AI in IR: Opportunities, Risks, and What You Need to Know

If there’s one aspect of artificial intelligence that I can relate to as a communications strategist and former journalist, it’s the fact that I’ve felt like a “large language model” for most of my career. 

I don’t mean model in terms of my physical attributes. I mean model in a way that describes how most generative AI tools process information and organize responses based on prompts. That’s effectively what I’ve been doing in my career for nearly three decades! 

The good news is that platforms like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude are extremely helpful when processing mass quantities of complicated information. Using these platforms to understand a concept or interpret text is like using a calculator to work through a math problem. And yet, many of us really don’t know how these word crunchers work.   

This applies to AI tools used for investor relations, public relations, or anything else where an AI model could be prompted with sensitive information, which is then consumed by the public. Think about how many people working for public companies may inadvertently prompt ChatGPT with material nonpublic information (MNPI), which then informs a trader to ask the platform whether they should buy or sell a stock. 

AI Concerns Among IR Professionals 

Earlier this year, I worked with the University of Florida on a survey that found that 82 percent of IR professionals had concerns about disclosure issues surrounding AI use and MNPI. At the same time, 91 percent of survey respondents were worried about accuracy or bias, and 74 percent expressed data privacy concerns. 

These factors are enough for compliance teams to ban AI use altogether. But fear-mongering is shortsighted. There are plenty of ways to use AI safely, and understanding the basics of the technology, as well as its shortcomings, will make for more responsible and effective AI use in the future.   

Why You Should Know Where AI Gets Its Data

One of the first questions someone should ask themselves when using a new AI platform is where the information is sourced. The acronym “GPT” stands for generative pre-trained transformer, and that is a fancy way of saying that the technology can “generate” information or words based on “training” and data it received, which is then “transformed” into sentences.  

This also means that every time someone asks one of these platforms a question or prompt, they are pumping information into a GPT.   

That makes these platforms even smarter when analyzing complex business models.  

For example, many IR folks get bogged down summarizing sell-side analysts’ models and earnings forecasts from research notes. Simply upload those models into ChatGPT, and the platform does a great job understanding the contents and providing a digestible summary. Interested in analyzing the sentiment of a two-hour conference call script? How about uploading the script (post call to avoid MNPI) to Gemini and requesting a summary on what drew the most positive sentiment among investors? 

The Importance of AI Training and Education in IR 

But here’s the rub: Only 25.4 percent of companies provided AI-related training in the past two years, according to the U.F. survey. This suggests a disconnect between advancing AI technology and people’s understanding of how to use it. 

That means the onus is on us to figure it out. So, where to start? Many AI tools, including ChatGPT, have free versions that can help people summarize, plan, edit, and revise items.  

Google’s NotebookLM, is an AI platform that allows you to create a GPT, so you know where the AI is sourcing the information from. NotebookLM can also create podcasts based on the information generated by its LLM.  This could be helpful if a chief executive officer wants to take a run on a treadmill and listen to a summary of analysts’ notes instead of having to read them in a tedious email. 

Here are some other quick-hit ideas: 

• Transcribing notes. If you’re like me, you still prefer using a pen and pad when taking notes. You can take a picture of those notes, upload them to ChatGPT, and have it transcribed into text.
• Planning investor days. If you can prompt an AI with the essentials – the who, what, when, where, why, and how of the event – it can provide a thorough outline that makes you look smart and organized when sending it around to the team. 
• Analyzing proxy battles. Proxy fights are always challenging, especially when parsing the needs and wants of key stakeholders, including activists, media, management teams, and board members. Feeding an AI with publicly available information (to, again, avoid disclosure issues) can help IR and comms professionals formulate a strategy.
• Crafting smarter AI prompts. Writing effective prompts requires some finesse. The beauty of AI is that it can help you refine your prompts, leading to better information gathering. Try asking ChatGPT the following question: “If Warren Buffet is interested in investing in a company, what would be an effective AI prompt to understand its return on investment?” 

There are many other use cases that can help eliminate mundane tasks, allowing for humans to focus more on strategy. But in order to use AI effectively, it’s important to know the reason you’re using it. Perhaps, it’s demonstrating to management that being an early adopter of this technology is important to help a company differentiate itself.  

Building a Responsible AI Policy for Your Organization 

Before implementing any AI initiatives, it’s best to formulate an AI policy that organizations can adopt for internal and external use. Most companies are lacking these policies, which are critical for establishing the basic ground rules for AI use.  

I helped co-author the National Investor Relations Institute’s AI policy, which recommends the following: 

• The IR professional should be an educated voice within the company on the use of AI in IR, and this necessitates becoming knowledgeable about AI. 
• The IR professional should understand the pace at which their company is adopting AI capabilities and be prepared to execute their IR-AI strategy based on management's expectations.
• Avoid Regulation Fair Disclosure (Reg FD) violations. The basic tenet is to never put MNPI into any AI tool unless the tool has the requisite security, as defined or required by the company’s security experts, and has been explicitly approved for this particular use by company management. 

AI Will Not Replace You. But Someone Using AI Might. 

There is this prevailing fear that somehow AI is going to take over the world. But the technology is not likely going to replace your job. It’s smart users of the technology who will likely replace your job.   

AI is transforming how IR professionals work, but using it responsibly starts with understanding how it works. From summarizing complex reports to enhancing stakeholder communication, AI can be a powerful tool when used thoughtfully. Start by learning the basics, implementing clear policies, and exploring trusted tools to unlock its full potential.