AI & Emerging Tech Executive Search

The companies powering AI have worked with us for years

Many were our clients in compute, semiconductors, and hardware long before AI led every headline. We have stayed close as they moved into this next phase, so we already know the operators who can lead it.

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1000+ Tech Searches

4.9 out of 5 rating

95% Referral Rate

98% Firm Placement Rate

The Industry

Technical depth and
commercial nerve.

Technology leadership in 2026 demands real technical depth and commercial nerve in one person. Our research found 94% of executives say AI is reshaping the role, yet only 9% rethink that role before they hire for it. Boards that close the gap get a leader built for the job they have now. Reaching that leader takes a partner who already has the relationship.
Source: ON Partners Widening Gap, 2026

Where We Work

Driving meaningful change on a global scale.

Click to see who we've placed, what roles we run most, and what's driving demand right now.

AI & Machine Learning

We have grown with the companies powering AI

Many were our clients in compute, memory, and photonics before AI led every headline, and we stayed close as they moved into this phase. So when you need someone who can build the systems models run on, or turn those models into product, we already know who they are and how to reach them.

Most-placed roles in this industry

Chief AI Officer VP of AI & ML VP of Research Chief Technology Officer

A sample of our work in this area

Cybersecurity

AI has raised the stakes on security

As AI makes attacks faster and harder to catch, a breach now puts data, customer PII, brand reputation, and regulatory standing on the line. We place the leaders building the teams that protect all of it, across detection, identity, and data protection.

Most-placed roles in this industry

VP Security Engineering CISO Head of Product Chief Technology Officer

See our work in IT, Security & Risk

A sample of our work in this area

Data & Analytics

Data became a revenue question

What was once governance and reporting is now where companies expect growth, and AI has raised what the data has to deliver. We know the operators who turn data into a business advantage, and our relationships across the market mean we can introduce you to the right one.

Most-placed roles in this industry

Chief Data Officer Chief Analytics Officer Head of Data Science VP of Business Intelligence

A sample of our work in this area

Robotics & Automation

From the lab to volume deployment

Plenty of autonomous systems work in a demo. Far fewer reach real deployment and revenue, where hardware, software, and commercial execution all have to hold together. We know the leaders who have made that leap, because we have worked alongside them and the companies backing them.

Most-placed roles in this industry

Chief Executive Officer Chief Commercial Officer VP of Engineering Chief Technology Officer

A sample of our work in this area

SaaS & Cloud

Thousands of Searches

Software is one of our most active sectors, from B2B SaaS and cloud platforms to developer tools, much of it for PE-backed and venture-backed teams scaling past founder-led growth. After thousands of these searches, the operators who have done it before are already in our network.

Most-placed roles in this industry

Chief Revenue Officer Chief Product Officer Chief Technology Officer Chief Marketing Officer

Visit our Software & SaaS practice

A sample of our work in this area

Semiconductor & hardware

AI put hardware back at the center

Semiconductors and hardware is where ON Partners started. Before AI made chips a household conversation, before reshoring became a national priority, we were running searches for the engineers, operators, and commercial leaders who built the industry. That history matters because we don't just know the space, we already know the people.

Most-placed roles in this industry

Chief Executive Officer Chief Operating Officer Chief Technology Officer VP of Sales

See our full semiconductor & hardware practice

A sample of our work in this area

The Leadership Landscape

What your peers are dealing with in
AI & emerging tech

The executive leadership challenges in this industry are moving faster than most anticipated. Here's what's actually driving search activity right now and what it means for the leaders companies need.

The Challenges

Talent exists. Closing them is the problem.

The executives who have shipped production AI at scale, sold enterprise automation into Fortune 500 accounts, or built a semiconductor commercial organization from scratch are identifiable. They're just not looking, and they're already getting 10–15 approaches a month.

75% of executives say market uncertainty is actively slowing leadership movement
Chief AI Officer role has no established talent pipeline
The best candidates receive 10–15 approaches monthly
Off-limits conflicts at large firms shrink your candidate pool
Long processes lose candidates to faster competitors

The Opportunities

The companies that move first are building durable advantages.

