AI – A Burgeoning Tool or Just Buzz?
Artificial Intelligence Survey Findings & Insights Part 1 of 2: Investment Professionals
In today’s thought leadership, we’ll be diving into investment community perspectives on artificial intelligence in AI – A Burgeoning Tool or Just Buzz? – part one of our two-week series from our inaugural Artificial Intelligence Survey. Next week, we’ll be continuing this analysis with an overview of emerging corporate AI communication trends and use cases, so be sure to stay tuned!
Setting the Stage
One of the most prolific questions we’ve been hearing from clients is how and to what extent the investment community is leveraging artificial intelligence to augment their investment process and approach. Is this shift akin to a scene from a sci-fi movie, where investors are ensconced behind screens engaging with sophisticated, seemingly omniscient technological analyses that spit out holographic alpha in real time? Or is the reality significantly less dramatic, more grounded in the realm of accelerating and streamlining existing processes? Where will the balance of AI benefits versus risks settle, and is there a middle ground the industry is working toward that we should all be aware of?
Indeed, as much as AI is a subject of intrigue and speculation, it’s equally a matter of practical application. Given the explosion of analyst focus on how companies are leveraging AI over the last two years from earnings calls alone, we thought it would only be fair to put a mirror up to the investment community itself and ask some of the critical AI-related questions that are top of mind from corporates and IROs.
Despite some very real shifts in the way investors are experimenting with AI to augment their investment processes, our analysis reveals that the role of investor relations has never been more important. While AI is far from “just buzz” with very real use cases in place today, it is increasingly spotlighting the value of human-to-human connectivity and communication or, said in its plainest form – trust.
So, without further ado, let’s get into it!
Corbin Advisors’ Artificial Intelligence Survey – Findings & Insights
Methodology and Approach
Key Findings
Our comprehensive analysis reveals several notable themes:
1.
AI Usage Among Investment Professionals Demonstrates Traction, though Investors Assign Various Levels of Significance at this Time
At a high level, more respondents indicate they are not using AI in their investment process. That said, 58% indicated they are evaluating its incorporation or are actively using it within their approach.
Of the 58%, half place a low significance on the tools being utilized today, with just 10% placing high significance. However, more than half, 53%, do say that AI has impacted their decision-making process in some way.
Open-ended commentary varied widely. Opinions ranged from enthusiastic endorsements, with one investor claiming AI is “better than my analysts”, to more measured acknowledgments such as, “it is helping around the margins.” However, what is clear is that those who have begun integrating AI into their processes are discovering varying degrees of utility and value.
AI has impacted my investment decisions in the sense I am able to get to an answer quicker.” Buy Side, $352M EAUM
“AI has helped form a full mosaic, but it has not been the end reason for making an investment and it has not been a hurdle on making an investment. It is helping around the margins.” Buy Side, $7B EAUM
“AI has improved my efficiency and accuracy.” Buy Side, $843M EAUM
“We use AI extremely minimally to evaluate companies, so not zero but close to zero.” Buy Side, $328B EAUM
“AI is better than my analysts!” Buy Side, $583M EAUM
2.
More Than Two-Thirds Utilize AI for Market and Company Research, while Efficiency and Data-Driven Investment Considerations Mark Top Benefits; ChatGPT Prevails as a Clear Favorite, though Many are Utilizing Proprietary Systems
But how, specifically, are investment professionals utilizing AI tools?
Well, the vast majority, 69%, point to market and company research (a common form of “machine learning” that crunches vast amounts of data), though sentiment analysis (largely utilizing “natural language processing” to rapidly evaluate tone and messaging), predictive analytics (a subset of machine learning to forecast future performance), and risk assessment all garner meaningful concentrations.
In terms of overarching benefits, efficiency, speed, and productivity garnered nearly universal acknowledgment, followed by two-thirds citing data-driven investment considerations and half pointing to AI’s ability to process large amounts of data.
