AI and Investor Relations: Practical Insights and Real-World Applications
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Innovate & Transform

AI and Investor Relations: Practical Insights and Real-World Applications

/ Report

As AI technologies continue to evolve, investor relations (IR) professionals are presented with new opportunities and challenges. This report, based on a keynote presented at The Conference Board Global Investor Relations Council, explores the practical applications of AI in IR, its impact on current practices, and considerations for successful implementation.

As AI technologies continue to evolve, investor relations (IR) professionals are presented with new opportunities and challenges. This report, based on a keynote presented at The Conference Board Global Investor Relations Council, explores the practical applications of AI in IR, its impact on current practices, and considerations for successful implementation.

  • AI is evolving from novelty to necessity in IR, driving efficiency and smarter decision-making but requiring IR professionals to develop new skills and strategies to leverage AI's capabilities in daily IR operations.
  • Automating routine IR tasks such as report generation, basic chatbots, and earnings call summaries with AI allows companies to prioritize quick wins and free teams to focus on strategic initiatives.
  • Activities that involve predictive and interactive elements including bespoke investor communication, optimized investor targeting, predictive Q&A for investor calls, and tailored equity stories are more complex to execute but are more rewarding.
  • AI-driven sentiment analysis is becoming crucial for understanding market perception and IR teams should adopt these tools for real-time insights into investor sentiment, enabling proactive and targeted engagement strategies.
  • AI is showing promise in financial statement analysis, with some models outperforming human analysts in earnings predictions and forecast accuracy.
  • Implementing AI in IR presents challenges in accuracy, data security, and ethics. Companies need to develop robust AI governance frameworks, emphasizing human oversight, data protection, and ethical use in financial communications.

Author

Claudio Truzzi

Claudio Truzzi Claudio Truzzi

Senior Fellow, ESF Center, Europe
The Conference Board

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