Artificial intelligence in Investor Relations – the new frontier

AI is a hot topic reshaping IR in fundamental ways especially through the current broker advantage over corporates in terms of access to both big and alternative data sets, greater computational power and the application of AI to trading and the application of AI to trading strategies. How can IR adapt to this rapidly changing environment? Do you have a complete overview of the latest development shaping the future of IR?

Generally, most regulation is local – except in the digital realm and this affects how Investor Relations is evolving due to several drivers of change, including the changing nature of investors, data analytics and artificial intelligence (AI). AI is increasingly accelerating change in capital markets, triggering a heightened focus in this rapidly growing area. On these grounds, NIRI convened a think tank back in 2019 of thought leaders and generated the report “Artificial Intelligence in Investor Relations” sponsored by Computershare/Georgeson and Q4. In the following the main findings in the report are recapitulated.

The findings in this report are important to Danish IRO as all key trends and developments affecting your daily work usually have their origins in the US or in EU regulation (cf. GDPR and MiFID II) and are applied globally. Widespread adoption of AI is not yet in place, and this gives IR professionals an opportunity to develop the capabilities required to work effectively in a world with greatly increased AI and automation.

Implications for IR

Most IR professionals may not use AI-powered tools in their internal day-to-day work. However, some of their external audiences use AI extensively. This puts IROs at a disadvantage to a degree and highlights the need to quickly come up to speed to understand AI and its implications. The buy-side, for example, is increasingly using alternative data sets from many unconventional media and social media content.

AI service providers use machine learning and natural language processing technologies to create products based on a specific company’s most-used words. Such unique resources can help institutional investors develop a better understanding of a company’s tone over time and the potential implications for corporate decision-making. E.g., about one third of Bloomberg News content is generated by some form of automated technology enabling the system to dissect a financial report the moment it appears and spit out an immediate news story the moment it appears.

In 10 years’ time a world of nearly free data is expected and there will be so much of it out there for models to go get exactly what they need. ESG issues are at the center of AI as investors seek to identify, process and structure data in ways that yield meaningful understanding of corporate ESG performance. So, if you do not do a good job of providing data, investors may fill in the gaps by averaging available data and make projections based on that.

IROs unable to adapt in this rapidly changing environment risk being made obsolete over time due to a mismatch in skills versus unfolding market demands. To remain indispensable contributors to corporate success, the report urges IR professionals to:

  • Understand and adapt to how AI is being used externally.
  • Centralize external communications.
  • Determine how to use and benefit from AI internally.

This is an opportunity for the practice of IR to change moving forward. Now IR often relies too heavily on active asset managers and the sell side communicate their equity story – but this audience is getting smaller, and the application of technology in the market is an information disadvantage for corporates.

What is driving valuation? It is necessary to think differently about the practice of IR going forward. IROs are not just managers of the story but also of the scorecards: ‘IR 2.0’ – moving to relationship and data management.

PDF of the Fall 2020 edition of NIRI’s magazine, IR Update. It includes a focus on AI.