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The most interesting stories in HR & AI weekly

HR Jobs Are “Booming”, But the Data Deserves a Closer Look

Josh Bersin argues that HR jobs are booming despite AI, citing Lightcast data showing HR job postings growing 6% annually over the past two years. Why it matters: The data push back against predictions of an imminent AI-driven HR jobs apocalypse and suggest demand for HR capabilities remains resilient. Reality Check: Job postings aren't employment; more postings can reflect higher turnover, longer time-to-fill or increased recruiting activity without translating into more HR jobs, so the data make a strong case that HR hiring remains resilient but a weaker one that HR employment is “booming.”

Women Are Missing Out on the AI Jobs Boom

Women accounted for just 26% of U.S. AI hires in 2025, with the gender gap widest in higher-paying technical roles. Why it matters: As AI roles become an increasingly important path to economic mobility and leadership, HR leaders risk carrying existing gender disparities into the next generation of work. Reality Check: AI jobs remain a small share of the overall labor market, but today’s hiring patterns could shape who builds, leads, and benefits from AI over the long term.

Lumen Puts Managers at the Center of AI Adoption

Lumen’s Chief People & AI Enablement Officer Ana White says the clearest signal of whether AI adoption is taking hold is in the “middle” of the organization, where managers translate AI strategy into everyday decisions about when and how employees should use AI. Why it matters: As companies move from AI pilots to scaled adoption, HRBPs may have an increasingly important role helping managers redesign workflows, establish guardrails and coach employees on where human judgment still matters. Reality Check: Lumen doesn’t share adoption data or measurable results in the article, so this is more an emerging management playbook than evidence that the approach produces better AI adoption.

Gartner Predicts HR and IT Will Blend, Somewhat

Gartner predicts 30% of organizations will form blended HR-IT teams by 2029 as agentic AI blurs responsibility for work, talent, and technology. Why it matters: Closer HR-IT collaboration will be critical, but the bigger unlock may be HR partnering with leaders of lines of business, Finance and Operations to rethink workforce capacity, costs, and work design as AI scales. Reality Check: A 30% prediction is hard to translate into planning or incorporate into decisions; it suggests the model will gain some traction, but offers little guidance on whether any individual organization should plan around it.

After a 75-day pilot in which 273 candidates for senior technical roles completed AI interviews, Zapier says 97% rated the experience excellent, candidates averaged 31 minutes explaining their reasoning, and recruiters saved 228 hours, prompting the company to test offering an AI screen to every applicant for certain roles while keeping humans responsible for evaluation and hiring decisions. Key Insight: Rather than using AI to screen more candidates out, Zapier is experimenting with AI to screen more candidates in, replacing recruiter bandwidth as the gatekeeper and potentially giving applicants who might have been rejected on their resume alone a chance to demonstrate their capabilities.

Survey Says: ChatGPT was the leader among respondents to last week’s poll, with 25% selecting it as their preferred day-to-day GenAI tool.

Which general-purpose GenAI tool do you currently prefer for your day-to-day work?

Gallup finds organizations are increasingly leaning on managers to drive AI adoption, with 78% of CHROs encouraging peer learning, 57% providing managers with AI training and 62% creating AI centers of excellence or internal champions. Why it matters: As AI adoption shifts from a technology rollout to a change-management challenge, managers are becoming a critical bridge between enterprise AI strategy and how employees actually change their day-to-day work. Reality Check: Managers already face expanding responsibilities and wider spans of control, so adding “AI transformation leader” to the job without additional capacity and support could undermine the adoption companies expect them to drive.

A new Frontiers in Psychology experiment found that employees reacted significantly worse to performance feedback labeled as fully AI-generated, while feedback written by a manager and refined with AI produced reactions comparable to fully human-written feedback. Why it matters: For HR teams designing AI-enabled performance management, the emerging sweet spot may be using AI to improve a manager’s feedback rather than outsourcing the judgment and message to AI. Reality Check: The study involved just 192 participants responding to a hypothetical scenario, not real performance conversations, so the findings are suggestive rather than definitive, but they reinforce the idea that employees still place meaningful value on visible human ownership of feedback.

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Until next week,

Mike & Adam

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