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The Rise of a New Associate
If private equity previously relied on gut instinct, twelve-hour Excel marathons, and interns equipped with endless caffeine and anxiety, today it is certainly bringing a new type of associate into the picture: artificial intelligence. This new employee never sleeps, and brings a very different energy to the traditional finance workflow. At the same time, AI might eventually promote more equalized opportunities, enabling smaller firms to compete within the industry without needing to hire an army of analysts. To explore this transformation firsthand, I sat down with Michael Fieldstone, co-founder and partner at Aterian Investment Partners, and Evan Merzon, an AI engineer, to discuss how AI is affecting their workplaces. Merzon offers the perspective of someone building the tools that firms like Aterian are beginning to rely on, making his insight essential to understanding how AI actually works behind the scenes. In private equity, AI shapes how firms work and what they invest in, and within AI engineering, every aspect of Merzon’s role is rooted in artificial intelligence.
Michael Fieldstone: AI Meets Caution
When conversing with Fieldstone he chuckled at how quickly the private equity industry has started hunting down AI. “If your portfolio isn’t exposed to AI, you’re not seeing great returns,” he said. Private equity firms are now throwing money into the companies building the infrastructure that AI runs on– the construction, data centers, and the system behind its hype. Ironically, although everyone is investing in AI, not all employees are actually utilizing it. “We don’t use it nearly enough,” Michael admitted. According to Fieldstone, the bigger firms have begun using AI’s advanced abilities in identifying and evaluating new investments, but the majority of smaller firms are still learning how to spell ChatGPT.
The potential is huge. AI can analyze markets, identify patterns, and evaluate deals faster than an analyst could ever aspire to. This means fewer midnight marathons and more efficiency or, as Michael put it, “doing more with less.” However, he is not ready to transfer the control. “AI is good for research,” he said. “Not for judgment. Too dangerous.” The human factor— reading a creator’s body language, judging whether a management team can actually execute, sensing when a deal partner isn’t being fully transparent— remains profusely human. You cannot teach intuition to an algorithm.
AI is changing what private equity teams invest in, not how it invests. Firms are shifting toward categories that power AI like data-center infrastructure, energy, chips, and industrial cooling because these areas are exploding in value as AI grows, Fieldstone explained. “If you already own a company, you want to make sure it’s part of those categories.” He continued on to say, firms that dismissed AI two years ago are now struggling to buy a piece of it.
Evan Merzon: Ethics, Medicine, and Machine Learning
Although Merzon works outside of finance, the ethical and practical challenges he faces with AI mirror the ones private equity is just beginning to confront. In comparison to Fieldstone’s caution, I conversed with Evan Merzon, an AI engineer who sees firsthand how artificial intelligence is reimagining another high-stakes field: healthcare. His work in developing AI that detects lung cancer mutations from radiology scans without expensive genetic testing highlights how impactful AI can be when utilized ethically. “It could literally save lives,” Merzon said. For private equity, the takeaway is similar: AI’s value comes from its ability to uncover insights humans miss, whether in medical scans or in evaluating companies and markets. However, he reiterated the same hesitation as Fieldstone. “It’s hard to deploy AI at scale in established industries. The risk of failure is too high.” The implication for private equity is similar: adopting AI too quickly could jeopardize investment decisions if the models misread data, fail under pressure, or can’t adapt to real-world complexity.
Merzon’s realm of work sparks questions that private equity is only beginning to face: ethical boundaries, data privacy, and how much trust to put into AI. “All data has to be de-identified,” he explained, remarking that his company actually bans ChatGPT for privacy protection. Rather, they utilize Microsoft’s safe AI program, demonstrating that even within technologically proficient industries, caution still overweighs convenience.
Both Fieldstone and Merzon agree that AI will not take the place of human intelligence, but will definitely reshape it. Fieldstone forecasts that the larger firms with enough capital to invest in advanced AI systems will have the most significant initial lead. Bigger firms can afford the powerful computing infrastructure, proprietary data, and specialized talent needed to run advanced AI models. Their advantage enables them to analyze deals faster, test more scenarios, and make decisions with greater precision.
However, AI might eventually foster more equalized opportunities, allowing smaller firms to compete in the private equity industry without needing to hire an army of analysts.
The Future: AI as Partner, Not Replacement
When asking what advice Fieldstone would give to students hoping to go into private equity during this AI-powered era, he responded without a pause: “Get to know it. Don’t be fearful. It won’t go away.” Merzon remarked that learning to collaborate with AI, rather than simply copying and pasting from it, is key. He explained that working with AI involves guiding it, checking its work, and making the final decisions yourself.
So no, AI might not replace private equity professionals’ intuition and decision-making, but could replace their coffee. When the AI can review data at 3:00am, people might be able to finally get some sleep!
