Top trends in upskilling

Workforce leaders talk about the importance of human skills in the face of the artificial intelligence gold rush, but what does that mean? Andy Nelesen, head of solutions and market insights at behavioral assessment company SHL, told HR Dive to think of the relation between tech skills (the AI element) and strategic judgment skills (the human element) like a tree. 

The leaves, which are prone to falling off the tree and regenerating, are what Nelesen and SHL call “perishable skills.” These tend to be tied to tasks done in specific software, like Microsoft Office. “Those are a lot of the skills that might be replaced by AI,” Nelesen said.

Meanwhile, the trunk of the tree represents “semidurable skills,” such as cloud computing or marketing prowess. The roots are “durable skills” that will carry human workers far no matter what, like judgment, critical thinking and decision making, Nelesen said. In its research, SHL observed that people who leaned more into these durable skills were more effective than people who focused on perishable skills.

Put simply: "It really isn't your ability to write a great prompt in ChatGPT5," Nelesen said, but rather a person's AI literacy and analytical ability that differentiated those who were high performers from the rest of the pack.

Similarly, an August study by Multiverse shared the 13 human skills researchers determined would bode well for AI adoption. Chief among these skills were “creativity,” “analytical reasoning,” and “systems thinking.”  

While researching the AI model, Nelesen and his team also found that certain generations tended to have different strengths. Part of successful AI adoption is “having a go-getter attitude” when it comes to new technology; another part is “knowing when to use it and when not to use it,” Nelesen said.

“More established” employees tend to have rules and regulations top of mind, Nelesen said. Meanwhile, younger employees, Nelesen said, are “very skilled and they're very willing to try new technologies, but they don't have some of those governance aspects.” In short, “neither cohort was fully AI-ready.”

As with many learning and development programs, personalization may be key. When it comes to AI integration by a workforce, Nelesen said, “You can't just paint with a broad brush.”

Upskilling opportunities promoted throughout the year may be associated with higher employee engagement, findings from SHRM indicate.

Surveyed workers who said their organizations share such offerings were “significantly more likely” to feel engaged at work, compared to others at companies that didn’t promote such opportunities (59% versus 31%). The more than 1,500 respondents also reported higher job satisfaction and increased commitment to their organizations when they had access to upskilling.

In light of those findings, SHRM recommended employers integrate upskilling into career development plans and communicate those plans consistently throughout the year.

Employee engagement has trended downward in recent years, according to Gallup tracking. But given the state of the job market, that doesn’t necessarily mean employees are leaving. Instead, workers are holding tight to their current positions, economic experts told HR Dive following last week’s jobs report.

Low engagement combined with low turnover can equal reduced productivity — dragging down company culture and costing employers dearly, research indicates.

Learning and development professionals, however, may be well positioned to help, given SHRM’s finding that upskilling can improve engagement — perhaps significantly so. Resources such as workshops, online courses and mentorship programs can help workers enhance their technical skills, interpersonal skills and AI-related skills, the organization concluded in its report.

HR can’t stop there, however. SHRM’s report specifically tied engagement to upskilling opportunities being “promoted” throughout the year. That means those tasked with L&D may need to ensure regular, clear communication about which resources are available and how employees can access them.

Employers also must also ensure workers have an opportunity to put to use any new skills acquired. January survey results from Resume Now revealed that 69% of U.S. employees say their skills aren’t being fully realized in their current positions, and when that happens, engagement can fall even further.

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Technological advances are disrupting work and increasing the need for upskilling and reskilling. But these efforts require insight into workforce skills gaps. When skills data is fragmented across systems, teams and programs, employers may struggle to identify what skills employees have, what skills they need next and where development should be focused. 

Companies may operate under the false assumption that they have a centralized and accurate view of their workforce skills data. But this information can be fragmented, limiting insight into employees’ true capabilities. 

How skills data becomes fragmented

Different teams define skills in different ways 

Without a common skills language across departments, skills could be defined differently between HR and L&D. Or the same skill might be labeled differently across HR and L&D teams. The result is potential confusion between employees, L&D professionals and HR. 

Managers assess capability informally  

Managers may be aware of some skills (like the ones employees use to do their jobs) but may lack visibility to other untapped skills or skill development potential. In some cases, managers rely on workers to self-report their skills and levels of proficiency. According to a report by Deloitte, only 48% of surveyed HR and business executives are confident that they have verified and documented human capabilities within their organization.  

