AI can speed up the hiring process—but if MSPs aren’t careful, it can also create risk. In this final installment of our AI in Hiring series, we’ll break down how to do it right, as well as how to close the trust gap and fraud risks we covered in previous installments.
Start with the Right Question
AI works best at the top of the hiring funnel, though it requires more verification than is currently standard to prevent fraudulent candidates. This can include AI tools built into hiring platforms, such as Dice’s TalentSearch feature, mentioned in part 1 of this series. It could also mean custom-built or trained application screeners.
That’s where things start to break down. Too many recruiters are handing over screening to AI without fully understanding what it’s doing. According to hiring platform Greenhouse’s 2025 AI in Hiring report,
- 53% rely heavily on AI/ATS screening
- 25% don’t trust the results
- 8% don’t know what their AI prioritizes
That’s not just inefficient; it can put you in legal jeopardy.
As discussed in the second installment of this AI in Hiring series, knowing how your AI filters candidates is critical; otherwise, you risk ending up in a lawsuit for candidate discrimination. Just as important: you can’t automate the human element out of hiring, and any attempts to do so risk alienating an applicant pool already wary of indiscriminate AI use.
The question MSP should ask isn’t “What can we automate?”—it’s “What should we automate?” The key is taking a thoughtful, intentional approach to AI usage.
Here’s what to keep in mind.
Automation at the Top of the Funnel
There’s no doubt that MSPs are looking to make the hiring pipeline flow faster with AI. Emi Chiba, HR tech analyst at Gartner, says one of the number one questions she gets from organizations and clients is in regard to how they can deploy AI in their recruitment processes. “There’s a need and a desire for it, for sure. And in HR especially, recruiting is an attractive place to experiment with AI, because it is so fast paced and has such easily measurable deliverables and so much volume,” she explains. “Repetitive AI for recruiting is often a place where most enterprise HR functions will pilot [their] first AI rollouts.”
When it comes to recruiting, AI “allows for speed at scale and highly repetitive tasks at volume,” says Chiba. “You can get through it faster and reallocate that time and [those] resources to something more valuable. I think a lot of people are … using AI at the top of the funnel: to generate outreach, personalize communications, write job descriptions, give insight into candidates, make suggestions, etc.”
Keep in mind: candidates are using AI too, which means the returns are shrinking over time. As a result, this means more work and verification checks at the top of the funnel than were previously necessary.
In her breakout session at Gartner’s Identity and Access Management summit last December, Chiba shared her best practice advice: to verify identity 3 times during the hiring process.
Triple Verification Needed
As discussed in our last installment, fraudulent applicants present a critical risk in the hiring landscape right now. With the number of fake applicants only increasing, it’s more important than ever to integrate verification into the hiring processes of yourself and your clients.
Verifying identity three times is your best practice, according to Chiba. “This is how you get the most holistic picture about consistent behavioral information.”
Then, the question becomes when to verify your identity. Historically, identity has been verified towards the end of the pipeline, such as through an in-person interview. While this is a great strategy, it’s too late in the hiring process to stand alone. Candidates aren’t likely to hand over a picture of their driver’s license with their application either. Even if they did, you don’t want to spend time and money verifying candidates who won’t move forward anyway.
The goal is to find places to verify toward the middle and end of the hiring process. Chiba recommends verifying identity at the hiring manager interview, at the offer stage, and during onboarding. This gives you 3 rounds of verification and “strikes the balance between cost and candidate experience,” she says. Plus, “generally the closer you are to an offer, the more incentive there is for a candidate to manage those process tasks.”
If you can only choose one time to verify, Chiba says to “focus on the offer. It is the most conservative, and it is probably the most similar to what happens today, because it is usually at that offer stage that we begin to collect that information anyway,” so candidates won’t be taken aback.
The Human Element: Empathy and Connection
The human element is just as essential as identity verification in today’s AI-driven hiring. In fact, it’s more important than it has ever been.
In a job market full of fake job postings and AI interviewers, interpersonal connection and empathy for candidates are critical. Those are your secret weapons to standing apart in a job market full of potential employers.
When it comes to candidates utilizing AI in their resumes or cover letters, your knee-jerk reaction might be to eliminate them immediately. But “in some ways, we have to have empathy for candidates trying to present their best self. It’s natural to want to use every tool available to give the most polished version of yourself,” says Chiba. “Unfortunately, for recruiters, yes, sometimes that means you get a bunch of [resumes that] look similar or all have the same tone or voice. But is there also an argument to be made for faulting people not for using AI, but for using poorly or ineffectively? If you take the first draft and say it’s good enough, does that reflect on you and your ability as a candidate?”
“This is a sort of philosophical question that employers have to reckon with—you cannot expect an AI-ready workforce and an AI-free recruiting process. Whatever the role requires and entails, those expectations and circumstances should be replicated as much as possible in the recruiting process,” Chiba says.
Mending the AI Trust Gap with a Human Touch
The human element is also a core component to addressing the AI trust gap. While many workers are curious about AI, most are uneasy about how it’s shaping the future of work. A striking 74% of respondents admitted being interviewed by an AI agent would change their perception of that company. While many are open to interacting with an AI interviewer, they still want human involvement and accountability in the process, found SHL, a talent intelligence company in a recent survey.
“AI can quickly shape the perception of a company as either innovative or impersonal,” says SHL’s CSO Sara Gutierrez. “Most employees are open to AI that improves efficiency and consistency—and they place high value on employers being transparent about where and how it’s used, particularly in decisions that impact careers.”
More than anything, transparency is crucial. “Being open about AI’s purpose, design, and use builds trust and differentiates organizations, Gutierrez says. “Our experience shows that when responsible AI is thoughtfully integrated into any talent workflows—particularly interviewing—and paired with open communication and human oversight, workers view it as innovative, efficient, and fair.”
AI clearly isn’t going anywhere, and that includes in the hiring process. But as it becomes more prevalent, one future possibility is that it will “beget more of a human touch,” says Chiba. “That’s where we might see a return to in-person recruiting events, or more referrals, internship programs, or alumni networks. More of that in-person, human touch and [connection].”
For more on the latest in AI, learn how to escape the AI pilot purgatory so many MSPs are getting trapped in.
