AI Is Taking Over Hiring. What Does That Mean for Total Rewards?

Many organizations are already using artificial intelligence (AI) tools to write job descriptions, review resumes and even interview candidates — and a third of them predict AI will facilitate their entire hiring process by the end of 2026.

Among employers surveyed by career tools website Resume.org, almost 60% are using AI technologies in various aspects of hiring, with three-quarters saying it’s led to higher-quality hires. Only 4% reported negative feedback from candidates about their use of AI in the interview process.

Access bonus Workspan Daily Plus+ articles on this subject:

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“The benefits of AI-led hiring include efficiency, consistency and scalability,” said Kara Dennison, the head of career advising at Resume.org. “AI can process large applicant pools quickly, apply objective criteria and reduce the administrative burden on recruiters. However, the risks are significant and shouldn’t be considered lightly.”

“I’m hiring people, not task masters; it’s the most important use of my time to make sure I get hiring right — and the human element of that is paramount.” 
— Courtney Palmer, executive director of HR, Insight Global

Incorporating AI Across Hiring Components

According to Resume.org, the ways in which organizations are utilizing AI tech vary widely. Typical hiring category use cases include:

• Resume reviews (utilized by 79% of respondents)
• Candidate rejections (74%)
• Candidate assessments (66%)
• Researching applicants (63%)
• Candidate communication (41%)
• Onboarding (39%)
• Interviews, such as scheduling, transcribing, conducting, analyzing language or assessing tone (34%)

Staffing and professional services agency Insight Global’s 2025 AI in Hiring Report also found near-ubiquitous AI use in hiring, with other AI-assisted hiring tasks ranging from establishing talent strategy to checking references and completing new hire paperwork.

For example, the report found:

• 99% of surveyed hiring managers use AI in some way in the hiring process.
• 98% saw significant improvements in hiring efficiency.
• 95% plan to increase their investment in AI for recruiting.

Yet, 93% of hiring managers reiterated they continue to see the importance of the human touch.

Courtney Palmer, the executive director of HR at Insight Global, said she selectively leverages AI for administrative aspects of hiring, such as creating initial drafts of job descriptions, scheduling interviews and analyzing interview notes. She also uses AI tools to search for public salary data to cross-check her internal salary survey tools, and supplements AI hiring and total rewards (TR) recommendations with her own case-by-case evaluations of the factors that make an individual candidate and role unique.

However, Palmer noted, she does not hand over the task of conducting an interview or making a hiring decision.

“I’m hiring people, not task masters; it’s the most important use of my time to make sure I get hiring right — and the human element of that is paramount,” she said. “In the end, I still may hire the candidate with less experience but a great attitude and learning aptitude over the person that is more qualified on paper.”

“Challenges can arise when algorithms fail to account for the unique needs of candidates or roles, or evolving market factors. A too-rigid, data-only approach may create standardized offers that lack the flexibility candidates expect in today’s market.” 

— Kara Dennison, head of career advising, Resume.org

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AI’s Influence on TR Packages and Offers

The ability for AI tools to aggregate various data sources — including external market trends and internal salary history and pay scales — can help create efficient, less biased TR packages that may lead to higher candidate acceptance rates, said Mark Dwyer, the chief of data science at Trusaic. The pay equity and regulatory compliance software company currently incorporates AI into its platform to augment human-powered pay equity work.

Dwyer stressed the importance of requiring managers to justify and document their decisions to override AI-recommended TR decisions. He reiterated the need to comprehensively audit and perform pay equity analyses on the data used to train an AI model before its input into the tool. And after the system is in place, he said the data should be continuously monitored, updated and analyzed.

“The foundation of a fair automated system is high-quality, unbiased data,” Dwyer said. “Without this, the AI will simply learn and perpetuate existing pay inequities.”

He also noted that when employers use AI in certain aspects of the hiring process, transparently communicating that information with candidates can help build trust beforehand.

To safeguard pay equity and consistency as automation continues to proliferate in hiring, Resume.org’s Dennison urged organizations to maintain human oversight in candidate offers and formulate clear ethical guidelines for AI use. She also discussed retaining the option for customization of AI-recommended offers.

“Challenges can arise when algorithms fail to account for the unique needs of candidates or roles, or evolving market factors,” Dennison said. “A too-rigid, data-only approach may create standardized offers that lack the flexibility candidates expect in today’s market.”

Keep Legal Considerations Top of Mind

Among the organizations surveyed by Resume.org, 57% of those using AI in hiring are concerned that the tools screen out qualified candidates, while half of them are worried it introduces bias.

If implemented hastily or without appropriate review or oversight, Dennison said AI tools may introduce bias into the hiring process, exclude qualified candidates or diminish candidates’ experience — leading to corporate reputation or legal risks.

Dennison noted organizations using these tools should closely track and comply with local and national equal pay, anti-discrimination and data privacy regulations and laws to mitigate legal concerns.

In addition, she said the future may portend increased use of more-advanced AI tools such as sentiment analysis and facial recognition — which are intended to score communication skills, honesty, emotional intelligence or attentiveness. For these tools, she cautioned organizations to move carefully and anticipate regulations.

“It’s highly controversial, because both of these tools can be biased against certain genders or ethnic groups and raise concerns around privacy, consent and ethics,” Dennison said. “I would say that professionals who are neurodiverse, speak English as a second language and those with interview anxiety would be among those at a high likelihood of being discriminated against with these types of technologies.”

The Evolving Role of AI and TR

With the increased use of AI tools and automation taking place in the hiring process, the TR function will most likely develop along with it.

According to Dennison, TR professionals will likely experience a shift from time-consuming or repetitive administrative tasks to higher-level, strategic roles, including:

• Weaving internal context into HR decisions;
• Monitoring legal shifts and requirements;
• Measuring compensation against business goals; and,
• Communicating internally and externally the reasoning behind compensation decisions.

The human components of hiring, including empathy, trust-building, negotiating and navigating challenging conversations, also will continue to require skilled TR leaders, said Dennison.

According to Insight Global’s Palmer, TR professionals who implement AI hiring tools in a measured way without fully removing themselves from the process are likely to see the best results.

“People take jobs for more than the work itself — they want to know about the culture, the team, the leader and the working environment,” she said. “AI can’t give candidates a genuine picture of that without the hiring manager being directly involved. Otherwise, you risk losing out on great talent, because great talent wants to join a company and work on a team and for a leader they respect.”

Editor’s Note: Additional Content

For more information and resources related to this article, see the pages below, which offer quick access to all WorldatWork content on these topics:

• Employee Compensation
• Organizational Performance
• Total Rewards