AI use in hiring has become one of those topics everyone has an opinion on, usually before they’ve actually defined where the line should sit. We get asked about it frequently by clients who want to know what we’re doing on their searches, and by candidates who want to know whether a human actually read their resume.
So instead of giving a vague answer, here’s exactly where AI fits into our process at Fusion, and just as importantly, where it doesn’t.
Where Does AI Use in Hiring Actually help?
There’s a real, practical list of things AI handles well in our day to day work. None of it replaces judgment. All of it saves time on tasks that used to eat hours out of every search.
- Writing and refining job descriptions
- Summarizing search kickoff notes
- Pulling together candidate submittal summaries for hiring teams
- Drafting outreach sequences
- Building phone screen questions for specific roles
- Running sourcing activities to generate candidate pipelines
These are the parts of a search that benefit from speed and consistency without requiring someone to weigh in on a candidate’s actual fit. A tool can help organize information. It shouldn’t be the one deciding what that information means.
Where we draw the line
Here’s where we don’t use it, and won’t, regardless of how good the technology gets.
- We don’t use AI to review or disposition candidate applications.
- We don’t use it to conduct interviews.
- We don’t use it to evaluate fit against job requirements.
Those are judgment calls. They require context AI doesn’t have access to, the tone of a conversation, what someone didn’t say as much as what they did, the read on whether a candidate’s hesitation in an interview means something or means nothing. In executive search specifically, that context is the job.
I know other firm owners and recruiters who use AI for resume screening and candidate evaluation, and I respect that we don’t all land in the same place on this. There aren’t global standards yet for how recruiters should use AI, so right now it comes down to what each company and each individual decides is responsible. That gap is exactly why being specific about where we stand matters more than staying quiet about it.
Why transparency about AI use in hiring builds trust, not skepticism
We’ve found that walking clients through how we use AI, and what we deliberately keep human, leads to a better conversation about our process overall. It’s not a disclaimer we’re required to include. It’s information clients and candidates actually want, and most firms aren’t volunteering it.
The firms that handle this well aren’t the ones avoiding the topic. They’re the ones who’ve actually thought about when, how, and under what conditions AI belongs in their process, and who keep revisiting that as the technology changes.
Three things we learned that most people don’t know
A couple of details from a recent AI conference stuck with us enough to share, because they’re the kind of thing that changes how you should be using these tools, not just whether you should.
It’s important to consider what information you’re giving AI access to. For example, if you’re using the desktop version of Grammarly, there are no firewalls. It has access to everything on your desktop, not just the document you’re editing. The web-based version still works well, but it’s worth knowing before you decide which AI tools touch sensitive search or client information.
We’ve also started recommending that companies invest in one enterprise-level AI platform rather than a patchwork of consumer tools. An enterprise platform gives your team a shared, collaborative environment and protects company data and intellectual property in a way consumer-grade tools simply weren’t built to do.
And finally, it’s important to consider where AI gets its information. Websites are starting to block AI crawlers, which means AI tools doing market research are losing access to current data. When that happens, some tools don’t say “I don’t know.” They generate something that sounds plausible instead. If you’re using AI for market research or competitive insight, validate what it tells you. The gap between a confident answer and an accurate one is getting wider, not smaller.
The takeaway
No matter where you land on this, the goal is the same: know your why before the technology changes again. Or, feel free to reach out if you’d rather talk through where your team should land.
