Global search firms differ less in how big their database is than in what kind of data they hold and what they do with it. Some run large data platforms, some build AI tooling into the search, some lead on assessment, and some rely on partners' networks. The way to compare them is to ask five questions about their AI talent data and judge the answers. Olofsson & Company, an executive search firm for AI and technology leadership, maps the full market for every search with its own AI platform.
Every search firm says it has the best network. Ask to see it.
That one request separates the field quickly. Some firms will show you a data platform built over years. Some will show you an assessment model. Some will show you a partner's address book and call it a database. This guide won't rank them; we've done that elsewhere. It explains what "database of AI professionals" actually means at a global search firm, the five kinds of data asset you'll meet, and the questions that tell you which one you're buying.
How do global search firms compare on their databases of AI professionals?
They compare on three things, and headline size is the least useful of them.
- What the data asset really is. A proprietary platform, a research team, or one consultant's contacts.
- How the firm judges AI leaders. Finding a name is half the job. Deciding whether that person will succeed is the other half.
- How fast it turns data into a shortlist. A database you can't search well is a filing cabinet.
A database of AI professionals is only as useful as its reach beyond one person's address book. A slate drawn from a single consultant's network tends to look like that network. Full-field market mapping is how you find the leader your competitors haven't met.[1] So treat "database" as a method question, then ask for evidence.
What kinds of AI talent data do search firms actually hold?
Strip away the marketing and you'll find five models. Most large firms mix two or three, but each leans on one.
| Model | What the "database" is | Example | Strong when | Watch for |
|---|---|---|---|---|
| Scale data platform | Years of assessment and role data in one system | Korn Ferry Intelligence Cloud | You run leadership programmes across many countries | Breadth of data is not access to scarce passive AI leaders |
| Search tooling platform | AI built into sourcing and workflow | ZRG Partners' Zi, Kingsley Gate Partners' IGNYTE | Speed matters and you want a scorecard | The tool speeds up the search; it doesn't replace judgement |
| Assessment-led | Psychometric and potential data on candidates | Spencer Stuart ExI, Caldwell Analytics | The leader is stepping into an untested role | Assessment only helps once the right people are on the slate |
| Practice and network-led | Partners' relationships plus a research team | Most large global firms | Board-level appointments with a long runway | The slate can mirror the partner's contacts |
| Per-search market mapping | A fresh AI-built map of the whole field for each role | Olofsson & Company | One scarce AI or tech leader, needed soon | Ask how many people were mapped and how many were passive |
A few numbers make the differences concrete. Korn Ferry's Intelligence Cloud draws on 5 billion data points on roles, skills and motivations and is built on 86 million assessments.[2] ZRG Partners built Zi to combine talent intelligence, candidate insight and process improvement, and reports a 30% cut in recruitment cycle time.[3] Kingsley Gate Partners calls itself the first AI-native executive search firm and runs IGNYTE, its own AI platform.[4] Spencer Stuart's Executive Intelligence (ExI) evaluation is designed to show which leaders can thrive in new, unfamiliar and complex situations.[5] Caldwell pairs IQTalent sourcing with Caldwell Analytics, which measures behavioural and cognitive traits.[6]
None of these is the "right" model. Each answers a different hiring problem. The mistake is buying one while believing you've bought another: paying for a partner's network and assuming you've had the whole market mapped.
Why does the method matter more than the size of the database?
Because the base rate is ugly. Leadership IQ studied more than 20,000 new hires and found 46% fail within 18 months. In 89% of those failures the cause was attitude; only 11% came down to technical skill.[7]
Read any firm's database pitch with that in mind. A bigger pool doesn't fix a weak filter. An AI leader who aces the technical interview and then can't carry a board or a team is the expensive failure.
Supply makes it worse. ManpowerGroup's 2026 Talent Shortage Survey of more than 39,000 employers in 41 countries found 72% struggle to fill roles, and AI Model & Application Development is now the hardest skill to find globally, cited by 20%.[8] When everyone is chasing the same few hundred proven AI leaders, holding a big list counts for little. What counts is finding the ones nobody else has called and judging them well.
What should you ask a search firm about its AI talent data?
Ask these five questions before you sign anything. Then listen for the answer behind the answer.
1. Show me the map
How many people did you consider for a similar search, and how many of them were passive? A firm that genuinely maps the market can give you a number and show you an anonymised map. A firm working from its network will talk about "the right people" and "relationships" instead.
