Another project, Mercury, a secretive project that is slowly progressing by OpenAI, was created to automate the major work of entry level banking analysts and consultants.
The project is reported to have over 100 ex-finance professionals who were hired to train the AI engine to deal with all the tasks, including modeling and client pitch preparation.
How Project Mercury Works
Meanwhile, OpenAI has employed former bankers and consultants in highly respected institutions to assist in creating and perfecting its AI in the financial services sector, according to insider reports.
It is said that these professionals are earning an average of around 150 dollars per hour, and this makes their positions higher than most salaries of analysts.
Their task, stuff the AI with prompting, authenticate its results, and verify that the system gives results in accordance with real life financial modeling norms.The concept of Project Mercury is a big one.
OpenAI will use the experience of a marketing team of professional, seasoned financial experts to train AI models to automate the processes of discounted cash flow forecasts, leveraged buyout predictions, IPO modeling, restructuring frameworks, and client presentation decks.
These are the conventional workloads of the junior analysts. When the AI can do this work in minutes and not weeks, OpenAI feels that it can transform the way financial firms work.
Alliances with investment banks and consulting firms are said to be included among the early pilots.
These tests are the combination of proprietary information of companies with the open AI stack of generative AI, which enables the model to create insights into investments, market summaries, and pitch materials that would otherwise be created by analysts.
The relocation is an indication that OpenAI is not only no longer focused on consumer facing AI but also on enterprise grade solutions in high stakes areas.
To junior bankers and new consultants, Project Mercury may represent a change in career path.
The standard entry level financial career is long hours of modelling, analysis, and deck building frequently regarded as a training ground for a higher level position.
When AI steals most of those jobs, the question will be, what becomes of the apprenticeship mechanism? Other experts opine that future analysts will become more of an oversight and strategist checking which AI outputs are valid and not creating their own.
OpenAI argues that the initiative is more about increasing productivity and not massive layoffs.
The company lays stress on the fact that human in the loop is paramount, particularly with financial services where accuracy, compliance, and context are paramount.
Nevertheless, the implication is obvious, since AI will become the grunt worker, the demand for uniquely human abilities, such as judgment, client relationships, and creative strategy, may increase.
The overall meaning of Project Mercury lies outside of banking.
In case it succeeds, the model could be a template for automating high skill, high volume work in the consulting, law, accounting, and other professional services.
It highlights the fact that artificial intelligence is not only adding to the jobs but is even defining them.
In companies operating in the competitive, high volume industries, such AI tools are capable of generating a more finely honed leverage.
Nonetheless, there are still some questions, how realistic are the AI results in the real world? What will companies do to make sure that it is transparent and auditable?
What are the so called regulatory guardrails that will be placed on AI provided financial guidance? And among young professionals, what is their adaptation?
Project Mercury by OpenAI can become a noteworthy turning point in the application of AI to the finance industry.
Although there is a possibility that entry level analysts cannot be eliminated in a single day, their functions are distinctly changing and are being transformed to quality assurance and strategic input.
The form of the banking and consulting careers may have a completely new appearance in several years as the project passes the pilot stage and becomes adopted.
