Do you use AI at work and for what?
curious with all this AI buzz if companies are already asking analysts to use AI agents and ChatGPT
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Based on the most helpful WSO content, AI is already being integrated into various roles, including those in finance. Analysts and associates are increasingly using AI tools like ChatGPT and other large language models (LLMs) for tasks such as:
Automating Repetitive Tasks: AI is being used to automate lower-value tasks like data collection, creating financial models from reported financials, and generating summaries of key portions of documents like 10-Ks.
Improving Productivity: Tools like ChatGPT can assist in drafting reports, creating slide decks, and even performing sentiment analysis on earnings transcripts to identify "risky" language.
Higher-Value Work: By automating mundane tasks, analysts can focus more on higher-value work, such as securities analysis, macro-level projects, and alternative data research.
Operational Efficiency: AI is also being used to streamline internal processes, such as answering operational questions or automating client documentation workflows.
However, while AI is enhancing productivity, there are concerns about its potential to replace entry-level roles, especially in areas like asset management and investment banking. Some firms are already cutting back on new associate positions, anticipating that AI will handle many of these tasks in the near future.
Sources: Work at top AM -- AI will virtually kill of entry-level roles in AM over the next 5yrs, ChatGPT: The AI Analyst Who Ate Wall Street, Thoughts on AI and the future of the job market?, https://www.wallstreetoasis.com/forum/hedge-fund/machine-learning-taking-over-hf-research-analyst-roles-in-near-future?customgpt=1, GPT-4 & Microsoft Co-Pilot
I use AI constantly for finance—everything from analyzing earnings calls and building financial models to researching industries, competitors, and market trends. The biggest challenge isn’t getting answers anymore; it’s keeping all the context organized across dozens of reports, filings, spreadsheets, and conversations.
That’s why I’ve been using Trustgraph. Instead of treating every prompt like a fresh start, it connects information into a context graph, so relationships between companies, metrics, assumptions, and previous analyses persist over time. It feels less like searching through notes and more like building a knowledge base that AI can actually reason over.
For finance work, that means I spend less time re-explaining context and more time analyzing the business. It’s become one of the more practical open-source AI tools I’ve used because it improves the quality of long-running research instead of just making individual prompts better.
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