Tuition programs run outside workforce planning  

Tuition programs have historically existed outside of a company’s L&D objectives and talent strategy. As a result, companies can face a disconnect over who holds responsibility for creating career pathways, as well as who should fund and support employee training and continued education.  

Where does fragmentation show up operationally?  

The lack of an organized skills visibility system can show up in the following ways.  

Completed training versus competency demonstration  

In some companies, HR leaders are unaware of what skills their employees possess and rely on self-reporting without validated proficiency. This is especially problematic when companies make decisions on pay, promotions and allocation of responsibilities without valid and verified skills data. 

No shared view of capability gaps  

Closing skills gaps is a top priority for many organizations. Yet few have the readiness to act on it, often due to a lack of skills visibility. According to a report by McKinsey & Company, fewer than 50% of survey respondents say their organizations are fully aware of employees’ current workforce skills.  

What are the hidden costs of fragmented skills signals? 

The true cost of fragmented skills signals goes beyond operational friction; it can result in wasted budgets and lost talent.  

Duplicate learning investments  

Companies in the U.S. already spend billions of dollars on workforce learning and development programs collectively. When skills data is fragmented, companies may find themselves paying multiple times to train employees on skills they already have. 

Slower internal mobility  

Employees with the skills to advance internally may leave when career development pathways are unclear or when employers lack visibility into their capabilities.  

Misaligned development priorities 

There are instances where employees receive training in skills that address problems but don’t actually solve them. For example, an organization may train employees on advanced tools while overlooking the foundational skills employees need to apply those tools in daily work. 

How to move from fragmentation to alignment 

To overcome the challenges posed by fragmented skills signals, HR managers should prioritize systems that connect talent acquisition, learning and internal mobility, including: 

• Shared skills language: Skills taxonomies provide clarity on which capabilities employees need to perform job responsibilities.  

• Validated proficiency signals: HR leaders should know which skills a company needs and how those skills are demonstrated.  

• Cross-functional access: Learning pathways should connect across functions to help employees keep up with changing business needs. 

• Transparent capability gaps: Companies that can pinpoint the skills required to meet future demands are positioned to create tailored, skills-centered learning pathways.  

Why is alignment no longer optional? 

In an environment that demands constant adaptability, alignment is a must for keeping up with evolving business and workforce demands. That alignment begins with better skills visibility: understanding what skills employees have, where gaps may exist and where development should be focused.

In HR Dive’s 2026 Identity of HR survey, the number of respondents who named employee training their organization’s top priority jumped 4 percentage points year over year, from 5% to 9%. While the overall percentage remains small (recovering from a comparatively large drop after 2024), the increase is significant — especially considering artificial intelligence tools are changing how work is done, experts told HR Dive.

“The shift from 5% to 9% reflects something real happening inside organizations, and AI transformation is the primary driver,” Vishnu Shankar, chief data officer at Draup, a talent intelligence company, said in an email. “Not because companies are replacing workers, but because AI is increasing role complexity faster than existing training programs were designed for.”

AI remains a key theme for much of the change rolling through HR departments — but the shifting state of the job market also retains an influence, as do budget restraints.

How is AI prompting changes in employee learning?

In an AI-driven business environment, employers are struggling with a gap between “adoption and capability,” Chris Eigeland, CEO of Go1, a learning platform, said in an email. 

A Go1 survey of more than 2,000 learning and development leaders and workers found that 7 in 10 professionals said they use AI weekly, but only 14% said they considered themselves advanced users.

In other words, if employees lack the skills to adjust to the new technology, that creates a “value realization problem” for employers, Evan Metter, HR transformation practice leader at KPMG U.S., told HR Dive. After all, ROI on tech investment is tied almost entirely on the ability of the workforce to actually use it.

“What organizations are recognizing is that they can’t hire their way out of this challenge — that everyone needs to learn together in the face of new technology and ways of working,” Eigeland said — making upskilling a “strategic priority.”

The focus on employee learning may also be shorthand for a broader push toward changing how work is done, including “how employees make decisions, collaborate, communicate and adapt alongside increasingly automated systems,” Matt Poepsel, VP of talent optimization at software company The Predictive Index, told HR Dive in an email.

Is learning investment tied to the slower job market?

Thanks in part to the state of the economy, employers are slowing hiring, meaning employers must “become more intentional about developing the talent they already have,” Poepsel said. 

Training is a “more sustainable solution” than scrambling to compete for specialized AI talent, especially as the skills required continue to change at unprecedented rates, Poepsel continued.

