This week, I talk with John Sumser, publisher of HR Examiner and a widely known industry analyst. We talk about compensation as the foundation of work itself – everyone works for money, after all – and how fair and effective pay is prerequisite for employee engagement, not a replacement. We look at this history of AI – it’s older than you may realize – and how it’s been used throughout HR.
Sumser’s cautious about the explosion of modern AI tools. While the technology is improving HR processes, it remains uncertain whether it’s truly making people better at things like recruiting or workforce management. For all the focus on automation, however, hiring still depends on human decision-making. Resumes are marketing documents designed to get interviews, not complete reflections of candidates, John notes, just as job descriptions rarely describe the actual work. AI, can’t yet replace that human judgment.
HR’s adoption of AI mirrors past technological shifts: there is initial excitement, but it takes years before meaningful results emerge. Many “AI agents” today, Sumser notes, simply replicate old features like employee self-service, adding little true innovation. The real challenge lies in validating AI-generated insights. That’s especially important because large language models still make errors roughly 10% of the time. Still, early adoption remains valuable because those who learn how to use AI effectively will gain credibility and advantage.
While AI’s promise is vast, its integration into human systems of work will be a long, complex journey. We’re still in early days.
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Other News
Workers worry about perceptions of laziness when they use AI, even though more of them are using the technology. A study by SnapLogic found 81% of employees leverage AI tools and 57% use AI agents regularly to save time. Despite this, workers worry about being seen as lazy (43%) or being second-guessed (24%). Most trust AI and their colleagues to maintain work quality, yet 52% expect to manage more AI agents than humans in the future, which 61% believe will be easier. Only 36% say they’ve had formal AI training. More than half (54%) say they’re self-taught. [TechRadar]
Recruiters increasingly leverage technology to reshape talent acquisition, with 65% using AI in workflows and 67% planning to boost tech spending, according to Employ Inc. While automation enhances efficiency, organizations prioritize fairness, transparency and human oversight. More than three-quarters (76%) of recruiters expect to replace their primary platforms within two years to adopt scalable, AI-driven solutions. Meanwhile, candidate quantity has become the top priority over quality. Today’s HR teams must balance budgets with hiring needs, prompting investment in process optimization, diverse talent pools, internal mobility and pipeline development. [HR Dive]
ServiceNow rolled out AI agents designed to automate repetitive HR tasks. The intelligent, context-aware agents handle end-to-end HR workflows across departments while governed by ServiceNow’s AI Control Tower for security and compliance. Employees can interact via a single AI front door or voice agents, while HR business partners gain AI-powered dashboards to detect turnover risks and automate interventions. The platform aims to eliminate busywork, boost productivity and enable proactive, seamless HR operations. [ServiceNow]
Qualtrics announced a $6.75 billion agreement to acquire Press Ganey Forsta, a leader in experience measurement and analytics. The acquisition aims to enhance experience management across industries. By combining Qualtrics’ AI capabilities with Press Ganey Forsta’s industry expertise, the companies plan to improve employee, patient and customer experiences at scale. [Qualtrics]
Just a thought: AI assistants aren’t particularly good journalists, concludes a study by the European Broadcasting Union. Overall, 45% of AI’s answers to news-related questions had “at least one significant issue” with accuracy, sourcing, context, editorializing and distinguishing opinion from fact. Some 20% of answers contained major errors, including hallucinations and outdated information. Missing, misleading or incorrect attributions occurred in 31% of the AI-reported news while a lack of context affected 14%. “[The] AI fails to answer the question with a simple and accurate ‘we don’t know,’” said a BBC journalist involved in the study. “It tries to fill the gap with explanation rather than doing what a good journalist would do, which is explain the limits of what we know to be true.” [EBU]
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