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The most interesting stories in HR & AI weekly

Former GE CHRO: AI Is Rewriting the CHRO’s Job

Former GE, American Express, and Pepsi Bottling Group CHRO Kevin Cox argues that HR leaders must become architects of the “human-to-AI organization,” redesigning operating models, talent development, succession, and transformation while staying grounded in a clear personal purpose. Why it matters: As AI disrupts career ladders and flattens organizations, CHROs will need to make sharper choices about how work is divided between people and technology, and whether their own calendars reflect those priorities. Reality Check: HR cannot remove all the anxiety created by AI transformation; credible leadership requires defining the reality, offering justified hope, and creating enough space to think clearly about what must change.

Nvidia Launches Open AI Security Alliance After OpenAI Cyber Incident

Nvidia has launched the Open Secure AI Alliance with Microsoft, Palantir, SpaceX, Hugging Face, and dozens of other companies to build open AI cybersecurity tools, arguing that open-weight models are essential for defending against increasingly sophisticated AI-powered cyber threats following the recent OpenAI-related Hugging Face security incident. Why it matters: The debate over open versus closed AI is shifting from an innovation issue to a strategic workforce and enterprise risk issue, with implications for how organizations build secure, AI-enabled operations. Reality Check: While the alliance underscores growing confidence in open AI for defense, most organizations are still in the early stages of developing the governance, security, and talent capabilities needed to safely deploy these technologies.

Anthropic’s AI Jobs Debate: Data Says “Not Yet”

Anthropic’s head of economics argues AI has not yet caused meaningful white-collar job losses, citing stable unemployment and strong labor market data, while acknowledging softer hiring for entry-level, AI-exposed roles and leaving open the possibility of greater disruption over time. Why it matters: HR leaders should focus less on imminent mass layoffs and more on how AI is reshaping hiring, early-career talent pipelines, and workforce productivity. Reality Check: Despite high-profile predictions of an AI-driven employment crisis, current labor market data suggests organizations remain in a transition period where augmentation, redeployment, and slower hiring are more evident than widespread job displacement.

Altman Says the “Singularity” Is Already Here

Sam Altman argues the AI "singularity" (when AI helps accelerate its own development) is already underway because AI is accelerating scientific discovery, software development, and even AI research itself, creating compounding feedback loops that could dramatically speed the pace of innovation. Why it matters: If AI is beginning to accelerate its own development, the pace of workforce change could become increasingly difficult for organizations to anticipate, making continuous workforce planning and skills adaptation more important than periodic transformation efforts. Reality Check: The singularity remains a highly debated concept, and many AI leaders, including Jensen Huang, argue predictions about runaway AI progress remain speculative.

After identifying "sunrise" and "sunset" skills through strategic workforce planning, Standard Chartered quantified the value of reskilling, estimating it would save roughly $49,000 per employee compared to hiring externally, and used that business case to launch an internal talent marketplace where employees can be matched to projects based on skills rather than job titles, accelerating work across functions and geographies. Key Insight: The marketplace emerged after the bank identified its future skills, quantified their value for the board, and began treating skills, rather than jobs, as the primary unit of workforce planning.

Lion redesigned its end-to-end employee journeys before introducing AI, consolidating HR, IT, and finance workflows into a unified platform that increased employee self-service by 200%, cut People Services resolution times in half, and improved People function operating costs by roughly 30%. Key Insight: To avoid automating complexity, redesign work first, then digitize second, and automate with AI third.

OpenAI’s latest research analyzing more than 800,000 ChatGPT work conversations found that nearly half of occupation-specific AI use now involves tasks outside a worker’s traditional role, with HR professionals among the top groups using AI to perform cross-functional work such as legal, financial, marketing, and technical tasks. Why it matters: AI may reshape organizations less by replacing jobs and more by enabling employees, and especially HRBPs, to take on broader, more strategic responsibilities across functions. Reality Check: While job titles may not change overnight, AI is already changing the mix of work people do, making adaptability and AI fluency increasingly valuable competitive advantages.

Everest Group: AI Is Making Hiring Harder, Not Easier

AI-generated resumes, interview preparation, and application tools are making it harder for employers to distinguish genuine capability from polished AI-assisted presentation, with 54% of organizations reporting weaker hiring signals and 45% increasing their reliance on assessments. Why it matters: As AI becomes embedded in the hiring process, organizations may need to rethink how they evaluate candidates, placing greater emphasis on demonstrated judgment, problem solving, and work samples over resumes alone. Reality Check: AI isn't just changing how people work, it is changing how they apply for jobs, forcing employers to redesign hiring practices alongside the workplace itself.

CompTIA: AI Adoption Is Outrunning AI Skills

While 80% of professionals report using AI regularly, only 29% consider themselves highly familiar with the technology, and most are learning through informal channels rather than employer-sponsored training, leaving much of their AI use disconnected from business workflows. Why it matters: The survey suggests organizations can improve training by making it role-specific and giving employees dedicated time and clear expectations to build AI capabilities as part of their jobs, not as an extracurricular activity. Reality Check: The challenge isn't convincing employees to use AI; it's helping them integrate AI into the work that matters most.

As AI automates routine work, employers are placing greater emphasis on analytical thinking, creativity, adaptability, and judgment while redesigning entry-level roles around supervising and improving AI-generated work rather than completing repetitive tasks. Why it matters: Entry-level job descriptions, campus recruiting, interview guides, and development programs may all need to shift from emphasizing technical proficiency toward evaluating and building judgment, adaptability, and AI collaboration. Reality Check: It's easier to say "hire for judgment" than to do it; most organizations have mature ways to assess technical skills, but far fewer know how to reliably evaluate judgment and human-AI collaboration in early-career candidates.

KPMG: Why Some High Performers Become AI Underperformers

KPMG found that junior employees with stronger critical thinking and domain expertise sometimes performed worse than peers with weaker skills because they challenged AI in unproductive ways, while top performers focused less on correcting AI and more on framing problems, directing its reasoning, and iteratively improving outputs. Why it matters: As AI raises the baseline for knowledge work, competitive advantage may come less from knowing more and more from knowing how to orchestrate AI effectively. Reality Check: Organizations may need to rethink what they measure and develop; moving beyond AI literacy toward judgment, problem framing, and human-AI collaboration.

While 77% of HR professionals remain bullish on AI, most are still using it for drafting, brainstorming, and summarizing rather than redesigning workflows, with only about one-third experimenting with agentic AI despite those users reporting significantly greater business impact. Why it matters: The competitive advantage may no longer come from adopting AI, but from rethinking HR work around autonomous workflows and human-AI collaboration. Reality Check: The biggest barrier appears to be organizational change, not the technology, as many HR teams remain hesitant to delegate meaningful work to AI.

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Until next week,

Mike & Adam

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