What HR pros need to know about AI in the workplace

Most CEOs in a recent SHRM survey, 75%, said they expect to see further workforce reductions or layoffs in the broader economy next year, reflective of economic and technological uncertainties over the short term, the HR organization said.

Artificial intelligence adoption emerged as the most frequently cited primary objective for 2026 among respondents, ahead of both growing revenue and attracting top talent.

CEOs face pressure to show their organizations are leveraging AI and that doing so will improve financial results, James Atkinson, VP of thought leadership at SHRM, said during a media event announcing the research.

And while AI is expected to displace some jobs, Atkinson said executives increasingly believe the tech can create value instead of solely being used as a cost-cutting method. He added that economic developments like the effects of inflation and tariffs are among the factors that, alongside AI adoption, organizations have cited when conducting layoffs or slowing hiring.

“All of these things are related, but that hesitance really comes down to some of those challenges that are articulated here around inflation and economic uncertainty,” Atkinson said. “That makes it harder to plan when you’re not sure, or are only marginally sure, how these things may play out.”

Earlier, outplacement firm Challenger, Gray & Christmas found that October job cuts were up 175% year over year and had reached their highest single-month totals since 2008. A separate survey of employers by Resume.org found that 3 in 10 respondents had already shedded jobs via AI, while 37% expected to do so by the end of 2026.

In a statement, SHRM President and CEO Johnny Taylor urged employers to balance technological progress and caring for employees.

“We must lean into AI and new technologies without losing sight of our greatest asset: our people,” Taylor said. “The future will be shaped by leaders who move faster than the disruption, who invest in upskilling and reskilling, and who build future-facing workplaces ready for anything.”

SHRM found that 81% of CEOs expected rising labor and workforce costs next year, and 74% anticipated restructuring efforts. Agility and efficiency were commonly cited reasons for making adjustments, which may take the form of hiring more independent contractors, gig workers and freelancers.

CEOs are nonetheless struggling to find skilled talent for some in-demand roles, Atkinson said, and 27% of respondents said attracting top talent is a priority over the next twelve months.

SHRM is expected to follow up its CEO survey with two additional reports — to be published early January — on CHRO and worker perspectives. Atkinson said that while SHRM was not prepared to release any findings from those reports, it has found a “good amount of alignment” between CHROs and CEOs on AI adoption as well as economic uncertainty.

The end of 2025 painted a dour picture of the job market, especially entry-level roles.

Entry-level jobs are disappearing, says one survey. Companies plan to replace those positions with artificial intelligence tool use, says another. The tech may even be killing younger workers’ job prospects at a disproportionate rate.

But amid a market recently described as “frigid,” is AI actually to blame?

The story is more nuanced than that, experts told HR Dive, but the ramifications of AI adoption are numerous. And employers that use the technology for tasks typically apportioned to entry-level employees may be unprepared for the changes such investment may require.

What the narrative hides

Some high-profile layoffs and job cuts at the end of 2025 — including 14,000 roles eliminated at Amazon — were pinned on AI adoption, but that may be a convenient narrative for employers, Jason Walker, co-founder, CEO and CPO of Thrive Consulting, told HR Dive in an email.

“Layoffs are pretty much always on the table, frankly,” Walker said. “But I think what makes them easier to do is the guise of ‘we need to get more efficient’ and AI allows for that narrative.”

Companies are hiring less, he continued, particularly right now as they assess the effect of AI and whether it will actually make them more efficient.

Entry-level workers seem to be at risk, but they aren’t necessarily the only victims of cuts, and they’re not necessarily being laid off faster than anyone else, Emily Rose McRae, senior director analyst with Gartner, told HR Dive. But organizations are hiring less, she said, and universities report difficulty helping graduates land jobs.

Early career workers aren’t likely to be completely shut out from the market, either, Wendy Mazoway, global vice president of recruitment process outsourcing at Korn Ferry, told HR Dive. One of the company’s clients, a large global aerospace tech manufacturer, brought AI into the fold while maintaining a “very strong commitment to hiring early career folks,” Mazoway said. That program for early hires has actually grown, she added, spotlighting how work is changing but still creating opportunity.

So is AI adoption really driving massive headcount shifts? “The thing is, no one can really tell you how much of that is due to excellent returns in AI,” McRae said. “It probably isn’t at all.” 

