The human resources environment is undergoing a continuous transformation as organizations navigate the integration of artificial intelligence (AI) into their operations.
HR leaders hear promises and warnings about the power of AI from every direction: news headlines, C-suite demands, employee expectations, industry analysts, consultants and technology vendors. Considering the swift market momentum of AI—in both the workplace and personal pursuits—HR teams are endlessly presented with tech-related options and initiatives.
But the reality is that each organization—depending on location, industry and ethos—will acquire and use artificial intelligence in its own way. There is no sweeping essence of how HR fits into the AI equation, as each workplace is unique in the ways it balances risk, innovation, business goals and enterprise readiness.
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The shifting AI narrative
As Rebecca Wettemann, CEO of industry analyst firm Valoir, wrote in December 2024 for HR Executive, a year ago, generative AI felt like the “golden ticket to business transformation.” In 2023, companies eagerly built or integrated large language models (LLMs), fueled by promises of exponential benefits and a competitive edge, she wrote. She believes that now the narrative has shifted: “What started as a ‘fear of missing out’ (FOMO) on AI has transformed into a ‘fear of messing up’ (FOMU) as organizations and vendors alike tread cautiously to avoid costly mistakes.”
Despite these concerns, key trends are driving the urgency for HR digital transformation, with AI at the heart of the matter, according to Anna Carlsson, founder of Stockholm-based analyst firm HR Digi who will discuss the “HR 2030 Journey” next month at HR Tech Europe in Amsterdam. She identifies a talent shortage, rising employee expectations, the need for data-driven decisions and a focus on sustainability as momentum builders. “Transformation is no longer optional—it’s essential for staying competitive,” warns Carlsson.
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Maintaining human-centered leadership
Implementing AI ethically, cost-effectively and with a strong focus on employee experience is a balancing act. One thing remains clear: In the U.S., EU and elsewhere, AI-driven decisions must ensure humans stay in control of key career-related choices.
Industry analyst Mervyn Dinnen says HR leaders can cultivate a purpose-driven work culture that leverages AI responsibly and prioritizes employee wellbeing and inclusivity, but it will require a human-centered approach to leadership across the business.
He says employees should be meaningfully involved in shaping how AI supports and aligns with their work. “There will no doubt be concerns from some of the workforce that AI might replace human input, and these fears need to be allayed by leadership,” advises Dinnen.
One way to address this anxiety is by designing AI systems to act as assistants and not authority—allaying human fears and maintaining some human oversight. “This can be achieved by ensuring AI is leveraged for automating tasks in a way that will allow employees to focus on creative, strategic and more meaningful work that gives satisfaction and boosts employee engagement,” says Dinnen. He’ll talk more about keeping the human in human resources at HR Tech Europe on March 4-5.
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The evolution of AI in skills-based work
A skills-based workforce relies on a strategy in which organizations prioritize employees’ skills over traditional job roles—an increasingly talked-about approach that many experts believe will be made easier with AI. There’s been a significant increase in the market size of technology available to support this approach, with RedThread Research firm identifying 83 skills tech providers in 2024, up from 55 in 2022. RedThread analysts say that skills tech companies are also scaling quickly, but does this market growth reflect the needs of HR professionals?
According to the latest Future of Jobs Report from the World Economic Forum (WEF), the pace of skill transformation has moderated recently, yet remains significant: “Workers can expect that two-fifths of their existing skill sets will be transformed or become outdated over the 2025-2030 period.”
As organizations adapt to this emerging reality, analytical thinking has emerged as the cornerstone of future workforce capabilities, with seven out of 10 companies considering it essential for 2025. This is followed by resilience, flexibility and agility, along with leadership and social influence, according to the WEF report.
However, both people and jobs are complicated, and “fit” is a continuum, according to a recent HR Executive article by Wharton professor and NAHR Fellow Peter Cappelli. “There are better ones and worse ones when it comes to meeting the minimum job requirements and sorting that out is really difficult,” he wrote.
Cappelli believes HR professionals need to put employees and candidates through skill testing more frequently, despite the high cost. “Skills tests mainly measure only one task, and virtually all jobs require multiple tasks, so we will likely need multiple tests,” wrote Cappelli.
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The current state of AI in HR adoption
Implementation of AI in HR reveals a striking disparity between potential and current usage. Industry expert Josh Bersin notes a crucial distinction in implementation approaches, saying: “Clearly, just ‘giving people an AI tool like MS Copilot’ has the lowest ROI.” In a recent interview, he told HR Executive that companies that simply “turned on Copilot without any real focus on training and applications are not seeing huge returns.”
Still, many HR departments have only dabbled in generative AI, without making much progress beyond content generation. According to Payscale’s Compensation Best Practices Report, the current use of AI in HR is limited. Specifically, 21% of organizations use AI for managing or generating job descriptions, 18% for parsing resumes and identifying candidates, and 17% for creating or supporting learning and development or standard HR documents.
HR Executive‘s recent survey, What’s Keeping HR Up at Night?, found that only 5% of HR leaders cited AI as a key technology they are currently using, prioritizing HRIS, payroll and performance management tools instead. However, nearly 34% identified AI, including generative and agentic AI, as one of the most needed HR technologies.
These figures underscore the considerable gap between AI’s potential and its current application in HR practices. In contrast, organizations implementing focused AI solutions are seeing remarkable results. “Companies that buy focused applications like Paradox, Eightfold or Galileo can see massive returns,” Bersin explains. “In the case of Paradox, companies like McDonald’s see time-to-hire improvements by orders of magnitude.”
