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Investor Relations

How AI Helps Investor Relations Be More Proactive

March 21, 2023 | by Liron Hadar
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Artificial intelligence (AI) is transforming the investment industry. If harnessed correctly, AI can...

Artificial intelligence (AI) is transforming the investment industry. If harnessed correctly, AI can provide new opportunities and minimize potential threats for investor relations officers (IROs).  

By 2025, AI and data science will dictate technology investment decision-making, according to Gartner. More than half of the institutional traders surveyed by JP Morgan said that AI and machine learning will be the most influential technology in shaping the future of trading over the next three years. IROs need to embrace AI while at the same time being mindful of its limits.

AI changes investing

AI-based predictive analytics, natural language processing (NLP), algorithmic trading, and risk management tools can help investors process and analyze data faster and more comprehensively than ever before. And even newer tools such as ChatGPT – a form of generative artificial intelligence that creates human-like conversations – are being used by investors for sentiment analysis and summarizing news/opinions about a certain company or trend.  This means that investment decisions, with the help of AI, can increase efficiency and improve predictability. Applying AI in investment decisions presents an enormous opportunity to evaluate target companies' financial health and performance from weeks to minutes. 

How AI helps institutional investors

AI helps institutional investors in a number of ways:

1. Predictive analytics

AI can help institutional investors by providing predictive analytics that inform their decisions about investments. By analyzing vast amounts of data, AI algorithms can identify patterns and trends that might not be apparent to humans. This provides insights into potential investment opportunities and risks.

2. Risk management

AI can also help institutional investors by providing risk management tools. By analyzing market data and other relevant information, AI algorithms can identify potential risks and suggest strategies to mitigate them.

3. Portfolio management

AI can assist institutional investors in portfolio management by providing insights into portfolio performance and suggesting adjustments to optimize returns. AI algorithms can analyze market data, investment trends, and other factors to identify potential opportunities and risks.

4. Natural language processing (NLP)

NLP technology can help institutional investors by analyzing large volumes of news articles, press releases, and other sources of information to identify relevant data that may affect investments. NLP algorithms can also help investors monitor social media and other online platforms for sentiment analysis and real-time market insights. 

5. Algorithmic trading

AI can also be used to develop and execute algorithmic trading strategies. By analyzing market data and executing trades automatically, AI-powered algorithms can help investors capitalize on market opportunities and reduce the impact of human bias.

There is no denying that change is happening right now. But these myriad applications of AI can easily put any IRO on the defensive.  

For instance, consider how an activist investor can use AI. By analyzing data from financial statements, news articles, social media, and other sources, AI algorithms can identify companies that may be undervalued or vulnerable to activism. AI can help activist investors evaluate target companies' financial health and performance. And on top of that, remember, AI does all this quickly – and of course a fast-moving and informed activist investor can give an IRO plenty of headaches. 

How AI changes Investor Relations

So, what does this mean for IROs? The key here is to understand AI and its frameworks; utilize the opportunity it creates and minimize threats it imposes. 

It’s easy to see how AI can have an enormous impact on IR in a number of ways:

  • IROs need to be more accurate and transparent about the data they share. That’s because investors possess more comprehensive information about the companies they assess, down to a level of granularity (and history) that IROs have not had to answer to before.
  • IROs need to act more quickly. Since institutional investors can process data about a company, its competitors, and investment risks faster, IROs, in turn, need to respond faster. 
  • IROs need to produce quality content. Producing quality content is more important than ever. That is because generative pre-trained language models are being fed data and sometimes learn from invalid data. Producing quality content will make sure that the information gathered is accurate and reflective. Language models still have limitations and lag in logical reasoning and providing correct answers. 

These pressures can place enormous strain on any IRO – especially as more institutional investors adopt AI. So, what’s the answer? It’s pretty simple: if you can't beat them, join them.

How IROs can get better using AI

Analyzing financial data

AI algorithms can analyze financial data from various sources, including company reports and market data, to identify trends and patterns that can help IR teams understand the financial health of their own company and make informed decisions.  

Providing real-time market insights

AI can analyze news articles, social media, and other sources of information to provide real-time market insights to IR teams (just like investors do). This can help IR teams stay informed about market trends and react quickly to any potential issues. The realm of social media alone is fertile ground for using AI-powered social listening tools. With AI, these tools can scan real-time investor sentiment being shared on Twitter and other social media platforms to identify trends and potential threats from activist investors before they bubble to the surface. (And the rapid demise of Silicon Valley Bank, which was fueled by Twitter, is an example of just how quickly an issue can escalate.)

Improving communication

AI-powered chatbots and virtual assistants can be used to improve communication with investors. These tools can help answer investor questions, provide information about the company and its financial performance, and offer personalized recommendations based on individual investor preferences. For instance, I noted above that NLP gives institutional investors an advantage. They can help IROs, too. Example: with NLP, an IRO can scan transcripts of multiple investor calls to find themes emerging from the question that investors ask and investor sentiment. 

Improving investor targeting

AI can help IR teams identify and target potential investors who are likely to be interested in their company, including activist investors. By analyzing data on investor behavior, AI algorithms can identify investors who have a history of investing in similar companies or who have expressed interest in companies in the same industry.

Predicting investor behavior

AI can help IR teams predict how investors are likely to respond to different communication strategies. By analyzing investor behavior and sentiment data, AI algorithms can identify which types of communication are most likely to be effective and tailor communication strategies accordingly.

In other words, AI helps IROs become more proactive.

Limitations of AI in communicating with stakeholders 

At the same time, AI is not a panacea. IROs need to use AI software judiciously. AI can help with all the above needs – but it’s no substitute for human judgment. AI will not:

Communicate with authenticity

IROs still need to create credible, compelling narratives that build trust. IROs need to lean into digital tools such as video, events, annual reports, and briefings. To be sure, AI gives IROs better data to make communications more targeted. And AI can certainly help IROs ideate on topics and create drafts of content such as press releases – but the onus of sharing great content comes down to a human being.  

Create great relationships

IROs and corporate officers act as chief brand ambassadors. A convincing and credible CEO, CFO, and their IRO need to convince investors to believe in them. AI software does not do any of that. Investor relations are still driven by people connecting with people at a personal level. 

Replace decision-making

IROs need to evaluate the data provided by AI along with human judgment and an IRO’s understanding of current market conditions. By definition, AI builds on historic data. But markets can change on a dime. And of course, AI does not possess intimate knowledge of a company that an IRO does. IROs need to weigh the recommendations provided by any AI software against the reality of real-time changes occurring in any company. 

Contact Investis Digital

As I discuss in this blog post, data informs decisions but does not make decisions. IROs require data-driven strategies, but IROs are still in the driver’s seat, applying human judgment. At Investis Digital, we help IROs do this all the time through our combination of strategic counsel and IR data analytics tools. To learn more about our capabilities, visit our website here. Read more of our IR-related blog posts here. And contact us today.