By Steve Saah, Executive Director of Finance and Accounting Permanent Placement, Robert Half
AI’s impact on hiring is significant—and for finance and accounting organizations, it requires serious attention. A bad hire can be costly, but hiring someone whose skills, credentials or experience are inaccurate or overstated can create even greater risk. The potential consequences are easy to imagine when new hires are joining teams responsible for financial reporting, tax and audit support, compliance, internal controls, ERP systems, sensitive company data and trusted business relationships.
On the positive side, responsible use of AI can make both the job search and hiring process more efficient. Generative AI tools can help candidates organize their experience, improve their resumes and prepare for interviews. And employers can use AI capabilities to support parts of the hiring process, from drafting job postings to organizing candidate information—provided they pair those tools with human oversight and careful review.
However, 65% of hiring managers responding to a Robert Half survey said the rise of AI-generated resumes is also creating hiring challenges. For one, it’s making it harder for employers to determine whether candidates truly have the skills and experience described in their resume. That means hiring managers must spend more time sorting through applications, conducting extra interviews and using deeper skills assessments to evaluate candidates thoroughly.
As AI and talent recruitment become more intertwined, finance and accounting leaders and their hiring teams need practical ways to verify candidates’ skills and experience—and even their identities—without slowing the hiring process unnecessarily. These 5 best practices can help.
1. Look beyond the resume for proof of experience
Resumes can’t tell a professional’s full career story, but AI-generated resumes can make even that partial story seem more compelling than it actually is.
AI tools can help job seekers present their experience in confident language, emphasize the right skills and frame routine responsibilities as strategic accomplishments. A polished resume that’s keyword-rich and highly customized to the job description may also help a candidate sail through the first round without giving employers a reliable sense of what that person has actually done.
The real test often comes later, when the candidate is asked to explain the work in detail. This is where the “resume illusion” can emerge—a disconnect between what is written and what is real. A potential hire may check all the boxes on paper, but then struggle in an interview to explain how they used the tools they listed, provide detailed examples of results or speak naturally about their experience.
In the AI era, it’s more important than ever for hiring managers to use resume details as a springboard for deeper questions that encourage candidates to explain the “how” behind the work they say they’ve done. Here’s what that might look like in practice:
If a candidate says they have month-end close experience, ask them to walk through how they handled reconciliations, variance explanations or competing deadlines.
If their resume lists financial reporting or analysis experience, ask how they verified data, explained a trend or variance, prepared materials for leadership or handled a last-minute change in assumptions.
If their resume lists tax, audit or compliance experience, ask how they handled missing documentation, reviewed work for accuracy or responded when deadlines and quality expectations were both high.
If they state they have advisory or business partnering skills, ask the candidate to describe how they communicated difficult news, managed expectations or helped a nonfinance stakeholder understand the numbers.
These follow-up questions help move the conversation beyond polished resume language and give interviewers a clearer view of a job seeker’s actual experience, judgment and readiness for the role.
2. Be vigilant for identity misrepresentation
AI’s impact on the hiring process doesn’t end with resumes. Employers are encountering issues during virtual interviews, including candidates who rely on AI prompts for responses or deliver well-packaged answers that lack substance when presented with common interview questions.
Identity misrepresentation, deepfake interviews and other forms of candidate impersonation are also becoming more common in the hiring process. Troubling real-world experiences employers have shared, when hiring on their own, with our company’s recruiting specialists range from a candidate who claimed to be from a specific city but couldn’t name a major road there to a new hire who arrived for the first day of work but wasn’t the person who appeared in the video interview.
These examples may sound extreme, but they point to a broader issue: AI can make it harder for employers to know whether the candidate they’re evaluating in a video interview or online is the person they claim to be. Gartner reports that 6% of candidates have admitted to participating in interview fraud, either by posing as someone else or having someone else pose as them. Gartner also predicts that by 2028, 1 in 4 candidate profiles worldwide will be fake.
The risk of interview fraud doesn’t mean employers should treat every candidate with suspicion. Most job seekers aren’t trying to misrepresent themselves—they just want to stand out. That said, it’s wise to err on the side of caution because even small exaggerations could lead to big hiring mistakes. Asking unscripted follow-up questions, requiring live discussion of work samples or adding a final in-person interview when it’s practical can all help to reduce risk.
3. Evaluate consistency across the candidate’s footprint
As noted earlier, a resume shouldn’t be treated as the only or best source of truth about a potential hire. Dig deeper into available information about the candidate to make sure the story they tell is cohesive and logical. For example:
Does the candidate’s work history make sense?Do references confirm the responsibilities listed?Does the candidate’s online profile align with the experience presented?Can the potential hire answer follow-up questions in ways that reflect real experience and judgment?
Taking the time to develop the full picture of a candidate isn’t intrusive. It helps protect the business, its employees and clients, and even the candidate experience. The key is to stay agile while taking these extra steps. If the hiring process becomes too slow or cumbersome, finance and accounting organizations risk losing strong candidates to competitors.
Learn more about the downsides of a long recruitment process.
4. Acknowledge AI use and communicate expectations clearly
While fraud prevention deserves serious attention in the AI era, the hiring process shouldn’t feel adversarial for candidates. Employers also risk looking out of touch if they take too hard a line on job seekers’ use of AI, especially when many candidates are using these tools to help organize their thoughts, prepare for interviews or better communicate their experience. (Plus, many finance and accounting organizations, especially those focused on modernization, are eager to hire AI savvy talent.)
A better approach is to communicate expectations about AI use to help promote transparency. Let potential hires know how AI use will be viewed, what parts of the process must reflect their own thinking and what verification steps they should expect. For example, let candidates know that live interviews, assessments and work discussions should reflect their own experience and judgment.
That balance matters. A clear, consistent process can help the business reduce risk while giving skilled candidates ample opportunity to explain—and show—what they can bring to the table.
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5. Align the resources needed to balance speed and diligence in hiring
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AI-generated resumes are contributing to rising application volume and making it harder for hiring managers to evaluate candidates quickly. As a result, many employers are looking for help validating the skills and experience of potential hires so they can make more confident hiring decisions.
In a Robert Half survey, 71% of finance and accounting leaders say the AI factor in hiring has made them more likely to turn to specialized recruiters for support. That strategy appears to be paying off, as 91% say staffing firms have been effective at helping them address AI-related hiring challenges, with more than half reporting the assistance has been very effective.
The takeaway for finance and accounting leaders? Diligence is even more critical in today’s AI-enabled hiring environment. But with a clear understanding of the risks, a practical plan for navigating them and the right resources to rely on, it doesn’t have to come at the expense of speed or competitive advantage.