AI is not a feature. It's becoming a platform for how companies compete. The organizations hiring the right leaders now are compressing the time it takes to build real AI capabilities. That head start is worth 12–24 months of competitive lead time.

AI-native companies can attract operators from Big Tech
PE-backed companies can move faster and offer equity upside that public companies and hyperscalers cannot match
The first CMO or CDO can define an entirely new category
40% of C-suite leaders say AI fluency is the #1 leadership capability needed in the next 3–5 years. Those companies hiring for it now are 12–24 months ahead

What's Changing

The definition of a "good tech executive" is being rewritten.

The CTO hired in 2019 may not be the right leader for 2026 and the CISO hired before AI-driven threats emerged is already behind. Role expectations are shifting faster than careers can keep up and the gap between who is in the seat and what the seat now requires is widening every quarter.

57% of organizations have no ready successor for critical leadership roles, according to our Leadership Clock Report
CTOs must now have a credible AI strategy, not just roadmaps
AI has expanded the attack surface faster. Model poisoning and deepfake-driven social engineering are now board-level threats.
CDOs are being asked to generate revenue, not just manage data

Common Questions

What leaders may ask before a search

What should I look for in a Chief AI Officer?

The Chief AI Officer role is one of the least standardized titles in the C-suite, which creates a significant hiring risk: companies end up interviewing candidates whose definitions of the role bear no resemblance to each other or to what the company actually needs.

Start with what problem you're trying to solve. There are three distinct archetypes:

The Builder: has shipped production AI systems at scale. Comfortable at the infrastructure and model layer. Ideal for companies building AI capability from scratch.
The Strategist: translates AI potential into business initiatives and board-level roadmaps. Ideal for enterprises in early transformation.
The Commercializer: takes an existing AI product and drives revenue from it. Ideal for companies with working technology that hasn't found its GTM motion.

Beyond archetype, the non-negotiables are: genuine hands-on understanding of how large language models work (not just the ability to discuss them at a conference), a track record of cross-functional leadership, and the ability to manage expectations from a board that may be oscillating between hype and skepticism.

How ON approaches it: We begin every CAIO search with a role alignment session between the partner running the search and the hiring committee; before we write a single candidate profile. Getting this wrong at the definition stage is how searches fail at the offer stage.

How is hiring a CTO for an AI company different from a traditional software company?

The most important difference is what "technical leadership" means at each type of company. At a traditional SaaS company, the CTO builds engineering culture, manages architecture decisions, and scales a team. At an AI company, the CTO must also have credible opinions on model selection, fine-tuning approaches, inference optimization, and AI safety - and must be able to evaluate researchers and ML engineers whose work they need to understand, not just manage.

The second difference is the speed of external change. A SaaS CTO's technical landscape is relatively stable. An AI CTO's landscape changes materially every six months. The role requires someone who is not just current but genuinely ahead — actively tracking foundation model developments, regulatory changes, and competitive technical moves.

AI CTOs need ML credibility in addition to engineering leadership
Candidate pool is meaningfully smaller than for SaaS CTOs
Compensation benchmarks differ significantly
Role expectations from investors vary by stage and sector

ON has placed hundreds of CTOs across technology sectors and can benchmark AI-specific CTO profiles against our full database of placed executives — including performance outcomes where available.

When is the right time to hire a CISO?

Almost certainly before you think you need one. Most companies hire a CISO reactively - after a breach, after a large enterprise customer demands one as a procurement requirement, or after a board member asks the CEO who owns this. Each of those moments is a worse time to search than the moment before them.

The structural triggers: a CISO becomes necessary when any of the following apply:

You are processing data that creates regulatory exposure — HIPAA, SOC 2, GDPR at scale
A breach would materially harm revenue, customer relationships, or fundraising ability
Your board has added a risk or audit committee or is preparing to
You are entering enterprise sales and prospects are asking about security posture
You are post-acquisition and the acquiring PE firm requires a security function
SEC rules now require public companies to disclose material cybersecurity incidents within four business days — executives who don't own that definition are a governance liability

The AI-specific case is now urgent for any company deploying AI in customer-facing applications. Model poisoning, adversarial inputs, deepfake-driven social engineering, and data extraction are not theoretical risks — they are active attack vectors that most CISOs hired before 2023 were not hired to manage. The question isn't just whether you have a CISO. It's whether the one you have was built for this moment.

