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The most interesting stories in HR & AI weekly

Millenium Gives Employees Their Own AI “Twins”

Millennium is rolling out personalized AI “twins” that employees can delegate routine work to, from research and meeting prep to inbox management, with roughly 1,600 already in use. Why it matters: Rather than deploying one generic enterprise assistant, Millennium is experimenting with giving each employee a persistent AI counterpart that learns how they work. Reality Check: The twins don’t impersonate employees, make decisions for them, or share their knowledge with colleagues; Millennium is separately developing team-level “AI teammates.”

Trump Creates “Super Intelligence Force” to Coordinate US AI Policy

President Trump announced a new federal “Super Intelligence Force,” led by Director of National Intelligence Jay Clayton and including senior FTC and Defense officials, to coordinate government engagement on AI and help maintain U.S. leadership in the technology. Why it matters: AI policy is increasingly moving beyond technology regulation into national security, economic competitiveness, and workforce policy, raising the stakes for employers navigating AI adoption. Reality Check: The announcement is light on operational detail, and it remains unclear what authority the new task force will have or how it will interact with existing agencies and AI oversight efforts.

Reflection Says New Model Could Cut Enterprise Compute Costs

Reflection AI unveiled Beam, an upcoming open-weight model it says can deliver competitive reasoning performance using substantially less computing power. Why it matters: If those efficiency gains hold up, enterprises could run powerful AI models at significantly lower infrastructure costs, potentially improving the economics of deploying AI broadly across functions like HR. Reality Check: The cost advantage is based largely on vendor-reported performance claims, and real enterprise savings will depend on deployment, usage, infrastructure, and how Beam performs outside benchmarks.

OpenAI to Watermark AI Text in the EU

OpenAI will add invisible watermarks to eligible ChatGPT and Codex text outputs in the EU over the coming weeks, with optional watermarking available globally for select API models. Why it matters: HR should clarify acceptable AI assistance in applications, assessments, and employee work as tools for identifying AI involvement evolve. Reality check: Detector access is initially restricted, editing can weaken detection, and a watermark cannot establish how much human effort went into a passage.

Decision-Ready Workforce Planning (October 14 | 12:00–12:30 PM ET | Open to All)

How can workforce planning remain useful when skills, capacity, and technology are changing faster than organizations can predict? Join us for a complimentary 30-minute briefing on our latest research and practical approaches for building more decision-ready workforce plans in the AI era.

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Genpact Rebuilds HR for an AI-Enabled Enterprise

Genpact is redesigning HR around AI and skills intelligence, including an AI-powered HR advisor, conversational workforce analytics, automated skills inference and AI-enabled learning. Key Insight: Don’t automate the complexity you already have. Genpact simplified its HR technology and data foundation first, cutting applications by 30%+ and integrations by 60%+, before scaling AI.

We’d love your input on our research agenda.

AWS research found one enterprise had reached 88% AI adoption, yet fewer than one in 5,000 interactions produced genuinely better work, reinforcing its finding that AI value depends less on how many employees use the technology than how well they use it. Why it matters: HR leaders may need to shift AI strategies from driving adoption and providing training toward building deeper capability through hands-on practice, progressively harder challenges, and redesigned workflows. Reality Check: The striking 1-in-5,000 figure comes from a single organization, and AWS explicitly says its broader qualitative findings aren't intended to be statistically generalizable.

Revelio Labs’ September labor-market tracker finds 90% of the year-over-year change in work activities is occurring within occupations, while employment among 22–25-year-olds in the most AI-exposed occupations is down 20% relative to the least exposed. Why it matters: The data suggests HR should focus not only on which jobs AI may eliminate, but on how existing roles, career paths, and entry-level opportunities are being redesigned. Reality Check: AI exposure isn’t synonymous with job loss; AI-adopting firms are growing headcount faster than non-adopters, although those gains are heavily concentrated in senior roles.

A new three-year ethnographic study of a multinational company’s AI recruiting initiative found that the pursuit of better data continually expanded the project’s scope, creating new work, monitoring, and standardization across HR and the business. Why it matters: HR leaders may underestimate how much organizational change and ongoing data production sit behind seemingly straightforward AI applications. Reality Check: Better data can improve AI, but the researchers warn against assuming that ever-more data will eventually produce perfectly objective decisions; an elusive goal they call “epistemic enchantment.”

Several California workplace-AI bills we’ve highlighted in recent newsletters are now law: SB 947 (“No Robo Bosses Act”) requires meaningful human review when AI is the primary basis for discipline or termination; SB 951 (expanding WARN requirements) requires employers to disclose covered mass layoffs substantially caused by AI or automation; and AB 1883 (emotion recognition & neural monitoring) AI-powered workplace surveillance used to infer workers’ emotions or collect neural data. Why it matters: California is moving from broad AI principles to specific rules governing how employers use AI to manage, monitor, and displace workers. Reality Check: These laws don’t prohibit most workplace AI, but they raise the compliance bar around consequential decisions, surveillance, and workforce reductions, and could provide a model for other states.

Pearson is acquiring Workera, an AI-native platform that uses adaptive assessments and simulations to measure employees’ demonstrated skills, including AI fluency, with customers including Accenture, ServiceNow and the U.S. Space Force. Why it matters: As companies invest heavily in AI upskilling, the acquisition reflects growing demand to verify what employees can actually do, rather than relying on course completion or self-reported skills. Reality Check: Workera’s promise of a “live” picture of workforce capabilities is compelling, but claims that these assessments can reliably inform broader decisions like redeployment and workforce planning still need to be proven at scale.

Workday Cuts Another 500 Jobs in Second Restructuring This Year

Workday is cutting roughly 2.5% of its workforce, about 500 employees, primarily in Product and Technology, its second round of layoffs this year, while saying it will continue hiring in strategic areas. Why it matters: The restructuring is notable for a major HR technology provider that is simultaneously reshaping its product organization and investing heavily in new growth priorities. Reality Check: Workday has not attributed these layoffs to AI; despite its growing investment in agentic AI, the company describes the move more broadly as aligning teams with strategic priorities.

Gloat is embedding The Josh Bersin Company’s Galileo content into its AI agents, allowing them to combine Gloat’s workforce data with Bersin frameworks and benchmarks when supporting activities such as succession, performance, and workforce planning. Why it matters: The move closely mirrors HiBob’s Galileo integration announced just weeks ago and points to an emerging HR-tech model: combining company workforce data with an external library of HR content to ground AI agents. Reality Check: Treat claims about the quality of the underlying “expert” guidance cautiously; The announcement comes from the commercial partners themselves, and there’s little independent evidence yet that adding proprietary HR frameworks produces better workforce decisions than other forms of AI grounding.

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Until next week,

Mike & Adam

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