Interestingly, absent broad-based standardized reporting or disclosure requirements for public companies in the U.S., AI has been categorized as more of an opportunity for ESG data collection and analysis. Of note, respondents were polled before the announcement of the SEC’s new climate disclosure rules last week, though we have heard anecdotal evidence of investors and executives alike summarizing the 886-page document with AI!
In terms of the AI platforms and programs used, a clear emphasis is being placed on OpenAI’s ChatGPT, though 41% indicate using a proprietary platform, such as an enterprise-level solution. Said another way, in-house resources customize AI tools to fit specific investment strategies and company requirements through a combination of blending publicly available AI resources (like ChatGPT) with proprietary data, policies, and large language models (LLMs).
Continuing, widely recognized tools like Microsoft’s Copilot, Bloomberg’s AI integrations, AlphaSense, and, to a lesser extent, Google’s Gemini are cited. That said, despite relatively large levels of concentration in some of the aforementioned tools, participants cite nine other solutions and providers2 as one-offs, demonstrating we are still in the early innings of exploring this space.
3.
Complexity and Reliability Concerns Drag on AI Adoption, and Over One-Third Report Firm-Level Restrictions
Still, several caveats regarding the use of the technology are identified.
First and foremost, lack of understanding and complexity is a notable hurdle, cited by 38%, with slightly fewer, 36%, reporting taking a “wait-and-see” approach as the technology develops. Moreover, 27% point to reliability issues, as systems will often “hallucinate” results and report them back to the user as fact or with little citations. One-quarter of those surveyed also believe cybersecurity concerns represent a privacy issue.
Other prominent concerns include cost of implementation (20%), lack of human touch (15%), and bias (11%), the latter of which Google’s Gemini grappled with publicly over the past month.
“I do not trust it and do not know how to use it. I am stuck in my old-fashioned ways. I fear it might become apparent to people at a certain point that something has changed in the tone or the quality of my work that would indicate I am not doing the work myself anymore. The language may be different or somehow it may not be as insightful.” Sell Side
“One concern is there is a learning curve, though it can make me more efficient once I get used to the technology and utilizing it. Another concern is because of not knowing it, it makes it difficult to hand over anything core to our business and reputation to an intelligence that may not be 100% accurate and proven at this stage.” Sell Side
“Cybersecurity concerns and the technology itself are keeping me away from AI. The technology needs to advance a little more but it has some potential.” Buy Side, $455B EAUM
“At some level, I do not believe it will ever work. I can imagine certain kinds of investing that might be able to replicate it. AI can do a lot of things but I am not sure it will ever predict the future, so I am skeptical on that one.” Buy Side, $74B EAUM
At a firm-level, nearly one-quarter note that their organizations have policies on leveraging AI platforms internally, with roughly the same amount indicating they have customized in-house platforms. Several note that policies and solutions are currently in the discussion phase.
To that end, 35% do cite some degree of firm-level restriction surrounding AI platform usage, with limitations ranging from AI being “completely disallowed” to constraints on inputting proprietary documents.
“It’s completely disallowed. They’re terrified proprietary information will be released.” Buy Side, $342B
“We need prior authorization for utilization to produce any work product. [AI] is restricted to those we allow, and no firm / investor / investment-level information can be shared.” Buy Side, $576M
“No direct connections to ChatGPT, limitations on loading internal documents.” Buy Side, $328B
“Things like ChatGPT, while I use it to play around with, are banned from being used inside our firewalls, so that says volumes about what my parent company thinks of letting AI in the door. I am sure they will eventually.” Buy Side, $74B
“AI policies are currently under evaluation.” Buy Side, $23M
“My firm does not have a specific policy on leveraging AI platforms internally, but it is being discussed.” Buy Side, $5B
4.