Employers are still in speculation mode when it comes to the technology’s benefits. Many may be pressured to make cuts as a form of “debt financing,” hoping AI investment gains will eventually justify the layoffs, McRae added.

Uncertainty about AI’s actual impact on operations, however, remains a sticking point. While some companies, such as Salesforce and Amazon, have openly explained how AI is changing their businesses, Walker said, those tangible examples are few and far between.

“Nobody can really tell you tangibly [t]hat AI is going to improve their business and make it more efficient,” Walker said. 

AI’s benefits have been notoriously difficult to quantify, Walker said. And as employers experiment, they may struggle to see the powerful productivity gains often promised by tech companies.

The key, according to McRae, is clarity: “Don’t make investments in your talent strategy assuming some sort of tech capability you don’t have access to,” she said.

If entry-level jobs are at risk, what does that mean for pipelines?

Even if AI’s impact on job cuts is so far overblown, the reality is that many entry-level jobs are, in fact, at risk, Walker said. And that effect can be quantified. 

Entry-level researchers, marketing communications professionals, administrative assistants and even early software engineers have seen large aspects of their work be taken over by automation, he noted.

Employers also may redesign workflows to better use AI, which could lead to entry-level jobs being cut, McRae said. But that creates another problem: How does an employer build a sustainable, trustworthy pipeline of workers with the experience needed for higher-level jobs? 

“That’s a two-fold problem,” McRae said. Not only are workers not obtaining the skills, in that case, but there’s also no easy proxy for competency — such as years of experience in a certain role — that employers can look to when considering promotions or hiring. 

And while employers can train those workers up, as Mazoway noted, those painstakingly trained workers could easily be poached by competitors instead — and they often are, McRae said. Too much uncertainty will drive people to leave fields entirely, making the talent crunch even more severe.

A question of change management and decision-making

Because AI is still so new, few guides exist on how to prepare the workforce for its impact, McRae said. To see returns on those investments, employers may have to lead costly redesigns on workflows and job designs — and many leaders, after seeing what effort it would take, may not see the change as worth it, she noted.

Employees, too, may be wary of employers’ attempts at change management. A December report from Eagle Hill Consulting showed that only 1 in 4 employees surveyed said their organizations effectively manage major change.

But not all change spells doom for jobs or opportunity. Many companies are investing in training centers again after they fell out of favor during the pandemic, Mazoway said. AI, in general, will require significant investments in infrastructure that will create jobs, she added.

AI is just the latest technology changing how work is done, and knowledge-based jobs have long faced this trend, she noted. “If I think about my job as a recruiter 30 years ago, I was flipping through a phone book and calling people,” Mazoway said. Instead, the person with that job today is much more focused on relationship building thanks to developments in applicant tracking systems and other recruiting technology.

But generally, change management will remain the elephant in the room as AI conversations move forward, Walker said. 

“I think educating and training are not the issues, it is change management and understanding how you use AI to be more efficient,” he said. “That is what people need to learn.”

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By The Predictive Index

Effective AI governance requires more than good intentions. It demands concrete practices that embed compliance and fairness into everyday operations. These best practices help HR leaders move from reactive problem-solving to proactive risk management.

1. Conduct regular bias audits with documented methodologies

Don't wait for a lawsuit to discover your AI tools produce disparate impact. Establish a schedule for bias testing: quarterly for high-volume hiring tools, annually for performance management systems. Use the four-fifths rule as a starting point, but apply statistical significance testing when sample sizes warrant it. Document your methodology, findings, and remediation steps.

When using tools like the PI Behavioral Assessment, leverage The Predictive Index’s existing validation research as a benchmark for evaluating newer AI systems.

2. Establish a human-in-the-loop review for consequential decisions

No algorithm should make final decisions about hiring, promotion, or termination without human review. Build checkpoints where trained professionals examine algorithmic recommendations, particularly when they conflict with manager judgment or affect protected groups differently.

This doesn't mean constantly overriding AI. It means ensuring human oversight catches bias patterns before they become systemic problems.

3. Maintain detailed vendor due diligence documentation

When using third-party AI tools, vendor assurances about compliance mean nothing in court.

