July 31, 2023 – By now, everyone’s heard both ample hype and ample skepticism around the topic of AI, as well as predictions for how it will either jump-start or ruin our economy (or both), with plenty of sector-specific considerations, many of which are all equally speculative.
What is clear is that AI is a hot topic and one that will continue to receive ample press coverage and mindshare over the next several years, according to Chase Harrison, senior partner at Kingsley Gate. “Perhaps most notably, AI is not likely to be like NFTs or the Metaverse, two trends that, despite their dominance in 2021, seem to have lost steam over the past several quarters,” he said. “Private equity, growth equity, and venture investors are keenly aware that this advancement in technology could yield tremendous value creation opportunities, but we anticipate that successfully navigating this new field will prove challenging for private equity firms in the short term.”
Defining What is AI vs. Not AI
Mr. Harrison says that one of the most challenging aspects of AI is that no single accepted or official definition of it exists. A headline from GCN states: “There [are] about as many definitions of artificial intelligence as there are researchers developing the technology.” Are calculators AI? What about personal computers? What about Microsoft Excel?
There are many terms being used and abused in this space — from AI, to deep learning, to machine learning, to neural nets, to computer vision, Mr. Harrison notes. “One question that many have struggled to answer is whether or not certain techniques that make existing quantitative models better (be they propensity models or other forms of predictive analytics) are necessarily AI,” he said. “They might just be simply that – better predictive analytics.”
According to The Verge, for years a lot of our technology was receiving inputs from us and acting on them in a formulaic way. Now, artificial intelligence is being trained through watching, listening, or absorbing – and is learning how to act on its own. “The extent to which this learning successfully takes place, however, remains to be seen,” Mr. Harrison said.
Specific Applications to Private Equity
Investors will look to accomplish three objectives to capitalize on the opportunity presented by AI, according to Mr. Harrison. “First, they’ll try to acquire target companies that specialize in AI, whether that be AI for a certain vertical (e.g., healthcare), AI for a certain function (e.g., risk), or AI for a certain capability (e.g., types of generative AI),” he said. “Second, they’ll try to encourage their existing portfolio companies to adopt AI techniques to enhance performance outcomes (e.g., growth, profitability, cash flow). Third, they’ll try to use AI themselves in conducting their business as investors. Regarding potential investment targets, Forbes warns that investors who lack technical knowledge may end up making the costly mistake of taking a target company’s claims of inflated business impact from AI at face value. They break down three distinct types of profit proximity (from the most to least proximal): AI that touches customer behavior, AI that improves products, and AI as a reputational driver.”
Chase Harrison is a senior partner with Kingsley Gate Partners. He brings a decade of experience in executive search having placed executives across various industries and functional areas. Mr. Harrison has substantial experience serving the C-suite, recruiting senior-level leadership.
“If last quarter’s message from Big Tech was all about efficiency and bottom line improvement, this quarter’s message is likely to be more forward-looking around the massive potential of artificial intelligence,” said Yahoo in a recent report, referencing publicly traded companies,
“But we believe that investors (whether public or private) shouldn’t have to choose between profitability and the promise of AI innovation. To do so seems to somewhat miss the point,” said Mr. Harrison. “Private Equity International has covered the potential appeal of AI from the LP’s perspective, not just as an important capability at the portfolio company level. They ask, ‘How can AI be used to identify attractive primary fund propositions? Or to price a secondaries stake? Or to determine what makes a good co-investment deal?’”
Talent and Leadership
Mr. Harrison says that for the foreseeable future, human talent is required to manage AI capabilities and get the most out of them. Eventually, AI itself might be able to execute those functions, as anyone who’s ever asked ChatGPT to generate ChatGPT prompts knows. When Kingsley Gate Partners helps private equity firms assess talent in this space, they consider five specific dimensions:
1. Pure Experience
First and foremost, AI engineers or data scientists — or business managers who are going to be overseeing technical AI talent — need to be able to do the job they are hired to do, says Mr. Harrison. “Typically, this means having the right set of quantitative skills, tool familiarity, and domain expertise,” he said. “Those qualifications, however, may reveal themselves through a wide variety of different past experiences. This is particularly true when thinking about potentially game-changing talent from across industries. While we may think that AI applications for healthcare have nothing to do with applications in energy, retail, or financial services, the truth is that AI, like all functions or capabilities, can be immensely transferable across sector lines.”
2. Business Acumen
“One highly differentiating trait of top AI talent is the ability to translate the technical into business terms,” Mr. Harrison said. “To the above point about cross-industry transferability, this may require a bit more attention paid and/or time invested if an organization is onboarding talent from another vertical. But even speaking the general business lexicon of profit, cash flow, cost of capital, NPV, etc. can be extremely valuable in a world where many engineers are not able to do so. While business managers who oversee AI are often responsible for translating, their job becomes significantly easier when technical talent brings a high level of strategic business capability to the table.”
Why Companies Miss the Most Important Factor in Executive Hiring
Surprisingly, the ability to make effective, timely decisions is often overlooked in leadership candidates. As companies search for new senior executives to navigate in these uncertain times, this skill is critical. In a new report, Kingsley Gate explains why this “missing piece” is so important in hiring strategy. The firm found that a quarter of senior executives say they were not asked about their decision making capabilities at interview stage and only around a third (36 percent) say that their decision making style aligns with that of their organization. There is also evidence to suggest that, even when asked about decision making, senior executives are not pressed to elaborate on their approaches to the process and thinking behind their decisions.
3. Managerial Experience
Managing teams is a difficult and often overlooked responsibility of business managers. “Anyone who is going to be supervising technical talent such as AI engineers or data scientists need to have a grasp on the day-to-day challenges of such a responsibility, which involves more than simply translation from technical to business and back,” said Mr. Harrison. “Assessment of candidates who are intended to supervise AI technicians should zero in on successful approaches to talent management and previous lessons learned.”
4. Ethical Orientation
Despite its importance, one area that rarely gets proper investment or airtime is alignment with new hires on ethics. “AI is such a nascent capability set with new applications materializing every day, it’s impossible to predict the questions that tomorrow will bring,” Mr. Harrison said. “While most firms are able to find broad ethical alignment with their new hires, it’s worth spending time on the nuances or gray areas that would be defensible or misconstrued if strong alignment is not developed from the outset. Understanding the scope of someone’s comfort with AI experimentation, data governance, etc. and comparing that to the organization’s own can be a very useful exercise to undergo before extending an offer.”
5. Fit with Operating Culture
Operators or investors who are excited about AI should not rush into hiring until they understand whether candidates are going to be able to get business done in the way that is congruent with the company’s existing (or desired future) practices. “Even basic norms or components like socialization, communication, collaboration, accountability, learning and development, and citizenship (i.e., initiatives outside one’s day job) are worth discussing in depth before extending an offer,” said Mr. Harrison.
Individual PE investors have little control over the direction AI goes in the future, but savvy investors will create, either directly or indirectly, systems, opportunities, and processes whereby AI capabilities can yield tremendous business value by influencing other levers that affect profitability and growth, according to Mr. Harrison. “For the foreseeable future, we anticipate a fair amount of hype but also some real business opportunities if investors can be disciplined about hiring and ask the right questions about profit proximity,” he said. “In the end, just like the internet, the economy, and the pandemic, we’ll make several incorrect and comically over-confident predictions before we learn, by experiencing it, how wrong we got it.”
Contributed by Scott A. Scanlon, Editor-in-Chief; Dale M. Zupsansky, Managing Editor; and Stephen Sawicki, Managing Editor – Hunt Scanlon Media