Goldman Sachs panel says AI investing remains a stock-picker’s market
Maverick Capital’s Ben Silver and David Tykocinski pushed a no-timing, deep-diligence approach that favors company-by-company AI calls over broad hype.
For Goldman Sachs staff parsing the next wave of AI exposure, the takeaway from a June 18 conversation with Maverick Capital co-CIOs Ben Silver and David Tykocinski was blunt: this is still a stock-picker’s market. Their message cut against the idea that AI can be treated as one trade, one theme or one easy bet, and it matters most for the people inside Goldman who have to turn noisy market enthusiasm into actual client advice.
Silver and Tykocinski said Maverick has not changed its basic process in three decades: do not try to time the market, take a long-term view, partner with management teams and rely on deep diligence. That is a useful reminder for Goldman analysts and associates covering AI beneficiaries, software disruption, semiconductors and infrastructure, where the pressure is often to publish fast and sound certain. In this frame, the job is not to match the loudest narrative, but to identify which companies can sustain execution when the hype cycle fades.
The real edge, according to that approach, lies in work that is often invisible to clients until it proves right: understanding where revenue actually accrues, how durable management execution is and which businesses convert AI spending into profit. For research teams, that means more time on second-order effects and less time on blanket thematic language. For salespeople and bankers, it changes the pitch from broad AI enthusiasm to a narrower conversation about which names deserve conviction and why. That is especially relevant in a market still focused on capex and infrastructure, where many companies can claim exposure but far fewer can show durable economics.
The implication for Goldman’s internal priorities is straightforward. A sell-side note or client meeting built around broad AI exposure is less useful than one that separates the companies benefiting from capital spending from the companies merely riding the story. That favors disciplined bottoms-up work, tighter collaboration with management teams and a sharper focus on evidence. In a market that rewards patience and stock selection, the people who can explain who truly turns AI into earnings will be the ones shaping the conversation, not the ones repeating the theme.
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