Maintain vendor due diligence documentation by:

• Documenting what questions you asked vendors about training data, bias testing, and algorithmic logic.
• Requesting copies of validation studies.
• Understanding what metrics they used to assess fairness.

If a vendor can't or won't answer these questions, that's a red flag. Always keep in mind that HR bears the ultimate responsibility for AI outcomes, regardless of who built the tool.

4. Create transparent AI disclosure policies for employees

Employees have a right to know when AI systems evaluate them. Develop clear policies about which tools are deployed, what data they collect, and how decisions are made. This transparency isn't just ethical; it's increasingly legally required. Use accessible language, too, not technical jargon.

When rolling out new AI tools, communicate proactively rather than waiting for employees to ask questions.

5. Build cross-functional AI governance committees

AI oversight can't live solely in HR. Establish a governance committee that includes HR, legal, IT, and business leaders. This group should review new AI tool proposals, set organizational standards for algorithmic fairness, and adjudicate concerns when they arise.

Regular monthly or quarterly meetings ensure AI governance remains active rather than another forgotten initiative.

6. Implement escalation protocols for algorithmic concerns

Create clear channels for employees and managers to raise concerns about AI-driven decisions. Designate specific HR team members to investigate these concerns and establish response timelines. Track patterns in complaints. For example, if multiple employees question the same tool, that signals a problem requiring immediate attention.

The stakes are high. Without proper oversight, AI systems can introduce bias, violate anti-discrimination laws, damage employer brand, and erode employee trust. But with the right frameworks in place, HR can harness AI's efficiency while maintaining fairness, transparency, and compliance.

While HR leaders largely said they have more input into which tasks are selected for automation than they did two years ago, only 30% said they were involved from the outset on artificial intelligence strategy. That shows a strong disconnect from other C-suite leaders, 60% of whom said HR is involved from the start.

In fact, HR is “often sidelined” when it comes to workplace AI transformation, HR data vendor Beamery said in a recent report. When asked to pick the two most influential decision-makers on AI, survey respondents picked the CEO (81%), digital transformation lead (50%) and CIO (36%) among the top three. CHROs trailed at 12%. 

“If HR doesn’t get a seat at the table, workforce considerations, skill gaps, and employee engagement may not be fully accounted for in AI-driven transformation,” Beamery said.

For its report on AI workplace redesign, Beamery surveyed more than 170 C-suite executives, 115 HR leaders and 200 early-career employees with five or fewer years of experience at companies with more than 5,000 employees.

“With the right workforce insights, and HR involved from day one, companies can ensure that AI-driven decisions fully account for workforce implications,” Beamery said. The report noted that HR can be brought in earlier to prioritize tasks that can be automated without hurting employee engagement or customer outcomes; shift employees to higher-value tasks that develop workers’ skills, experience and growth; and align workforce planning, reskilling and role design with business goals. 

When it comes to specifics, more than a third of HR leaders said there was not enough clarity in what employees do day to day, creating a barrier to effective AI adoption. More broadly, the C-suite highlighted three challenges when it comes to workplace automation: choosing the right tasks to automate, ensuring data quality and availability and gaining employee trust and overcoming pushback.

Perhaps surprisingly, early-career employees largely reported optimism about AI, regarding it as a “launchpad, not a threat,” according to Beamery. Nearly three-quarters of employees said AI made them more likely to stay with their current employer, with 66% of those respondents saying it was because the technology was creating major growth opportunities and 60% stating that their engagement has increased due to new career and skill development opportunities.

Smaller percentages reported staying put due to fear: either of becoming a “last-in, first out AI layoff” at a new company or that AI has made it harder to find new jobs.

CHROs will play a critical role in the future of AI, two AI leads at Deloitte wrote in an op-ed for HR Dive, similarly pointing to HR’s potential to help maintain employee buy-in through AI transformation, align AI’s usage with business goals and focus upskilling strategy.

Leaders’ failure to connect AI adoption to upskilling may be the biggest workplace challenge; an October report from Express Employment Professionals and Harris Poll found that while nearly three-quarters of hiring managers said their companies had adopted AI, more than half also said their companies don’t have the resources to train their employees to use it effectively. 

