5 min read
Event Recap: Modern Consensus Management at CIRI Senior IRO Leadership Day
Ask any IRO about consensus and you'll hear the same frustration. A group of analysts builds forecasts on your...
Over the past several months, our pulse surveys have captured how IR professionals view the promise and the limits of AI. The answers reveal a pragmatic community: focused less on hype, more on time saved, risks managed, and sharper engagement. As the data shows, IR teams are beginning to shift from experimentation to embedding AI into everyday workflows, and the patterns are telling.
Earnings: Where AI Delivers Fastest
When asked where AI creates the most value, nearly 49% of respondents pointed to earnings call and report summarization. In a separate survey, 35% ranked predictive Q&A generation as the capability that will most transform their earnings preparation in the year ahead, with 30% highlighting sentiment and tone analysis.
These results make sense. Earnings are high-stakes, high-frequency, and repetitive. AI reduces the heavy lifting of summarizing transcripts, preparing draft scripts, and building Q&A lists, while leaving the strategic narrative and investor messaging in human hands. The value here is not replacing judgment but reclaiming time to sharpen it.
Communications: From Speed to Safety
For investor communications, respondents split evenly between real-time disclosure testing (40%) and investor reaction forecasting (40%) as the most transformative use cases. Only 20% selected analyst coverage synthesis, while no respondents saw competitive positioning or Q&A training as priorities.
The emphasis on disclosure testing and forecasting marks a shift in how AI is viewed. It is not just about faster drafting; it is about de-risking communication. Before key announcements, teams want assurance that language is clear, tone is measured, and potential market reactions have been considered. AI’s role here is as a safety net that supports judgment, not a replacement for it.
Engagement: Precision Over Volume
When it comes to engagement, predictive targeting (35%) came out on top, with personalization (22%) and narrative development (22%) close behind. Less urgency was placed on strategic risk alerts (13%) or sentiment intelligence (9%).
At the same time, nearly half of respondents cited limited bandwidth (48%) as their biggest challenge, while another 45% pointed to data overload. This shows that IR teams are not looking for more tools or more channels. Instead, they want solutions that cut through complexity and surface the right opportunities. The goal is quality over quantity: focusing outreach on the right investors at the right time with tailored, relevant messages.
ESG: Targeted, Not Universal
The ESG conversation is also evolving. 39% of respondents said ESG remains important but more targeted, while 37% noted investor interest has declined. Only 20% still see ESG as central, with the rest viewing it as a secondary or evolving focus.
The takeaway is that ESG is not disappearing but becoming more selective. Investors want clarity on the issues that are truly material to long-term performance. For IR, this means grounding ESG communications in measurable business impact, tying them to risk management, growth drivers, or cost of capital, rather than treating ESG as a blanket priority.
Looking Ahead: IR Priorities
When asked what will matter most in the remainder of 2025, responses split evenly between leveraging AI and data (38%) and enhancing the corporate narrative (38%). Other priorities ranked much lower, with retail engagement at 13%, proactive risk management at 9%, and closer C-suite alignment at just 2%.
This dual focus reflects the new reality for IR. AI is becoming essential to handle volume, speed, and insight, but the endgame remains human: telling a sharper story that resonates with investors. Efficiency and narrative are no longer separate goals—they reinforce each other.
Final Word
The pulse surveys show a profession evolving fast. What began with summarization, preparation, and automation is now shifting toward forecasting, targeting, and disclosure checks. AI has moved from experiment to infrastructure, an operational layer in IR.
Teams that start with immediate wins in earnings prep and communication support, and then build toward predictive use cases, will be best positioned to show measurable impact with both leadership and investors. With the right governance and secure platforms, AI is strengthening judgment and decision-making.
Q by Q4, the industry’s first IRO AgentTM, brings this to life by combining forecasting, targeting, and communication support into one intelligent layer. Learn how Q can support your team’s next chapter.