AI – A Burgeoning Tool or Just Buzz?
Artificial Intelligence Survey Findings & Insights
Part 2 of 2: Corporates
In today’s Thought Leadership, we’ll be diving into corporate perspectives from our inaugural Artificial Intelligence Survey in the second installment of our two-week series AI — A Burgeoning Tool or Just Buzz?
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AI’s Impact on the Investment
Process and Investor Relations
Setting the Stage
During last week’s Thought Leadership – Artificial Intelligence Survey Findings & Insights, Part 1 of 2: Investment Professionals, we covered the ways in which the investment community is leveraging artificial intelligence to augment their investment process and approach. At a high level, we distilled four key findings from our survey:
- AI usage among investment professionals is demonstrating traction but early days; the surveyed buy side and sell side assign various levels of significance at this time
- More than two-thirds utilize AI for market and company research, while efficiency and data-driven information access mark top benefits; ChatGPT prevails as a clear platform favorite, though many are utilizing proprietary systems
- Complexity and reliability concerns are dragging on AI adoption, and over one-third report firm-level restrictions
- Opportunity is seen for public companies to leverage AI for enhanced communications and targeted disclosures
But what about AI’s role in public companies and specifically investor relations?
At Corbin, it’s a pressing question. In fact, across the whole of investor relations, the industry is experiencing a renaissance moment, and it’s left many thinking the same question: what’s really going on?
At this point in 2024, issuers and individuals alike are familiar with the deluge of emails promising the latest “AI Tips and Tricks.” In fact, this overwhelming interest is not just anecdotal; Google Trends1 data shows that searches for AI have sustained unprecedented heights this year.
However, separating the wheat from the chaff to discern both insightful and actionable practices is no easy task. In today’s piece, we aim to do just that. This week, we’re going to focus our analysis on detailing trends and use case examples of AI impacting investor relations with commentary from professionals tooling with solutions today.
AI adoption in investor relations is still in its infancy. However, practical use cases that can be applied to your next earnings call, for example, are not only bubbling to the surface, but actively being evaluated and put into practice today. Moreover, new opportunities ripe for adoption are being imagined daily. For IR professionals, the altitude is elevating, and it is incumbent upon us all to stay up to speed on novel ways to responsibly (and securely!) leverage AI technology to make way for more meaningful interactions with The Street.
Let’s dive in!
Corbin Advisors’ Artificial Intelligence Survey – Findings & Insights
Methodology and Approach
To evaluate emerging corporate perspectives, we surveyed2 46 investor relations professionals across a variety of market caps and sectors. Importantly, participants encompass a wide breadth of experience levels and age groups.
Key Findings
Our comprehensive analysis reveals several notable themes:
1.
AI Adoption Is In Its Infancy, Though 51% Are Evaluating Its Integration At This Time; Investors Are Increasingly Exhibiting Curiosity in Meetings
More respondents, 38%, indicate they are not using AI in IR functions at this time; however, 51% are evaluating AI’s potential integration and overall sentiment suggests a strong interest in exploring practical applications.
At the same time, the investment community is playing a pivotal role in proliferating this trend with 38% noting investors are asking about AI during meetings, with queries ranging from AI’s influence in identifying market opportunities and new products to how teams are leveraging the technology to drive operational efficiencies.
“AI is a priority to explore. However, it must [be] done within the right parameters (maintaining confidential information) and in compliance with company policies.” Mid-cap, Technology
“AI has been good for creating efficiencies by doing work to free team members up to focus on higher-level strategic items.” Large-cap, Healthcare
“We have not officially started exploring AI in IR, but it is on the roadmap for FY’24.” Mid-cap, Technology
“I have not seen anyone publish a roadmap or even try to solicit me with a roadmap of how to deploy AI.” Mid-cap, Energy
“Investors are asking about 1) the market opportunity, 2) its incorporation into products, and 3) its incorporation into internal processes.” Large-cap, Technology
“Investors are asking about if there are plans to incorporate AI both internally and through product development.” Large-cap, Technology
2.
Three-Quarters Have Or Are Actively Considering Utilizing AI For Investor Communications, Such As Prepared Remarks And Press Releases, While Efficiency And Ideation Are Touted As Leading Benefits; ChatGPT Is A Runaway Favorite
In terms of AI use cases — both idealized and realized — three-quarters point to investor communications, specifically earnings scripts and press releases, and 43% and 38% cite sentiment analysis and competitive intelligence, respectively. That said, market research, data analysis, and investor targeting are budding areas.
In terms of overarching benefits, efficiency, speed, and productivity registered universally, largely in line with investment professionals (96%), followed by roughly two-thirds and one-third citing ideation and drafting capabilities and AI’s ability to process large amounts of data, respectively.
In terms of the AI platforms and programs, most point to OpenAI’s ChatGPT, in line with investment professionals, followed by AlphaSense. Other solutions garner less concentration overall. One-off mentions include BloombergGPT, Anthropic’s Claude, Microsoft’s Copilot, NotionAI, and Google’s Gemini.
3.
While Data Privacy And The Technology’s Novelty Are Of Paramount Concern, Governance Protocols Are Being Established And 20% Report Having Customized Platforms For Internal Use; 30% Report Company-Level Restrictions
Still, concerns and hurdles are front of mind throughout responses. Topping the list of challenges are data privacy concerns and the fact that AI is still “too new”, each cited by 58%. In third place, cited by half of all respondents, lack of understanding and complexity is proving troublesome. Notably, this was the number one challenge cited by investment professionals.
At a company-level, over one-third, 35%, note that their organizations have governance protocols or policies on the responsible use of AI. Moreover, 30% also cite some degree of company-level restriction surrounding AI platform usage, just below that of investors and analysts (35%).