2. Where does the data come from?
A proprietary platform, a research team, licensed databases, or the partner's contacts? All four are legitimate. You just need to know which one you're paying for, and how recently it was refreshed. AI talent moves fast; a profile from two years ago describes a different person.
3. How do you test leadership as well as technical depth?
Ask to see the assessment, not a description of it. For an AI role the hard part is rarely the model knowledge. It's whether a strong researcher or engineer can set strategy, hire, and explain trade-offs to a board. If the firm can't show how it tests that, the Leadership IQ numbers above are your risk.
4. How many mandates is my consultant carrying?
On a scarce technology hire at a large firm, your role can end up competing for attention with dozens of other searches.[9] Ask for the number. Ask who actually does the sourcing, and whether it's the person who pitched you.
5. When will I see a shortlist?
Get a number in days, then hold them to it. A firm that can't commit to a date usually doesn't know how big the market is yet, and that tells you something about its data.
What a good answer sounds like
| Question | Good answer | Red flag |
|---|---|---|
| Show me the map | A number, a passive share, an anonymised example | "We know everyone in this space" |
| Where does the data come from? | A named source and a refresh cycle | "Our network" and nothing else |
| How do you test leadership? | A sample assessment you can read | "Our partners have great judgement" |
| How many mandates? | A specific number per consultant | A change of subject |
| When's the shortlist? | A date in writing | "It depends on the market" |
Any firm worth hiring will answer all five without flinching.
How does Olofsson & Company use AI talent data?
We built our search around the per-search map. Our AI platform scans millions of profiles and builds a full market map within 48 hours, then specialist consultants with 15+ years of experience narrow it to the 5 to 10 candidates worth meeting.[10] For senior search (CEO, CTO, CAIO, VP Engineering) we report a 20-day average time-to-shortlist and a 97% placement success rate.[11]
The point of the data is coverage. The platform finds the passive leaders who aren't on any recruiter's list, and our consultants judge the part software can't: whether a brilliant technologist can also lead. We work with startups, VCs and fast-growth companies around the world from our Singapore headquarters.[11]
That makes us the right call for one scarce AI or engineering leader, or a small leadership team, needed this quarter. If you're running a multi-country leadership programme, a scale data platform may suit you better, and we'd tell you so.
If you want the ranked view of firms, see our Top 10 executive search firms for AI-native technology recruitment. For the wider trade-off, read our guide to boutique vs. global executive search, and before you make an offer, check what to pay a Chief AI Officer in 2026.
Size gets a firm into the conversation. The map, and the judgement applied to it, gets you the right leader.
Frequently Asked Questions
Which executive search firm has the largest database of AI professionals?
Korn Ferry has the largest documented data asset. Its Intelligence Cloud draws on 5 billion data points and 86 million assessments.[2] Scale of data isn't the same as access to scarce passive AI leaders, which is why a firm that maps the full market for each search can outperform it on a single hire.
Do search firms use proprietary platforms or public profiles to find AI talent?
How can I tell if a search firm's AI talent database is any good?
Ask to see an anonymised market map from a similar search, with the total number of people considered and the share who were passive. Then ask how the firm tests leadership as well as technical depth, and for a shortlist date in writing. Vague answers to any of the three are the warning sign.
Sources
- olofsson.ai: Why network-only search narrows the slate, and how full market mapping finds passive leaders.
- kornferry.com: Korn Ferry Intelligence Cloud, 5 billion data points and 86 million assessments.
- zrgpartners.com: ZRG Partners Zi platform, reported 30% reduction in recruitment cycle time.
- kingsleygate.com: Kingsley Gate Partners, AI-native executive search and its IGNYTE AI platform.
- spencerstuart.com: Spencer Stuart Executive Intelligence (ExI) evaluation.
- caldwell.com: Caldwell Analytics behavioural and cognitive assessment, alongside IQTalent.
- leadershipiq.com: Leadership IQ study of 20,000+ new hires; 46% fail within 18 months, 89% due to attitude.
- manpowergroup.com: ManpowerGroup 2026 Talent Shortage Survey, 39,000+ employers in 41 countries.
- olofsson.ai: How large global firms trade speed for breadth on a single scarce technology hire.
- olofsson.ai: AI platform scans millions of profiles and builds a market map within 48 hours; specialist consultants surface the top 5 to 10 candidates.
- olofsson.ai/expertise: Senior search figures (20-day average time-to-shortlist, 97% placement success) and global client base.