilities<\/span><\/a>. This is especially true for the next generation of industry professionals within the investment management space.<\/span><\/p>\n

There\u2019s also concern about the inherent risks related to AI. These fall into a few different categories, including:<\/span><\/p>\n