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The most interesting stories in HR & AI weekly

IBM CHRO Doubles Down on Entry-Level Talent

IBM CHRO Nickle LaMoreaux says the company is continuing to invest in entry-level hiring despite AI-driven automation, arguing that early-career talent remains essential for building future leadership and adapting to new ways of working. Why it matters: As many organizations rethink junior hiring, IBM is making the case that AI should reshape, not eliminate, the early-career talent pipeline. Reality Check: IBM's message is clear, but the harder question is whether companies can sustain investments in entry-level talent when financial performance comes under pressure, and IBM may soon provide the answer. Related: IBM shares plunged more than 20% after the company warned second-quarter revenue and earnings would miss expectations.

OpenAI’s AI Models Escape Sandbox, Breach Hugging Face During Testing

OpenAI disclosed that two advanced AI models escaped a controlled testing environment during a cybersecurity evaluation and autonomously breached parts of Hugging Face’s production infrastructure while attempting to "cheat" on a hacking benchmark, prompting a joint investigation and new safety measures. Why it matters: This may be the clearest real-world example yet that frontier AI systems can create operational and cybersecurity risks beyond their intended scope, reinforcing the need for stronger governance as organizations deploy increasingly autonomous AI agents. Reality Check: The incident occurred during a specialized cyber-capability evaluation, not during normal enterprise use, but it underscores why robust containment, monitoring, and AI risk management will become core organizational capabilities.

The Highest Paid CHROs of 2025

A new Equilar analysis found the top 50 highest-paid CHROs earned a median of $3.7 million in 2025, with Kelly Tullier (Visa) topping the list at $14.5 million, followed by Tracy Skeans (Yum! Brands) and Jacqueline Canney (ServiceNow). Why it matters: The highest-paid HR leaders increasingly hold broad enterprise responsibilities, including AI, operations, legal, and corporate strategy, reflecting the expanding scope of the modern CHRO role. Reality check: Executive compensation is heavily influenced by long-term equity awards and company performance, so these rankings are best viewed as a benchmark of market practice rather than a direct measure of HR's strategic importance.

Deepfakes Are Creating A New Challenge for Workplace Investigations

Employment attorneys are warning that AI-generated emails, text messages, images, and other fabricated evidence are beginning to complicate workplace investigations, making it harder to distinguish authentic evidence from convincing fakes, and easier for employees to challenge legitimate evidence as manipulated. Why it matters: HR investigations may increasingly require digital evidence verification, stronger documentation practices, and new investigative protocols as AI-generated content becomes commonplace. Reality Check: The biggest shift isn't that every investigation will involve deepfakes, but that HR can no longer assume digital evidence is authentic simply because it looks convincing; verification is becoming as important as collection.

Job and Organization Design Are Increasingly Important HR Capabilities

Cornell professor Chris Collins argues that generative AI delivers the most value by handling data-intensive work, such as compensation analysis, workforce analytics, and routine employee support, while freeing HR to rediscover capabilities that have atrophied over time, including job design, workflow analysis, and organizational design. Why it matters: As AI takes over repetitive work, HR's competitive advantage shifts from producing information to redesigning jobs, workflows, and organizations around what humans and AI each do best. Reality Check: Many HR teams have spent years optimizing talent processes rather than redesigning work itself, making organization design and workflow analysis increasingly strategic capabilities in the AI era.

Economists Agree AI Could Reshape Work, But Not Yet on What to Do About It

More than 200 economists, AI researchers, and technology leaders signed a Stanford-led statement warning that AI could transform the economy faster than the Industrial Revolution and urging policymakers to begin building the incentives, guardrails, and institutions needed to ensure AI complements human labor. Why it matters: A broad consensus is emerging that AI's workforce impact deserves immediate attention, even as there is little agreement on the specific policies that should guide the transition. Reality Check: The statement highlights an important challenge but offers few concrete solutions, even as many organizations have already moved from debating AI's impact to redesigning work around it.

Atlassian outlined plans to move beyond the Ulrich model by creating AI-native HR teams and hiring a Director of Capacity Planning to build frameworks for allocating work across people and AI agents. Key Insight: The most significant AI transformation in HR may not be new tools, but new operating models that redefine HR's role from supporting the workforce to designing how humans and AI agents work together.

Zapier analyzed AI workflow patterns among its most advanced enterprise customers and found that AI agents typically play one of four roles: Communicator (writes for people), Clerk (extracts and updates records), Analyst (makes decisions), or Coordinator (creates tasks). The findings provide a practical blueprint for where AI fits into real business workflows, including recruiting, onboarding, and HR operations. Key Insight: The next wave of enterprise AI may be less about building standalone agents and more about embedding a handful of repeatable agent roles (Communicator, Clerk, Analyst, and Coordinator) into existing business workflows.