Opportunity Seen for Public Companies to Enhance Communication Via Sentiment Analysis and Robust Disclosure
In terms of what the investment community sees as opportunities for public companies, 77% believe sentiment analysis is the leading application of AI for corporates to leverage to improve the overall quality of shareholder communications, followed by enhancing the robustness of disclosure (44%), conducting trend analysis (40%), and implementing IR chatbots (33%), which can be used to automate and carefully facilitate some of the more “routine” communications between a company and its investors, such as questions around dividend policies, earnings timing, quiet periods, etc.
Our results reveal artificial intelligence is indeed impacting the way a growing portion of the investment community work and function. While the significance of the technology’s impact is still early days, our research finds investors and analysts are keeping a watchful eye on the evolving tools, capabilities, and use cases.
Key takeaways for clients from our inaugural Artificial Intelligence Survey:
AI-Enhanced Decision-Making Is Creating a Premium on Human Connectivity
While AI is influencing investment approaches by increasing efficiency, the core of investment decision-making — trust — remains sacrosanct. Improving the speed and efficiency of investment processes and decisions has always been paramount for investment professionals, but not at the expense of making bad decisions or violating internal compliance. Asset managers are adopting a range of AI technologies like machine learning, predictive analytics, and natural language processing, but the human element, namely meeting directly with management, remains pivotal for engendering trust in the investment opportunity and building relationships.
Proactive Adaptation and AI Literacy are Crucial
Corporates must proactively adapt to the rapidly advancing AI landscape by developing AI literacy. This entails a twofold approach: first, by understanding the nuances of AI-driven investor strategies as they evolve; and second, by using this knowledge to inform and evolve investor relations practices and communication. For example, are there specific pieces of information that investors are prioritizing through AI analysis, such as disclosure items, ESG factors, or market trends that are influencing their investment decisions? Stay apprised of how AI tools commonly used by the buy-side portray your company, its news flow, sentiment, and fundamentals and seek to explicitly communicate, clarify, and emphasis that information on the corporate website.
- Implement comprehensive training for management and investor relations teams to enhance their understanding of AI tools and methodologies.
- Engage directly with investors to understand how they use AI in their decision-making process. Use this feedback to align corporate communications and disclosures with investor priorities. For example, include webcast transcripts on the website versus audio-only to enable investors to easily access this piece of information, and/or consider incorporating written FAQs on the IR website.
- Conduct regular audits on how AI tools are interpreting and representing your company’s financial health, ESG initiatives, and market position. Use these insights to correct any misrepresentations or unintended perceptions. For example, after feeding your prepared remarks from the last quarter’s earnings transcript into a system such as ChatGPT, what does the system believe are the key takeaways and questions investors may have? How do those differ from your own conception?
- Tailor communication strategies to emphasize the company’s strengths and address potential areas of concern that AI may flag. This could involve more detailed and explicit discussions of strategy, operations, and risk management in earnings calls and investor presentations.
Role of the IRO Will Become Even More Strategic
It is more important now than ever before to understand how investors think about your company, why they have those views, and how you can strategically communicate to shareholders to increase your valuation multiple. While AI is certainly assisting some of the busy work happening on The Street, we are in the early days and, according to our findings, investors are exhibiting reluctance to rely on these tools in their own right. However, as the technology improves and investment professional become more comfortable with the outputs, IR professionals will be left to focus on the things that matter most.
- For example, one-third of investment professionals, unaided, identified “IR chatbots” as an opportunity for companies to automate portions of the IR function. In its ideal form, this will enable face-to-face interactions to be more meaningful and impactful.
- Additionally, 28% of respondents supported the idea of using AI for anticipating questions and answers. This proactive approach can enhance preparedness and responsiveness, allowing IR professionals to address investor queries proactively and more accurately, freeing up earnings calls and conversations for more strategic discussions.
In Closing
We hope you found the first installment of our Artificial Intelligence Survey — views from the buy side and sell side — interesting and insightful. As mentioned, next week we’ll cover the corporate perspective.
- Survey Timeframe: August 2023 – March 2024
- Responses include BERT, Claude, FactSet, Homebase GPT, JLL GPT, RavenPack, Scite, and Sudowrite