Still, 22% report their organizations have customized AI platforms, also in line with investment community professionals. Several note they are evaluating “closed loop” systems or “testing beds” for employees to utilize when handling proprietary information.
“Our company is piloting enterprise versions of Microsoft AI software. In the meantime, public AI engines are blocked to reduce confidentiality risk.” Large-cap, Industrials
“We are not supposed to use public tools for work-related items. We’re evaluating closed loop corporate solutions.” Large-cap, Healthcare
“Risk of MNPI exposure is too high until the security elements are worked out.” Small-cap, Industrials
“We have types of use outlined. There is a permission tree.” Mid-cap, Technology
“We are limited to use case-specific restrictions.” Mid-cap, Technology
“Employees are not allowed to use open-source tools. That said, IT has set up a generative AI testing bed for employees.” Large-cap, Technology
4.
IR Professionals Are Actively Upskilling And In Conversation With IT Departments, As The Intersection Between AI And IR Comes Into Focus
In terms of preparing for AI adoption in IR functions, 65% of professionals point to education and training modules as the primary step. Notably, half assert they are collaborating with their IT department, recognizing that the successful implementation of AI in IR often hinges on a seamless integration with existing technological infrastructure and company-level security protocols.
Other prominent steps include third-party consultation (40%), pilot projects (35%), and collaboration with legal (35%).
For our clients, we’ve thought deeply about AI — both present applications as well as impending impacts — on the investor relations industry. AI, around for nearly seven decades, is going through a revolution and as many benefits as there are, the technology brings its own set of challenges. These factors must be navigated in lockstep with technological implementation to ensure safeguarding your company’s interests and security.
As such, we are providing key considerations for clients from Part 2 of our inaugural Artificial Intelligence Survey.
Explore Customized AI Platforms for Secure, In-House Use in Collaboration with IT and Legal
Considering the concerns around data privacy and the handling of material non-public information, corporates should investigate the possibility of developing or subscribing to customized AI platforms that offer enhanced security features for in-house use. Such platforms can be tailored to the specific needs and workflows of IR teams, incorporating features like competitive intelligence and sentiment analysis within a secure environment.
As previously noted, 22% of those surveyed have explored such solutions, and we expect that percentage to grow. Working closely with IT and Legal departments, IR professionals can explore the development of ‘closed loop’ AI systems that securely process and are, in part, trained by internal and market data for insights based on historically public and/or internal company information.
Leverage AI to Prep for Earnings
IR teams can use AI tools like ChatGPT to refine management-prepared remarks, support Q&A development, and check for alignment and disconnects.
- Use Case: In a secure environment, upload prior company and competitor earnings transcripts, sell side preview notes, minutes from recent investor meetings, and the draft earnings script and prompt the system to anticipate the types of analyst questions that will be asked, as well as proposed answers based on the data provided.
- Use Case: In a secure environment, upload key earnings materials and prompt the system to test different versions for clarity, impact, and/or discrepancies.
A tangible, real-life example of where this could have been implemented is the recent and widely publicized Lyft earnings kerfuffle, in which the press release included an extra zero indicating a “500 bps” EBITDA margin expansion rather than the intended “50 bps,” causing the stock to surge and then dramatically reverse course after restatements were made. After uploading the press release, earnings script, presentation, and supplementals, a simple prompt in a secure system as demonstrated below would have saved the company from a public relations crisis.
Example: Lyft (Technology, $8.2B) Q4’23 Earnings:
The Next Generation of Analysis is on Your Doorstep: Get Creative!
Next-gen analysis tools powered by AI are redefining how corporates approach complex tasks and strategic planning. These tools, including the likes of ChatGPT, offer an unparalleled ability to process vast amounts of data, identify trends, and provide actionable insights in a fraction of the time required for traditional analysis.
- Use case: Quickly and effectively analyzing the latest SEC rules surrounding emissions disclosure. Reviewing an 887-page regulatory document is a daunting task by any standard, but with an AI tool, one could start by comparing the regulation’s requirements against its company’s existing sustainability report, prompting the system to identify alignment and gaps, as well as suggest areas of focus to ensure compliance and strategic positioning. While certainly not a substitute for formal compliance reviews by legal, this process saves a significant amount of time for IR departments in terms of external positioning and potential investor inquires. It also enables a proactive response to potential challenges and can be a good way to spark internal discussion and accelerate action.
Prepare for Increasing Investor Inquiries on AI Utilization
As AI is increasingly integrated into investor research and decision-making as well as corporate operations and investor relations, investors are beginning to inquire how companies are adopting and leveraging AI technologies. It’s becoming clear that being unaware or not utilizing AI within operations at some level, including IR, may soon be viewed as a disadvantage by the investment community. Therefore, it’s crucial for companies to proactively explore, adopt, and communicate their use of AI technologies.
This not only prepares them for inevitable investor queries but also serves as a forcing function to get aligned internally on how your company is handling this transition. Be sure to check the Thought Leadership Letter To Our Clients piece published earlier this year where we outline seven core elements of leading AI positioning statements with best-in-class examples.
In Closing
We hope you’ve found our Artificial Intelligence Survey, considerations, and use cases compelling and actionable. It has certainly been an interesting research topic to explore, and we will continue to produce thought leadership on this topic. If you have specific questions or areas of interest you’d like us to dig deeper on, please reach out directly. We conduct this research for your benefit, our valued clients.
- Source: Google Trends A score of 100 indicates peak popularity for a given search term. Conversely, a score of 0 indicates that the keyword is experiencing low amounts of interest.
- Survey Timeframe: August 2023 – March 2024