Why can’t we just hire the Head of AI from ServiceNow?
It’s a question that comes up frequently when Private Equity firms begin thinking about building AI capability at the platform level.
At first glance, it seems reasonable.
But it also reveals why these searches are harder than they appear.
After my post last week on how PE firms are structuring AI capabilities internally, investors asked a follow-up question:
𝗪𝗵𝘆 𝗮𝗿𝗲 𝘁𝗵𝗲𝘀𝗲 𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝘀 𝘀𝗼 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁?
Many firms instinctively evaluate AI talent the same way they would a traditional Operating Partner. However, the dynamics around AI leadership today are different.
𝗪𝗲𝗮𝗹𝘁𝗵 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝗻𝗱𝗼𝘄
Many strong AI operators at high-growth tech companies know they have a relatively short window to create generational wealth.
That tends to keep them in company-building roles where the upside seems clear.
𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝘃𝘀. 𝗮𝗱𝘃𝗶𝘀𝗼𝗿 𝗺𝗶𝗻𝗱𝘀𝗲𝘁
The best AI leaders today are builders. They want to ship products, design systems, and scale teams.
A platform-level AI role inside a PE firm requires a different muscle: diagnosing problems across companies, influencing CEOs without authority, and building repeatable playbooks across the portfolio.
𝗖𝗮𝗿𝗲𝗲𝗿 𝘁𝗶𝗺𝗶𝗻𝗴
Traditional Operating Partner roles often attract leaders later in their careers, when the motivation shifts toward sharing experience across businesses.
AI leadership is earlier in its lifecycle. Many operators are still focused on building companies rather than advising portfolios.
𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻
Senior AI leaders at hyperscalers earn several $M annually, with equity vesting Qly.
Leaders at AI-native startups may accept more risk, but they are in that same wealth-creation window.
There is excellent talent at mid-size public tech companies, but these profiles get overlooked because they aren’t “press release hires.”
Which brings us back to the original question.
Even if you could hire the Head of AI from ServiceNow, the bigger question is whether that person would actually enjoy or succeed in a PE operating role.
𝗧𝘄𝗼 𝗺𝗼𝗱𝗲𝗹𝘀 𝗜’𝗺 𝘀𝗲𝗲𝗶𝗻𝗴 𝗲𝗺𝗲𝗿𝗴𝗲:
𝗧𝗵𝗲 𝗵𝘆𝗯𝗿𝗶𝗱 𝗼𝗽𝗲𝗿𝗮𝘁𝗼𝗿–𝗮𝗱𝘃𝗶𝘀𝗼𝗿
Someone who spent time in structured problem-solving environments (McKinsey) and then moved into hands-on AI or data leadership inside a technology company.
Not the flashiest profile, but comfortable operating across companies and translating strategy into action.
𝗔 𝘀𝗺𝗮𝗹𝗹 𝗮𝗰𝗾𝘂𝗶-𝗵𝗶𝗿𝗲
Instead of one senior executive, bring in a small team of mid-career AI operators from respected software companies (Datadog, Atlassian, Okta, Workday).
People who have seen how scaled software companies are operationalizing AI.
Not the most obvious approach, but sometimes the right mix of technical credibility and pragmatic operating experience.
Curious what investors and operating partners are seeing?