The cost logic generally leans toward reskilling overall right now, Shankar noted, as “traditional labor-cost arbitrage has narrowed to below 20%,” meaning there’s no real cost advantage to hiring outside talent.

But these shifting budgets also reveal that, amid AI transformation, workforce capability and readiness may be the most important differentiating factors for employers seeking to stay afloat amid so much change — and that’s not exactly a new consideration for HR departments, Metter said.

Focus on the “total workforce,” Metter said, has long preceded AI, since it includes aspects of workforce management like contractors and vendors. But AI is now part of that cohort and needs to be considered as part of a workforce’s total capability. What work can it do and where is it most needed? These questions apply to all aspects of labor — and increasingly, that includes AI.

“The organizations making the strongest progress are not simply redirecting hiring budgets into incremental training. They’re treating workforce capability as a core business investment, much like technology infrastructure,” Eigeland said. “The real shift will happen when learning and workforce readiness become sustained board-level priorities, rather than budget items that fluctuate with hiring cycles.”

What kind of training is being prioritized? 

Not unexpectedly, technical training remains a key priority, including aspects like machine learning, AI and other tech-heavy skills — but training budgets are also going toward “human” skills, like emotional intelligence, communication and collaboration, Poepsel said.

“Every business is a people business, and the long-term winners will be equally high-tech and high-connection,” he said.

The type of training offered — such as group learning, on-the-job training, classroom setting and the like — also remains varied, Metter said. Employers have long sought ways to hyperpersonalize learning and coaching, in part to improve engagement and knowledge retention, but it’s difficult to find the proper triggers for learning in the flow of work, for example, Metter noted. AI can potentially change that.

“We think AI is going to make all of those modalities better and accessible and timely and relevant,” Metter said.

And while it is generally cheaper to train someone than to hire them, companies remain focused on training not just because of the economic implications but in part because of a “human recognition” of the value of internal mobility and training, Metter said. That remains strong, even in the AI era.

“For whatever reason, if it is the deeply human reason to invest in [people] flourishing or a deeply economic reason, they’re both leading us in the same direction,” Metter said. “It’s good business to be investing in the people part of our businesses.”

Training programs in industries with many front-line workers hinder workforce readiness by focusing solely on employer priorities without incorporating what employees say they need, according to a report from learning platform Chegg.

Employers and employees look at the same challenges and see different problems, Chegg CEO Dan Rosensweig noted in a media release. Employers pointed to a lack of practical skills as the biggest issues, the research found. By contrast, employees cited the lack of training in skills that offer a route to more responsibility or a senior position.

Training must address the concerns of both, the report stressed, and won’t be effective unless it “also speaks to employees’ ambitions and results in desired gains, whether in terms of career trajectory, remuneration, or job security,” the report said.

While employers said artificial intelligence and automation (36%) and digital and IT capabilities (24%) were the skills employees most lacked, workers pointed to training in leadership and people management (25%) and communication and teamwork (24%). 

Current training initiatives may be “failing to strike the right compromise between boosting performance in current roles, through building relevant technical skills, and teaching the durable skills needed for long-term career advancement,” Rosensweig explained in the report. 

The findings are based on a recent survey of 1,000 employers and 1,005 employees in 10 front-line-heavy industries across the U.S., including IT and software, finance and insurance, retail and manufacturing.

More than half of the employers said entry-level workers aren’t prepared for the job. However, there’s a disconnect on how well employees are being trained once they’re in the workforce; while 77% of employers believe their training programs are effective overall, only 58% of employees agreed.

Specifically, 51% of the employees who said their training wasn’t effective criticized it for being too general or not connected closely enough to their day-to-day responsibilities. Almost 4 in 10 said they aren’t getting enough hands-on practical learning; 34% cited insufficient coaching, and 27% pointed to weak managerial support. Almost three-quarters (71%) said their training has not led to any change in their pay or position.

One problem may be is that many organizations get fully invested in “license-to-operate” training efforts, such as those involving safety or compliance, but leave little time, budget or other resources for training that can improve current performance and also future-proof their business, according to an April 2025 report from RedThread Research.

Employers don’t have to invest equally in each area, the RedThread report emphasized. For example, license-to-operate efforts can focus on essentials like tightening proficiency requirements or reducing inconsistencies in training materials. Improving current performance may require more investment to determine which training components are missing and address those issues, the report said.

More HR leaders are identifying training as their top priority, according to HR Dive’s 2026 Identity of HR survey. The number jumped over the past year from 5% to 9%, a significant increase reflecting how AI is making roles more complex faster than traditional training programs were designed to address, experts told HR Dive.