And while currently employed workers may be optimistic about the effects of AI, job seekers are notably not — suggesting very different experiences for those looking for a change. Nearly two-thirds of job seekers surveyed by Express Employment Professionals and Harris Poll said they “worry AI will significantly limit job opportunities.”

Employees who use artificial intelligence tools may save nearly the equivalent of a full working day per week, around 7.5 hours on average, according to research from the London School of Economics’ Inclusion Initiative and Protiviti, a global consulting firm.

Rates of AI tool usage may rely on training, however. While 93% of the 3,000 employees surveyed who received AI training used it in their work, 57% of those who did not receive training said the same. 

Training can double productivity and the hours at work saved, upward of 11 hours per week, the report said. Generational diversity can also lead to greater productivity where AI use is concerned, according to the report.

The Protiviti and London School of Economics report emphasizes the role of training in unlocking the benefits of AI tool use.

“For business leaders, the priority is clear: closing the AI training gap is one of the fastest ways to unlock measurable returns,” Grace Lordan, founding director of The Inclusion Initiative at LSE and research leader, said in a statement.

Access to that training remains a sticking point in recent AI discourse, however. Employees routinely report that they are not offered the resources to learn to use the technology effectively — and while leaders have said they have access to training and understand the reasoning behind AI adoption decisions, rank-and-file employees have largely said the opposite.

This broadening training gap could intensify a “digital divide” within companies, BambooHR said in a report, straining workplace power dynamics and widening gender gaps. Employers that are not proactive about this gap could struggle to build a “future-ready” workforce, an Adecco Group report said, threatening attempts to innovate with AI successfully.

Almost half of U.S. workers now report using artificial intelligence tools at work at least a few times per year, which steadily increased throughout 2025, according to a report from Gallup.

At the same time, workers don’t always know what’s happening at the organizational level. While 37% said their employer has implemented AI to improve productivity, efficiency and quality, 40% disagreed and 23% said they didn’t know.

“The percentage of those who said they did not know was lower than the percentage who reported using AI at work at least a few times in the past year but higher than the percentage who reported using it frequently,” according to the Gallup report. “This gap suggests that a portion of employees used personal AI tools or otherwise used AI without awareness of their organization’s AI strategy.”

Despite increased AI adoption, a majority of U.S. employees report a “major AI trust gap” that affects their view of companies, according to an SHL report. Most workers said they’re open to AI that improves efficiency and consistency, yet they still want transparency about how AI is used, SHL’s chief science officer said.

In a Gallup survey of more than 23,000 U.S. workers, 45% reported using AI at work at least a few times per year, increasing from 40% in the second quarter. Frequent use — a few times per week or more — increased from 19% to 23%. Daily use shifted from 8% to 10%.

By sector, workers in knowledge-based jobs, such as technology, finance or professional services, were more likely to use AI than those in front-line positions, particularly in retail, healthcare and manufacturing.

Among workers who use AI at least yearly, about 4 in 10 said they use it to consolidate information, generate ideas and learn new things. Most workers use chatbots or virtual assistants, while fewer use specialized tools for data science, analytics or coding.

“Even so, daily use is still limited to about 10% of the American workforce, trails organizational AI adoption rates and is concentrated in specific roles and industries,” the report found. “Gallup research shows broader AI adoption among employees is strongly associated with having greater managerial support for AI and strategic integration of AI in their role.”

One aspect can help workers feel excited about AI adoption — job security, according to an Edelman study. Workers reported feeling more enthusiastic when AI is framed as a tool to empower them rather than replace them, researchers found.

Across eight countries, including the U.S., UK and Canada, more than 8 in 10 employed workers who use AI report saving at least one hour per day with AI tools, research by Indeed’s Hiring Lab found.

Workers most commonly use the time freed up by AI to take on other tasks and projects, according to a May and June 2025 survey of more than 80,000 individuals across eight countries, which also included Ireland, France, Germany, Japan and Australia. Workers’ other top uses for the saved time include enhancing the quality and efficiency of their current tasks and increasing throughput on existing responsibilities, according to the research, which was released in late December.

“We find that workers whose employers actively encouraged AI use are significantly more likely to actually use AI at work,” Hiring Lab economist Yusuke Aoki wrote in an analysis. The implication is clear, Aoki added: “If employers want workers to use AI effectively, encouragement and training are likely to matter more than waiting for workers to adapt on their own.”

