On Monday, Oracle Corp. announced its quarterly earnings, together with substantial financial information about its operations, via a conference call and live webcast. This earnings announcement resulted in an almost 12% increase in the company’s stock price the following day, with the corporation’s stock price closing at a record high in part due to increased demand for services underpinning widespread use of artificial intelligence.

Corporate financial information is for everyone. The information disclosed in financial statements should not be the purview of a small class of individuals who scry from indecipherable bones tossed forth by publicly traded corporations a few times a year. If companies use generative AI to disclose financial data, the resulting information can be less opaque, more accessible, and rewritten in ways suitable for the audience requesting it.

Everyone, except perhaps someone seeking to perpetuate or hide fraud, benefits from greater transparency. Markets respond more effectively to vital information such as earnings, and the public is better able to hold leaders accountable for their actions. Companies’ market values better track their underlying fundamentals, and individual investors are less likely to be misled when information is more transparent and understandable.

For example, corporations could use a chatbot that draws from the publicly announced financial disclosure on the investor relations section of their website (and which is already machine-readable due to the use of XBRL, a programming language that allows for the easy exchange of business information). Current and potential investors could ask simple questions, such as “How well did Oracle Corp. do this year?” and the chatbot could respond with simple information such as its recent stock price changes, its earnings, and how the earnings compared to the prior year. Investors could ask questions about the corporation’s underlying risks and the bot could respond with a distilled form of the risks and uncertainties disclosure in the corporation’s Management’s Discussion and Analysis.

With a corporate financial information chatbot driven by generative AI, investors could ask this bot questions about the company’s financial situation and it could provide information—based on the underlying company’s financial statements—answers and analysis in a manner appropriate to the user’s self-identified comfort and level of training in financial information.

All the underlying information and traditional financial statements should still be there for anyone to download and peruse. However, this would make the same information available to a wider audience and more effectively disseminate this information to a broader audience and vastly increase equity of accessibility to this information.

Current financial disclosure is also more robotically written than generative AI would create. Financial statement notes are full of boilerplate disclosure copy-pasted from one year to the next. This harms financial statement users by increasing opacity and, given limited processing costs of analyzing disclosure, imposes greater barriers to everyday users effectively utilizing the information in these reports.

There are currently other ways in which this information can be distilled for the everyday reader. However, these are generally behind various types of paywalls and require expensive subscriptions to access. Financial analysts create reports providing detailed investment advice, but these reports are primarily available only for large institutional investors.

Furthermore, those who write these reports are often subject to various biases or varying incentives, such as to drive sales of certain companies’ stocks. Instead, standard setters, such as the Financial Accounting Standards Board, could rely on academic research to identify key important measures and descriptors that bound an algorithm to describe companies’ performance for a period requested. Further, these tools can be interactive and tie answers to questions that users of financial statements often have to help better guide their investment decisions.

While risks are certainly present in the use of generative AI in the finance function, these risks are no greater to the bias, opaqueness, and cybersecurity risks that companies already embedded within traditional financial statement creation and disclosure face. These bots need to follow the same guidelines and principles that underpin the rest of the financial statement concepts—particularly that the information must be complete, unbiased, and free from error to be represented faithfully. Such tools are already on the verge of being provided by a multitude of third parties: Would it not be better for such tools to be created in a way that is regulated and guided by the same reporting principles as traditional financial disclosure?

It is true that some of this could be costly up front, particularly to smaller businesses. However, the efficiency gains within a company’s own finance function through the implementation of generative AI would quickly outweigh the up-front costs of implementation.

Further, the implementation of generative AI in the finance function would also allow those accountants and finance professionals to focus away from the mechanical aspects of financial disclosure that are largely already automated to focusing on value-added analysis on determining disclosure and reported amounts that rely on greater amounts of discretion.

It’s vital for leaders to be proactive in creating standards that guide the creation of tools that benefit everyone before there is a proliferation of unregulated tools. With automated and chatbot-driven financial disclosure, financial statement information will be more equitable and accessible, and will result in efficiency gains for corporations and financial markets.