Post-breach CISO searches are among the most pressure-tested searches we run. The companies that call us after a breach always say the same thing: they wish they had built the relationship before they needed it.

How do I know if my retained search firm has real AI sector depth?

Ask questions like:

"How many CAIO or AI leadership searches have you completed in the last 24 months?" A firm with genuine depth can give you a specific number and describe the searches. A firm without it will give you a category answer ("we've worked across technology broadly").
"Who are the off-limits candidates in AI, and how does that constrain this search?" Every firm has off-limits. The size of that list in AI tells you how committed they are to this sector — and how constrained your candidate pool will be.
"Who on your team will run this search, and what is their direct experience in AI?" A large firm will often have sector expertise in the practice but assign the search to a consultant who is newer to the vertical. At a partner-led firm, the person you meet is the person who works your search.

At ON Partners, every search is run by a partner from day one to close and we aren't handcuffed heavily by off-limits. You can ask the partner running your AI search what they've placed before, and they can tell you, specifically.

What executive roles most accelerate AI transformation?

The executives that create the most leverage in an AI transformation are not always the ones companies hire first. According to the ON Partners Leadership Clock report, 31% of executives cite rapid role evolution due to AI as their number one barrier to succession planning — which means most organizations are already behind on the leadership decisions that matter most.

Based on what we have seen across thousands of technology searches, the highest-leverage hires in sequence are:

Chief Data Officer: AI runs on data. Without this function in place, AI projects stall at the data readiness problem — which is almost always the real blocker. Hire this before the CAIO.
Chief AI Officer or VP of AI: Sets strategy, creates governance, and keeps the company from burning budget on initiatives without a business case. Hire after data infrastructure exists.
Chief Product Officer: AI that doesn't get built into the product doesn't scale. The CPO determines whether AI stays a demo or becomes a moat.
Chief Revenue Officer: Selling AI-powered products requires a different motion — buyers have high interest and high skepticism simultaneously. A CRO who has navigated category education cycles is worth disproportionately more.
CISO: AI dramatically expands the attack surface. Companies that don't hire this ahead of scale are building liability, not capability.

The sequence matters as much as the hire. Companies that bring in the CAIO before the CDO often find the AI strategy has no data infrastructure to run on. We advise on sequencing before we take a search.

Want to talk through the right sequence for your company? Our partners do this conversation before any engagement start.

What should boards know about AI-related cybersecurity risk when hiring a CISO?

AI has changed the cybersecurity threat landscape faster than most boards realize and faster than most incumbent CISOs were hired to manage. The risks boards need to understand before their next CISO hire:

The attack surface expanded overnight. AI has introduced entirely new threat vectors — model poisoning, adversarial inputs, deepfake-driven social engineering, and automated phishing at a scale no human team can manually defend against. A CISO hired before 2023 may have had no material exposure to any of these.
Personal liability is now real. The SEC requires public companies to disclose material cybersecurity incidents within four business days. "Material" is not always well-defined — and the CISO who cannot make that call confidently is a governance gap waiting to become a headline.
Regulatory complexity is compounding. GDPR, DORA, SEC disclosure rules, HIPAA, and sector-specific frameworks are tightening simultaneously across jurisdictions. A CISO who can navigate one framework but not all is a single-point-of-failure risk for any company with cross-border operations.
The role now requires board fluency. The CISO who cannot present risk in business terms to a board — without technical jargon — is not equipped for the role as it now exists. Communication and governance capability is as important as technical depth.

When hiring a CISO in the AI era, boards should look beyond credentials and certifications. The right questions are: Has this person managed an AI-specific incident? Do they understand what personal liability means for them in their jurisdiction? Can they hold a room with the board and the regulators simultaneously?

At ON Partners we understand the difference between the CISO a PE-backed company needs and the one a public enterprise needs — and we map candidates to the specific governance profile the board requires, not just the technical one.

The companies powering AI have worked with us for years

Technical depth and
commercial nerve.

Driving meaningful change on a global scale.