AI & Future of work - 8 May 2025
IBM fires hundreds of HR staff.
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Happy Friday!
Very honoured to be back on the 2025 HR Tech 100 Influencers list - thank you HR Executive for including me! As said on LinkedIn, a list is just a list but this list in particular has led me to so many interesting meetings, conversations and discussions!
Also, the four-year-anniversary of FullStack HR passed without me noting it, well done me. (yes, I started this before the whole AI-bonanza. yes, I had some “hot takes” on crypto, please don’t read them.)
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That said, let’s get to it with this weeks latest news that I deem relevant for us in HR and that AI has helped me summarize!
(But I have as always curated it and the “why it matters” are my own thoughts.)
Need help with your AI-prompting?
Sara Breman is hosting a 3-hour long masterclass in prompting in Stockholm in the 16th of June. 3990 SEK let’s you grab a spot, I’m betting you won’t be disappointed!
1. Google Cuts 200 Sales & Partnership Roles to Re-Route Budget Toward AI Infrastructure
Alphabet confirmed that about 200 staff across its global business organization were let go as the company “re-focuses resources on data-center capacity and generative-AI projects.” The layoffs follow earlier trims in the devices division and bring 2025 reductions to roughly 1 % of Google’s workforce. The firm said redeployed headcount and internal mobility will cover most customer accounts, but analysts note continued pressure to fund Gemini and TPU roll-outs.
Why it matters for HR: HR teams must rapidly re-balance talent strategies when revenue units shrink yet AI engineering ramps up. Expect more demand for internal talent marketplaces, reskilling funds, and retention programs.
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2. IBM CEO Says AskHR Bots Replaced “A Few Hundred” HR Staff – and Freed Cash to Hire in Tech Sales
Arvind Krishna told the Wall Street Journal that automating rote HR tasks with large-language-model agents let IBM invest in software engineers and “critical thinking roles,” even as HR headcount fell. He reiterated a hiring bias for customer-facing talent with AI skills and predicted AI cost curves will “explode demand.”
Why it matters for HR: Oh boy. The comment signals that AI efficiency savings inside HR will be reinvested elsewhere – making HR both the test bed and the budget source. Interesting move from IBM, to say the least. I wonder what effects it will have long-term.
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3. Salesforce Rolls Out “Career Agent” in Slack After 40 % Internal-Mobility Pilot Success
Career Agent and its companion platform Career Connect use AI to infer employee skills, recommend learning, and nudge workers toward open roles. In a three-month pilot 74 % engaged and 28 % applied for new jobs; Q1 data show half of all vacancies now filled internally. The company has frozen many external engineering hires, citing a 30 % productivity lift from AI.
Why it matters for HR: This is a live example of AI-driven talent marketplaces that cut recruiting spend, surface transferable skills, and make internal mobility measurable. We should study the design: skills inference, mentor matching, and just-in-time training.
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4. New Research – Large Language Models, Small Labor-Market Effects
A Becker-Friedman working paper (rev. 1 May 2025) analysed 25 000 Danish workers and found that despite rapid chatbot adoption, earnings and hours remained statistically unchanged (±1 %). Time savings averaged 3 % and wage pass-through was weak, challenging big-displacement narratives.
Why it matters for HR: The findings temper automation panic and emphasise firm-level policy and training as the real levers. We can use the data to argue for deliberate job redesign and measured ROI tracking rather than blanket cuts. (also I have opinions on the study - separate article incoming)
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5. CrowdStrike Lays Off 500 Staff (5 %) as It Pursues a $10 B AI-First Strategy
The cybersecurity firm called AI a “force multiplier” for threat detection and cost efficiency but flagged hallucination risks in SEC filings. Savings will fund customer-facing and engineering roles.
Why it matters for HR: Another data-point on “AI takes our job”? Or a PR stunt? We must partner with risk and legal teams to balance AI speed with compliance, and to retain scarce cyber talent amid restructuring.
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6. LinkedIn Adds Conversational AI Job Search and Interview Coaching
Members can now type ambitions in plain language and receive role suggestions, skill-gap feedback, and premium mock-interview drills. The upgrade spans the entire recommendation stack using LinkedIn’s Economic Graph.
Why it matters for HR: External talent will arrive with AI-sharpened expectations and insights. HR teams should match the experience internally – and prepare hiring managers for interview scenarios where candidates have had AI coaching.
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7. Ethan Mollick Warns of “Personality Engineering” in Personality and Persuasion
Mollick documents how tiny tweaks in GPT-4o made the model sycophantic overnight and reviews studies showing AI agents can shift conspiracy beliefs by 80 % when given user data. He argues that hyper-persuasive bots will arrive before AGI and urges policy guard-rails.
Why it matters for HR: Employee well-being, corporate communications, and even labor relations may be influenced by persuasive AI. HR should draft ethical use policies and build literacy training so staff recognise manipulation patterns.
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8. It’s Me, Hi. I’m the Vibe Coder – Every’s Katie Parrott on Non-Tech Employees Building Tools
Parrott coins “vibe coding” for natural-language programming with AI. She profiles marketers and ops leads who ship internal apps via Cursor or Lovable, arguing that AI lowers coding barriers and flips the builder–user divide.
Why it matters for HR: Democratised tool-building is an upskilling and engagement goldmine. HR can seed “citizen-developer” sandboxes, recognise grassroots innovation, and refresh job descriptions to value problem-solving over formal coding credentials.
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9. How Companies Can Mitigate the Harms of AI-Driven Inequality
Bhaskar Chakravorti argues that AI is already stretching six fault lines, from wage and skills splits to energy costs and gives companies a three-step playbook: choose inclusive tech, fund large-scale reskilling, and bake fairness metrics into pricing and supply-chain moves.
Why it matters for HR: The piece turns inequality into an operational risk we can own. By auditing every AI roll-out for wage dispersion and promotion velocity, HR protects engagement and retention while proving that “green and fair” AI can still pay.
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10. How Human Intelligence Can Guide Responsible AI in the Workplace
Summary: Host David Green and Workhuman’s Kevin Heinzelman outline a human-first AI blueprint: keep people in the loop for high-stakes calls, train models on recognition data to reflect culture, and give cross-functional ethics councils veto power.
Why it matters for HR: Responsible-AI isn’t theory anymore; it is a trust and retention lever. Owning a living “AI playbook,” pairing roll-outs with empathy training, and using recognition signals to steer algorithms help HR turn ethics into a talent advantage.
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