From pinpointing the smallest opportunities by scanning millions of documents to causing flash crashes, if widely adopted, full automation of investment research is a double-edged sword. This article will discuss the role of AI today in investment research, followed by what it can automate, the benefits and risks with automation, and then finally providing a verdict.
AI in Today’s Investment Research
In today’s investment research, AI is used to analyse reading, summarizing, and analysing earnings reports, classifying regulatory fillings, propose investment strategies, flagging risks, executing trade orders, and managing one’s trading portfolio. For example, the Goldman Sachs AI assistant will help “employees in summarizing complex documents and drafting initial content to performing data analysis”. Other large institutions such as BlackRock and JPMorgan have also rolled out internal AI assistants. BlackRock has launched Asimov, a virtual investment analyst AI that can scan text in research notes, regulatory filings and emails to produce portfolio insights, while JPMorgan has its Quest IndexGPT. Such moves reflect a broader trend: as data science capability grows, models can process far more information than any analyst, and decision-making becomes increasingly data-driven, underscoring the possibility of AI entirely automating investment research.
What can AI Automate
AI excels at data-intensive tasks, in financial analysis, this includes data aggregation and pattern recognition . Large Learning Models (LLMs) can analyse historical pricing risk models, alternative data, news stories, earning reports, or any other sort of information to make predictions. These predictions can be used to identify any opportunities that might be missed through traditional analysis or identify rising trends or the rise of a new growing industry. In other words, in investment research, AI can help investors identify upcoming or missing investing opportunities. For example, LevelFields AI analyses millions of events (what is happening in the world) to reveal outsized investment opportunities for self-directed investors.
Benefits and Risks with Automation of Investment Research
AI is reshaping investment research by boosting speed, cutting costs, scaling analysis, and integrating diverse data. AI has made investment research faster. Tasks like drafting and analysing reports now are done in minutes or hours compared to a week or more when done by a team. This efficiency reduces reliance on large teams, lowering costs for the company. Additionally, scalability is another key benefit: platforms like BlackRock’s Aladdin scan thousands of securities across markets in real time and display their prices. AI also unifies structured financials with unstructured sources such as news, satellite images, and social media, discovering essential trends and opportunities which may usually be missed - helping investors make more accurate decisions.
Despite the promise and potential, AI comes with serious issues. One key issue being "hallucination". LLMs, AI models can hallucinate false information, provide poor financial advice, or break down. This can impact investors’ decisions as false or misleading information can influence them to make essentially wrong decisions which can impact them financially. This can also occur if an AI misinterprets data and information, causing it to provide poor financial advice.
Moving on, fully automation also poses systematic risks - using AI to make investment decisions may lead to flash crashes or sudden runs in the market. As countless traders go to great lengths to incorporate all data they may find into their AI agents, these AI agents are likely to converge on the same data, leading to correlation risks, flash crashes, and sudden market runs as all the agents will execute the same order. For all individuals who depend on the earning of every dollar when trading, these flash crashes and sudden market runs can take one from ready for retirement to nearly bankrupt. Due to such volatile changes in the market full automation can bring, it can be a threat to countless investors in the world, further underscoring investment research automation risks.
Will investment research become fully automated?
No doubt that full automation of investment research has risks and it will be a decent amount of time before it does in fact occur, however, I believe investment research will inevitably become fully automated. Because of how it will make our lives easier, speed up the investment process, reduce costs for investment firms, the cons will be overlooked, and investment research will become fully automated.