The EU AI Act is often referred to as the leader in the regulation of artificial intelligence. According to Dragos Adascalitei, research officer at EU agency Eurofound, AI adoption in Europe varies significantly across countries, regions and industries.
He says, generally, AI deployment is more widespread in Nordic and continental European countries, while it is less common in Southern and Southwestern Europe. For example, in Denmark, over a third of companies use AI systems, whereas in Romania and Bulgaria, fewer than 10% of businesses have adopted such technologies, says Adascalitei.
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Barriers and compliance concerns
One significant barrier to comprehensive AI adoption, particularly in financial planning and cost optimization, lies in data quality and accessibility. As Bersin points out, “The tools here are new and they are totally dependent on having clear, accurate data. So, if you try to use any AI tool for financial planning, you need good workforce planning, headcount and budget data.”
If the data is flawed or biased, says Eurofound’s Adascalitei, there is a high risk that the AI system will replicate those biases. In such cases, using AI to eliminate bias in decision-making becomes “almost nonsense,” he adds.
Asha Palmer, senior vice president of compliance for learning platform Skillsoft, warns HR leaders of the reality of the rapid development of AI outside of regulatory environments. She says that organizations must remain agile to stay compliant. “Put somebody in charge of monitoring what’s happening” in the marketplace. She says the near-overnight appearance of DeepSeek is the perfect example of why business leaders need to track the risk of new technology on the workforce.
The traditional view that company growth comes solely from hiring more people is outdated—according to Bersin. He says that talent acquisition (TA) professionals need to be part of this shift. However, the Bersin team found that 77% of TA leaders say they lack visibility into their company’s strategic planning. “Many are simply receiving job requisitions and filling them,” says Bersin. “While that may be fine for some, it can lead to over-hiring or placing the wrong people in the wrong roles.”
He says the bigger picture is how AI enhances overall business operations—tools for identifying internal talent, assessing skills and understanding who is performing well and who isn’t. The transformation of talent through AI “isn’t just about making hiring faster and more efficient—it’s about fundamentally changing how companies manage and leverage their workforce,” says Bersin.
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Common pitfalls in AI transformation
Many organizations treat modernization as a tech upgrade rather than a business transformation, says HR Digi’s Carlsson. “They rush to buy systems, believing technology alone will solve their challenges,” she notes. “Without a clear why and what, they risk digitizing outdated processes instead of improving them.”
There’s a growing concern about organizations prioritizing easy victories over substantive transformation, Bersin warns. “The risk is that the company buys something and doesn’t go through training and job redesign in a systemic way, and then concludes ‘AI isn’t adding much value,’ ” he says. “These tools require HR to rethink how they work, and that takes training and support from the vendor on real-world HR use cases.”
Carlsson agrees that a lack of change management and training is sure to stall adoption. “Generative AI and other modern HR tech solutions require new ways of working,” she says. Carlsson has found that, unless there is a strong focus on adoption, employees stick to familiar habits, leading to low or no impact.
AI-related pitfalls are often embedded in the culture of the organization. Brian Hackett, founder of the leadership network The Learning Forum, says that many companies simply aren’t prepared with the data and job architecture to roll out AI-supported skills functionality. He says that, in many organizations, this information is “owned by” the compensation teams, and they can’t or won’t price jobs based on skills.
He also says that many CHROs don’t have AI for HR on their radar and plenty of HR leaders are still working on RTO and other immediate issues. Still, he says, CHROs who are preparing for AI have helped foster a culture of innovation where employees and leaders are building AI-driven tools that help them do their jobs. “This will make you indispensable,” Hackett says.
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Keys to successful implementation
The successful integration of AI in HR requires a comprehensive approach that goes beyond mere technology adoption. Carlsson emphasizes that by 2030, digitalization will be a defining factor in business success.
“HR digital transformation will shift from HR system implementation to true business transformation,” says Carlsson. Once organizations have established a solid foundation, they can explore how to evolve with technology and AI as strategic partners. The emphasis will shift from simply automating processes to enhancing the employee and manager experience while addressing business needs.
“Success will depend on HR people with a digital focus as well as business alignment, ensuring that technology adoption leads to real impact rather than just surface-level digitization,” according to Carlsson.
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The importance of post-implementation support
Melissa Shelley-Höjwall, global HR tech leader for fashion retailer H&M Group, highlights a critical aspect often overlooked in digital transformation: post-implementation support. “It is surprising to me that so many tech projects put 95% or more of the budget on releasing a system or tool,” she notes. “We know that most change projects fail due to processes and tools not being taken into use after the launch.”
She advises HR leaders to secure adequate, proactive and dedicated support for end-users from the launch and several months thereafter. “I call this role a local ambassador since it is ideal that they are sitting geographically close to end-users where possible,” says Shelley-Höjwall. She also recommends that the ambassadors be involved throughout the life of the project, even before launch.
When implementing AI and other new technology, it is wise to have a reference group of line managers and employees representing different personas, according to Shelley-Höjwall. She suggests that these individuals should provide input on usability, ideally by participating in demos during vendor selection, offering feedback during the design phase and being involved in user acceptance testing.
These colleagues tend to become ambassadors who will speak positively in communication meetings and training for the wider population. “A project will have more business credibility,” says Shelley-Höjwall, “if business representatives have influenced and validated a new process or tool, making it much harder for others to say ‘What idiot selected this system?'”
Learn more from experts including Josh Bersin, Anna Carlsson, Mervyn Dinnen, Melissa Shelley-Höjwall and Rebecca Wettemann at HR Tech Europe 2025. Register now.