Workforce skills gaps have real costs, the Chegg report found. Nearly one-third of employers said they spend the equivalent of a full day of work making up for skills shortfalls.

Workplace dependence on artificial intelligence has become increasingly widespread, with half of employees saying they depended too heavily on the technology, and just under a third saying they couldn’t function without it, according to a survey from IT firm GoTo.

Overdependence on AI has caused problems at work, with 39% of all workers and 46% of Generation Z saying their reliance on AI has weakened their skill sets and made them less intelligent. However, 60% of employees said they felt pressured to use AI to increase productivity.

When companies demand AI proficiency without providing the necessary training or effective policies to control its usage, misuse and workslop become more common, said report authors. Almost one in four IT leaders reported that AI-related mistakes “have already affected customers, clients, or their company’s bottom line.”

The research was based on a global survey of 2,500 workers and IT leaders and explored the realities of workplace AI usage as well as some of the potential problems the technology has introduced. 

Almost every IT leader (98%) said their company was using AI, and an additional 82% of workers said they were using AI on the job. In addition, more than 9 in 10 people surveyed approved of their organizations’ investments in AI.

Nonetheless, the technology is hurting worker confidence.

Just about 3 in 10 workers think AI is better at their jobs than they are, and 28% said they now trust AI more than they trust themselves. Even so, 41% said their overuse of the tech is going to negatively affect their long-term careers.

Notably, 83% people surveyed said they were concerned that they might be held responsible for an AI mistake, while 17% of all employees, and 30% of Gen Z workers, say they have blamed their own mistakes on AI.

Workers aren’t imagining the problem, either. Just under half of employees (43%) said they’ve used content created by AI even when it was low quality, and 43% of IT leaders said their companies aren’t very adept at gauging the ROI of the AI tools they implement.

GoTo CEO Rich Veldran said in a statement that when companies offer effective AI training resources for workers, it benefits productivity and overall corporate wellbeing. “The goal isn't just smarter technology,” Veldran said. “[I]t's a smarter, more empowered workforce.”

As worker sentiment sours on AI, providing clearer guidelines surrounding its usage may be even more critical. Recent research from national nonprofit Jobs for the Future found that out of more than 3,000 people, 44% believe the tech is a net negative when it comes to job hunting, creating wealth and improving quality of life.

HR professionals tend to speak highly of mentorship’s role in career development. In 2024, one chief transformation officer interviewed by HR Dive went so far as to say that having a mentor is a “priceless” component of learning and achieving future goals.

At the same time, it’s not always necessary for mentorships to be highly structured programs, said Michelle Kilroy, chief people and communications officer at The Weather Co. The organization offers both formal and informal programs, but it’s often the latter that allow employees to take advantage of opportunities to meet with other employees who pique their curiosity or who are doing interesting work.

“I personally think the most impactful ones are the organic, informal mentoring opportunities,” Kilroy said. “We foster a lot of opportunities for people to meet individuals like that, whether it is organically in their own departments or leaders across the organization.”

Additionally, informal mentorships provide flexibility that allows each relationship to meet different employees’ needs, she continued. That said, putting structure in place around the time frame of the relationship can help to bolster accountability and commitment to keep the arrangement from fizzling out.

It also may help for mentors to have certain qualities that are conducive to building trust with mentees. Looking back on her own career, Kilroy highlighted vulnerability as a key trait, particularly when her mentors relayed their experiences with impostor syndrome or situations in which they had reservations about a decision or mistake they had made.

“Vulnerability is a huge requirement in order to be considered authentic, and I think authenticity is what leads to trust,” Kilroy said. “Authenticity is really required for that trust building. You can’t have a good mentoring relationship without that trust.”

In order for mentorships to be beneficial, they need to be relevant and actionable, she noted. Both parties in a mentor relationship also have to agree on what the goal of the partnership is, whether that is advancement or the development of certain skills. The programs are especially valued for upskilling, according to a 2023 survey of hiring managers and job seekers by Express Employment Professionals.

Regardless of the goal, HR teams should keep employee experience front of mind when developing mentorship programs, according to Kilroy. That means having conversations about the kinds of experiences employees want and need to receive from both formal and informal programs rather than solely working backwards from the end goal of the mentorship.

“We might just jump straight to the results or outcomes, and I think we need to look at experience as being a foundation for whatever that desired outcome or result is,” Kilroy said.