How to Hire an AI-First CTO

An AI-first CTO is a technology leader who is actively reshaping the product, platform, and data architecture around AI, not treating it as a feature for next year's roadmap. For private equity sponsors, that raises a question most portfolios are facing right now: can the current CTO make this shift, or does the company need to upgrade the role?

Why the role is changing now

The CTO job at software companies is being rewritten in real time. In March, Atlassian's CTO stepped down and two executives split the role: Taroon Mandhana, formerly head of engineering for AI and products, became CTO Teamwork, and Vikram Rao, previously chief trust officer, became CTO Enterprise and Chief Trust Officer. The change came alongside roughly 1,600 job cuts, more than 900 in software R&D, to fund further investment in AI and enterprise sales.

We live in a world where software can now be built cheaply and quickly by competitors, startups, or customers themselves, and AI agents doing people's work are reducing seat counts. Pricing is following: pure per-seat pricing is down to about 15% of SaaS companies, with hybrid models gaining ground

Most PE portfolios are behind that curve. In FTI Consulting's 2026 survey of fund and operating leaders, only 36% said portfolio companies use AI in day-to-day operations, and 7% called it fully integrated. That gap is an uncomfortable place to sit, and pressureis landing on CTOs.

The two profiles that fall short

When companies look at the CTO role today, whether evaluating the incumbent or searching for a new leader, they tend to anchor on one of two profiles.

The first is the proven engineering operator: strong on delivery, trusted by the team, and trying to move AI from a side project to the main event, usually with the same playbook that built the current product.

The second is the AI specialist: technically impressive and often already building models, but still learning to run a large engineering organization, live with legacy systems, or defend a budget in front of a board.

Both have their place. Neither is enough on its own. The AI-first CTO does the work of both and understands the business well enough to point AI at problems customers will pay to solve.

Sponsors make a version of this mistake with incumbents, too. Some assume the current CTO will grow into the role. Others replace them reflexively without testing whether they can. Both are expensive.

What makes a CTO AI-first

Whether you're evaluating your current CTO or a candidate, four things set AI-first leaders apart:

• They start with data. Before any model conversation, they want to know what data exists, how clean it is, and who owns it. AI built on bad data is a demo, not a product.
• They manage AI as a cost line, not just a capability. They know what each AI feature costs to run, where it earns its keep, and when to use a smaller model, a vendor, or no AI at all.
• They're rebuilding how their own team works. A Q1 2026 developer survey found engineers using AI tools now spend more time reviewing generated code than writing new code. AI-first CTOs redesign roles, review, and quality control around that shift instead of just buying tools.
• They measure in business terms. Adoption, retention, margin, and revenue, not features shipped.

The AI-first CTO also differs from a Chief AI Officer. A CAIO usually owns AI strategy and governance across the whole company. The AI-first CTO owns the product and platform. At the largest companies, as Atlassian shows, the role is splitting in two. In most mid-market software companies, there's budget for one leader, and it's usually the CTO.

Upgrade, augment, or replace

Evaluating your CTO doesn't have to end in a binary choice. There are three realistic paths.

Upgrade. The CTO has sound judgment and the team's trust but hasn't led AI work yet. A clear mandate, board backing, and sometimes an outside advisor can close the gap.

Augment. The CTO is a strong operator but not the right person to lead AI. Adding a senior data or AI leader with real authority often works better than a replacement.

Replace. The AI plan is central to the thesis and the incumbent can't lead it. Waiting costs more than moving, especially inside a short hold period.

The right answer depends on the thesis, the timeline, and the person. What matters is making the call deliberately, and early.

Before the deal, or right now

If AI is part of why you're buying a company, the technology leader is part of the diligence. Many sponsors wait until after close to find out whether the current CTO can carry the AI plan. By then, a year of the hold may be gone.

The same questions apply to companies already in the portfolio, and most sponsors haven't asked them yet:

1. Can the current CTO lead an AI-driven roadmap, or only maintain the existing one?
2. Is the data foundation ready, or will the next year go to cleanup?
3. If a new or additional leader is needed, who's actually available, and at what cost?

The answers affect the value creation plan, the timeline, and sometimes the price.

What the next 12 months should look like

Whether it's the incumbent resetting the roadmap or a new leader coming in, the next year is less about launching AI features than making AI work at scale: fixing the data, choosing a platform direction (especially where add-on acquisitions have left several products stitched together), moving AI from scattered features into the core product, reworking pricing where seats no longer track value, and reshaping how the engineering team builds now that AI is part of the development process itself.

Sponsors should expect visible progress within the year, but judge it on foundation and focus, not feature count.

How we assess AI-first CTOs, incumbent or candidate

Titles don't tell you much. The role is still taking shape, and few people have held it for long. We look for:

• Recent AI in production. What they've shipped in the past year, what it did for customers, and what it costs to run. Pilots don't count.
• Data judgment. Given a product with fragmented data, do they start with the data or the model?
• Cost discipline. Can they tell you the unit economics of their AI features, and what they've done to improve them?
• Restraint. An AI project they stopped or chose not to start, and why.
• Board fluency. Can they explain an AI investment in cost, timeline, and margin terms?
• Change leadership. How they're changing the way their engineers work with AI, and keeping quality up as output rises.

In practice: Minitab

We recently supported the search that brought Kevin Gordon to Minitab as CTO, a case where the company chose a new leader to drive the shift. Minitab has decades of trust as the standard in statistical analysis, and it described Gordon's arrival as coming at "a moment when Minitab knows it must transform." The brief combined platform unification, deeper AI integration, and a customer base that relies on the product's rigor. That combination is the AI-first CTO role in one mandate.

FAQ

What is an AI-first CTO?

A CTO who is reshaping the product, platform, data architecture, and engineering team around AI, and is measured on business results rather than features shipped.

Is an AI-first CTO the same as a Chief AI Officer?

No. A CAIO usually owns company-wide AI strategy and governance. The AI-first CTO owns the product and platform. Large companies are starting to split the role; mid-market companies usually need one leader to carry it.

How do you know if your current CTO can become AI-first?

Look at what they've shipped with AI in the past year, whether they know what it costs to run, and whether they can explain an AI investment in business terms.

How long does an AI-first CTO search take?

Most of our AI-first CTO searches usually take 10-12 weeks, but depend on the mandate or scope.