Studies repeatedly identify employer encouragement and AI training as key to AI transformation.

For example, research released in October by the London School of Economics and global consulting firm Protiviti found that AI training is critical to unlocking measurable gains. In particular, with AI training, workers can double productivity and save upward of 11 hours per week, the research showed.

“Even active AI users report insufficient training, indicating that one-time introductions are insufficient. Ongoing skill development will be essential as AI capabilities evolve,” Aoki noted in the Hiring Lab post.

Notably, although 43% of workers in the U.S. said they have used AI at least more than once per month, according to the Hiring Lab analysis, daily use may be limited to about 10% of the American workforce and is concentrated in specific roles, a December report from Gallup found.

The Gallup report also found that broader AI adoption among employees is strongly associated with employees who receive greater managerial support for AI and when AI is strategically integrated into their role.

“Simply using AI is not enough,” Hiring Lab’s Aoki pointed out. How AI is integrated into workflows makes a difference, Aoki said.

About a third (32%) of U.S. workers who saved time using AI say they use it to improve their work-life balance, Hiring Lab found. Almost a quarter (23%) redirect the time toward breaks and stress management.

Even as 80% of U.S. employees use artificial intelligence at work, 57% say they’re reluctant to tell their manager or colleagues they do, according to results of a survey by software company Cornerstone OnDemand Inc. 

However, rather than being driven by embarrassment, shame or fear of job loss, workers are staying silent because they lack training, the survey found. 

Only 44% of U.S. employees have received AI training, and just 16% received that training often. At the same time, 65% of U.S. workers said they want training to help build their AI skills and confidence. Dynata conducted the survey in October and polled 1,000 U.S.-based consumers.

Nearly two-thirds of U.S. workers say their organizations encourage them to use AI at work, yet a third of those don’t receive training, the survey found. 

“Heavy investment in AI tools alone [is] not the answer, as training and governance systems are critical to success,” Mike Bollinger, vice president of strategic initiatives at Cornerstone, said in a statement. “This survey validates employees’ desires for training, particularly on AI, but shows significant discrepancies on who is receiving it and the key alignments that need to take place across an organization.”

A leadership divide in AI use is developing, and workers are being left behind, an October Perceptyx report found. While 82% of executives and 68% of managers said they use AI, only 35% of individual contributors said they do. Likewise, 84-90% of managers and executives said that they need to develop new skills due to AI, but only 67% of individual contributors said the same, which could be a further indication of the growing gap. 

More than half of companies said they don’t have the resources to train employees to use AI effectively, according to an October report from Express Employment Professionals and Harris Poll.

Meanwhile, half of workers may have undergone some training in the past year, but only 12% received training on AI, a February Pew Research Center report found.

Despite AI being everywhere right now, employees and business leaders alike feel trepidation about AI’s role at work. Data from Beamery, for example, shows that HR professionals feel like their AI opinions aren’t taken seriously; Likewise, survey results from talent firm SHL indicate that there’s a trust gap between job candidates and potential employers when it comes to AI in hiring.

But a recent study from Edelman shows that there is one factor that can make workers excited about AI. On average, according to survey results, employees who feel more secure in their jobs due to AI are more likely to embrace it (50%) compared to the workers who feel less secure in their jobs due to AI (21%).

Workers feel more enthusiastic about AI when it’s framed as a tool to empower rather than replace them, according to the study. In the U.S. specifically, 59% of workers surveyed said they felt that way. 

And while China and Brazil are more accepting of AI — with 54% and 35% of surveyed workers saying they embraced it, respectively — Germany,  the U.K. and the United States had the lowest rates of people saying they are embracing it, at 16%, 18% and 17% respectively. Edelman researchers noted that half of U.S. workers surveyed said they are refusing to use AI.

When trust is low between workers and employers, there is some recourse. In sharing the firm’s November report, SHL’s Chief Science Officer Sara Gutierrez reaffirmed that AI use can shape overall perceptions of a business. Her main tip for building trust was for companies to disclose how they are embracing AI.

“Employers shouldn’t be silent about how they’re using AI. Being open about AI’s purpose, design, and use builds trust and differentiates organizations,” Gutierrez said in a statement. “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.”