Hiring is a headache, just ask any MSP business owner. When you’re competing for talent, hiring the right candidate efficiently, the first time, is essential. Hiring the wrong person is a waste of time, energy, and resources.
Artificial intelligence may be the cure to that headache, opening the door to smarter, faster, and more intentional hiring. Today’s AI tools are helping MSPs write clearer job descriptions, identify promising candidates faster, and ask better, more targeted interview questions.
But there’s a catch. Candidates are using the same tools, leading to a hiring ecosystem where AI is increasingly “talking to itself.” This opens up the possibility that a fraudulent candidate will slip through the cracks, putting your company at risk, or the best-fit candidate will be overlooked because they’re not “gaming” the system.
Still, there’s no denying AI can be a force multiplier in your hiring process, as long as you understand how to work with it, balance it with human judgment, and use it to surface real potential beneath the polish.
That’s why in this three-part series, we’ll cover how AI is impacting the MSP hiring process, how to separate fraudulent applications from real ones, and how MSPs should be using AI in the hiring process, without accidentally eliminating quality candidates.
How Hirers are Using AI Today
One of the main ways employers are currently using AI in the hiring process is as a filtration system. This can take a number of different forms, from AI agents to AI-powered career platforms.
Valeo Networks, for instance, an MSSP headquartered in Rockledge, Florida, is building Copilot agents for customers, offering an early version of Agents as a Service. “You can create a Microsoft 365 Copilot agent in SharePoint to help with hiring practices or resumes or whatever in the hiring process,” explains Jim Gast, director of AI-powered new business development. “It saves the people we consult for so much time because they don’t have to do the individual reading themselves. That’s the key right there. And they can start doing queries in natural language, instead of just looking for keywords.”
Meanwhile, Dice, a technology career marketplace, recently launched their New Dice Employer Experience, a major platform redesign intended to modernize tech hiring with integrated AI-powered tools, like an AI Boolean enhancer that transforms search queries into Boolean strings. This allows recruiters with minimal Boolean expertise to utilize Dice’s TalentSearch feature’s more advanced capabilities, enabling them to refine searches and find the most relevant candidates with simple search queries.
“As the MSP community understands, there’s a million acronyms and different sets of descriptions for the same kind of role and technology,” says Paul Farnsworth, president of Dice. “We use machine learning to basically match not just the words, but the association of words around the outside. It’s about getting some scale and efficiency. As we continue to improve the ability for AI to match between a well-written job description and a well-presented profile with all the skills, you get better matches. And as everybody knows, it’s very expensive to rehire. So overall, it’s about getting the right person the first time.”
Brandis Kelly, president of the Midwest region of DigeTekS, says her MSP is mainly using AI “to look for red flags, gaps, and even culture fit” indicators in applicants’ resumes—while being careful not to feed any identifying information into ChatGPT, of course. After uploading portions of a resume into ChatGPT, Kelly’s team asks it to generate targeted first-round interview questions for that specific individual. “We’ll have ChatGPT customize it,” Kelly says. “I’ll say, give me 3 questions for that would be a good culture fit, that would look for situational behavior, or that might identify red flags or gaps in their resume that I should ask about. So we can customize the interview a little bit.”
Kelly is also interested in incorporating Fathom Notes into their hiring process, due to its ability to simultaneously take notes and produce live prompts. “It’s almost like live coaching from AI. It’ll prompt you and say I’m talking too much, or that I need to ask this follow-up question,” because the interviewee didn’t answer the original question completely.
Human Element Still Required
Overall, employers are feeling opportunistic about AI in the hiring landscape. Kelly says that when it comes to hiring, AI is “definitely a help. But it can’t do everything; it can’t take out that human element.”
Farnsworth anticipates AI helping “smaller companies have a little bit more efficiency and scale and skillset that you wouldn’t ordinarily have access to, if you don’t have a large HR team. I also think, if used correctly, AI improves matching between a candidate’s background and skills and the job description that is required from a job hire. Now, the balance on this is, on the hiring side, hiring managers need to understand that AI also enhances the presentation of a candidate and there’s still human work to be done to screen.”
Hiring platform Greenhouse’s 2025 AI in Hiring report, which surveyed over 4,100 job seekers, hiring managers, and recruiters across the U.S., U.K., Ireland, and Germany, found that 7 in 10 (70%) hiring managers say AI helps them make faster and better hiring decisions with fewer recruiter resources. Of recruiters, 50% say AI has improved hiring overall, mainly by saving time on screening and scheduling—but 25% admit they’re not confident in their AI systems at all, and 8% say they have no idea what their algorithms prioritize. Only 21% are very confident that their systems aren’t rejecting qualified candidates.
New Challenges for Applicants Too
More concerning is the rapid degradation of trust among applicants—the report found that 46% of job seekers in the U.S. say their trust in hiring has decreased over the past year, with 42% blaming AI directly. Of particular concern is AI bias, with 35% of job seekers in the U.S. thinking AI has shifted bias from humans to algorithms. Only 8% of candidates believe AI makes hiring more fair. And among U.S. Gen-Z entry-level workers, a whopping 62% have lost trust.
It’s easy to see why applicants are so distrustful of employers’ AI usage, when 69% of respondents reported encountering fake job postings, and nearly 49% submitting more applications than a year ago. Over half (54%) have encountered an AI-led interview.
At the same time, many job seekers consider AI usage a necessity to level the playing field, with 41% of the 1,200 U.S. job seekers surveyed admitting to using prompt injections—hidden text designed to bypass AI filters. And, of those who don’t use this tactic, 52% say they are considering it.
Beware of Fraudulent Applicants
With many legitimate job seekers using AI with increasing frequency, it’s becoming harder and harder for employers to tell fraudulent applicants with malicious intent from desperate job seekers doing whatever it takes to get a good job.
The report found that 91% of recruiters have spotted candidate deception, and 34% spend up to half their week filtering spam and junk applications. Two in every three hiring managers have caught applicants using AI deceptively, like reading from AI-generated scripts (32%), hiding prompt injections in resumes (22%), or showing up as deepfakes (18%).
“Our latest data shows that neither side is happy with the hiring process right now,” says Daniel Chait, CEO and co-founder of Greenhouse, in the report. “Trust is at an all-time low for both job seekers and recruiters. Candidates are doing whatever they can to break through the noise, while talent acquisition teams are drowning in so many applications they’re looking for ways to sort through what’s real and what’s not.”
“Unfortunately, although all sides are just trying to do their best, our survey shows that the collective result is worse for everyone,” Chait adds. “Jobseekers use AI to apply to more and more jobs, while employers use it to filter candidates back out again. It’s an AI doom loop that’s getting worse, not better.”
That said, AI can be a great tool for MSPs to enhance their recruiting and hiring processes—as long as they understand the risks and avoid the pitfalls.
In the next installment of our AI in hiring series, we’ll dig into methods MSPs are using to separate real applicants from the fake ones and avoid hiring bias. In the meantime, take a closer look at the challenges facing MSPs in 2026.