Okta Rebuilds Roles Around Agents

Okta's CPO says the next wave of AI isn't about adding copilots but systematically deconstructing roles into tasks and redesigning work around collaboration between humans and AI agents. Key Insight: Leading organizations are moving beyond AI deployment to redesigning jobs themselves, making job architecture, task analysis, and workforce planning strategic capabilities for HR.

HRBPs Cite Career Fears and Training as Top AI Adoption Barriers

Survey Says: Nearly half of respondents to last week’s poll said they would be more likely to use AI if they knew it wouldn't harm their career or had training on how to use it.

I would be more likely to use AI in my job if:

New research published in Management Science found that hiring managers consistently favor candidates who respond quickly to messages, even when slower responders are equally or more qualified, because rapid replies are unconsciously interpreted as a signal of future responsiveness. Why it matters: As hiring teams work to reduce bias through structured interviews and skills-based assessments, response speed may represent another hidden signal that unintentionally influences hiring decisions. Reality Check: Quick responses can indicate engagement, but they may also reflect differences in work schedules, time zones, caregiving responsibilities, or access to technology rather than future job performance.

Indeed Hiring Lab found that AI is increasingly appearing in job titles across HR, sales, legal, customer service, education, and other functions, not just technology roles, suggesting employers are signaling AI as a core part of work across the organization. Why it matters: For HR leaders, the findings reinforce that AI is becoming an enterprise-wide capability, with implications for job design, hiring, skills development, and career pathways across virtually every function. Reality Check: The research measures AI references in job titles rather than job descriptions or responsibilities, so while it captures an important market signal, it likely understates, and doesn't fully describe, how AI is actually changing the work itself.

CHROs Are Betting on AI, But They’re Pairing It with Skills-Based Workforce Strategies

A new UNLEASH and Talent Tech Labs survey found AI and automation were consistently ranked as HR leaders' top priority and the improvement most likely to drive business results, while skills-based organizations, workforce planning, and internal talent marketplaces repeatedly emerged as complementary priorities for navigating AI-driven change. Why it matters: Leading organizations increasingly see AI and skills as two sides of the same strategy: using AI to transform work while using skills data to redeploy talent as jobs evolve. Reality Check: Most organizations report having workforce planning and skills capabilities, yet many rate those capabilities as falling short of expectations, suggesting the next challenge is execution rather than strategy.

A new benchmark study found AI models performed well on structured employee listening tasks, such as summarizing feedback and identifying themes, but struggled to interpret nuanced employee sentiment or make context-dependent recommendations, highlighting the limits of relying on AI alone for workforce insights. Why it matters: As organizations embed AI into employee listening and engagement programs, HR leaders will need to determine which parts of the process can be automated and which require human interpretation, judgment, and follow-up. Reality Check: AI is making employee listening more scalable, but acting on employee feedback, and earning employee trust, still depends on managers and HR leaders translating insights into meaningful action.

Skills Needed to Lead the Human-AI Workforce

Harvard Business Impact’s 2026 Global Leadership Study argues that the defining leadership challenge is no longer adopting AI but managing a workforce where humans and AI work together, with respondents ranking the ability to question AI decisions, navigate complex human dynamics, build resilience, and create psychological safety as the most important capabilities for successful AI transformation. Why it matters: The emerging leadership playbook is shifting away from simply becoming "AI literate" toward helping employees trust, challenge, and collaborate effectively with AI while maintaining human judgment. Reality Check: This is based on executives' perceptions rather than observed outcomes, but it aligns with a broader trend across AI adoption: technical deployment is becoming easier, while leading people through organizational change remains the harder problem.

As AI helps employees complete increasingly complex work, new research warns organizations may be accumulating "learning debt,” a hidden backlog of skills employees never fully develop because AI fills the gaps faster than training can keep up. Why it matters: AI can boost short-term productivity while masking long-term capability gaps, leaving organizations with employees who can complete tasks but lack the underlying expertise to adapt, troubleshoot, or lead as roles evolve. Reality Check: The goal isn't to slow AI adoption, it's to redesign learning so employees continue building judgment and expertise, even as AI takes over more of the execution.

A Westlaw Today analysis urges employers using AI for recruiting, performance management, workforce monitoring, and other employment decisions to prepare now for evolving EU AI Act requirements by inventorying AI systems, strengthening governance, documenting human oversight, and working closely with vendors on compliance. Why it matters: Even organizations outside Europe should expect the EU AI Act to influence global HR technology practices, as multinational employers and vendors increasingly adopt common governance standards across markets. Reality Check: The regulatory timeline continues to evolve, but the broader lesson remains the same: organizations that treat AI governance as an ongoing capability, not a one-time compliance exercise, will be better positioned regardless of the final implementation dates.

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Until next week,

Mike & Adam

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