FIGURE 1 AREA


Earnings prep and scenario analysis Drafting and refining communications Shareholder targeting and engagement Compliance and risk monitoring Other


Security and Skills: The Two Biggest Barriers When asked about the biggest obstacle to adopting AI in IR, a majority, 56%, pointed to data privacy and security concerns, followed by 27% citing a lack of internal expertise or resources. Regulatory uncertainty and cost were cited far less frequently, at 4% and 2%, respectively. Tese results highlight that the challenge is less about budget


and more about trust. As investor relations sits at the crossroads of public markets and corporate disclosure, IR leaders must ensure that any AI adoption complies with governance standards and preserves confidentiality.


Where AI Adds the Most Value: Earnings and Communications Perhaps the most revealing section of the survey asked IROs where they believe AI could provide the greatest value to their function. Te results were revealing (see Figure 1). Nearly four in five IROs see earnings preparation as the most


valuable AI use case. From tracking analyst revisions and preparing Q&A for calls, to aligning internal forecasts with market consensus, the pre-earnings period is rich with structured and semi-structured data ripe for automation. Close behind is drafting communications, cited by nearly


three-quarters of respondents. AI’s ability to synthesize complex information into narrative form (such as earnings scripts, press releases, and investor presentations) represents an area of genuine efficiency gain, especially when combined with data sources that supply accurate, current consensus figures.


The IR Tasks Ripest for Automation When asked to choose one recurring task they would most like to automate with AI, IROs pointed to the same bottlenecks that


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% SELECTING 79% 73% 38% 15% 10%


dominate their workflows today: • Tracking and summarizing analyst models (27%) • Preparing Q&A for earnings calls (25%) • Building and updating peer comparisons (17%) • Drafting investor presentations (10%) • Monitoring investor sentiment (8%)


“Investor relations teams are selective about the technologies they use to automate because of their unique role and the sensitivities involved.”


Together, these activities reflect the growing volume of data


that IR teams must manage—broker models, consensus forecasts, KPIs, and qualitative sentiment from the market. Each process is repetitive yet highstakes; a misplaced assumption or outdated datapoint can skew internal alignment and external messaging.


The Next Frontier: Human Judgment + Machine Insight Te survey makes one thing clear: IROs aren’t afraid of AI—they’re pragmatic about it. Tey understand its promise and its pitfalls, and they want solutions that make their work more accurate, more insightful, and more strategic. AI in investor relations will not replace the judgment, relation-


ships, or credibility that IR professionals bring to the table. Instead, it is becoming an intelligence layer that connects disparate data sources, accelerates reporting, and improves decision quality.


IR UPDAT E ■ FA LL 20 2 5 9


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