The rise of the Chief AI Officer: What it means for private equity
How AI leadership is evolving across private equity portfolio companies
Artificial intelligence has rapidly moved from experimentation to a central part of the value creation agenda for private equity investors. Nearly 80% of organizations now use AI in at least one business function, yet many continue to debate who should ultimately own the strategy, governance and execution of their AI agenda.
AI is creating a new set of leadership requirements across private equity. Investors and management teams need people who can assess where it will improve performance, make decisions about investment and take responsibility for delivery within the hold period.
At Finatal, we’re seeing that requirement translate into different types of appointment. As Jake Grensinger explored in his recent article on AI leadership and execution, our work has included appointing an embedded AI engineer for a portfolio company and an AI Operating Partner at fund level. Those mandates illustrate how widely the scope can vary, from improving a specific finance process to assessing opportunities across a portfolio.
Interest in Chief AI Officers, Chief AI & Information Officers, Heads of AI and AI Transformation Directors sits within this broader shift. The titles are still evolving, and businesses are working out where responsibility should sit alongside existing technology, data and operational leadership.
For investors considering an appointment, the starting point is understanding the work the business needs someone to own.
Where should AI leadership sit?
The right structure depends on the scale of the opportunity, the business’s technology foundations and the capability already in the management team. Four approaches are emerging.
AI within the CIO or CTO remit
For many mid-market businesses, the existing technology leader is well placed to own AI. They understand the systems, data and implementation constraints, and already have relationships across the organization. The question is whether they have the capacity and experience to give AI the attention it requires alongside their existing responsibilities.
A combined Chief AI & Information Officer
Combining enterprise technology and AI leadership can bring investment decisions, infrastructure and delivery under one executive. The search requires careful calibration: candidates need the breadth to run the technology function and credible experience of implementing AI within business operations.
A standalone Chief AI Officer
A dedicated executive can make sense where AI has significant implications for products, services or the operating model. The mandate needs clear boundaries, particularly around decisions shared with the CIO, CTO, COO and data leadership. CEO sponsorship, budget and authority to change processes should be established before the search begins.
A Head of AI or AI Transformation Director
For a portfolio company with a defined set of opportunities, this can be a practical way to create focus and accountability. Reporting into the CEO, COO or CIO will depend on the work involved. The appointment needs access to the people and resources required to deliver, whichever reporting line is chosen.
What should investors look for?
The strongest briefs bring technical credibility and commercial delivery together. An AI leader needs to understand what is feasible within the business’s systems and data, assess whether the return justifies the investment, and work with colleagues whose processes will change.
The financial assessment deserves particular attention. In our reflections on AI Pathfinder’s Private Equity AI Strategy Day, we explored the gap between saving time and realizing a financial benefit. Additional capacity only becomes commercially meaningful when the business can explain how it is being used, whether to support growth, improve service or change its cost base. Technology and implementation costs also need to be included.
That gives hiring teams something specific to test. Candidates should be able to explain:
- Which business problem they took responsibility for and why it mattered.
- What they personally delivered, including the systems and data challenges.
- How they secured adoption from the teams involved.
- How the result was measured and whether the benefit continued after implementation.
Restricting a search to people who already hold a Chief AI Officer title can overlook relevant experience. CIOs, CTOs, data leaders and transformation executives may have built the capability through substantial delivery mandates. Their track record needs to stand up to the same scrutiny.
Where interim AI leadership can help
An interim appointment can be useful when a business has identified an opportunity but needs experienced leadership to establish its scope and begin delivery.
A six to twelve-month mandate could cover an initial assessment, implementation of priority initiatives and a recommendation on the permanent team required. The scope and duration should reflect the business’s readiness and the complexity of the work.
An Interim Chief AI Officer or AI Transformation Director might be asked to:
- Assess data, systems and operational readiness.
- Prioritize opportunities with an agreed business case.
- Lead implementation and adoption.
- Establish governance and financial measurement.
- Build internal capability and plan the handover.
The assessment process should establish how much implementation responsibility the executive has personally held. Investors need to understand what happened after a strategy was agreed, including how the individual handled delays, weak data or resistance to changing established processes.
The role of AI Operating Partners
At fund level, AI leadership has a different scope. An AI Operating Partner can help assess maturity across the portfolio, prioritize investment and determine where individual management teams need support.
Our appointment of an AI Operating Partner for TPA Capital, discussed in Jake’s article, reflects this requirement. Portfolio companies can be at very different stages, with some ready to implement specific initiatives and others needing work on data, processes or governance first.
Central expertise can help a fund make those judgments and share useful experience between businesses. Delivery also requires clear ownership within each portfolio company, with dedicated permanent or interim support where the mandate warrants it.
Our perspective
We expect AI delivery experience to carry increasing weight in CIO, CTO, COO and transformation searches, alongside demand for specialist AI leaders.
A standalone Chief AI Officer will suit some businesses. Others will be better served by extending an existing executive’s remit or appointing a Head of AI or interim transformation leader around a defined program.
Before opening a search, investors and management teams should agree the outcome, the decisions the appointee will control and the resources available to them. A clear mandate makes it easier to assess candidates, establish accountability and judge whether the appointment is delivering the value the business needs.