HR Data Labs

David, Mike and Vinay discuss how HR can measure work as AI becomes part of the workforce. They argue that headcount alone misses the shift: organizations need to understand which tasks people and AI handle, how AI changes people’s capacity, and how to use that capacity to create more value without losing the human contribution.  Key topics and takeaways  Measure work, not just headcount. The guests describe “workforce intelligence” as a way to manage and measure a blended workforce of people and AI coworkers.  More capacity doesn’t automatically mean less busyness. Vinay says employees may get time back from AI but feel pressure to do more. Organizations need to help direct that “capacity dividend” toward valuable work.  AI output still needs human oversight. The host points to extra quality checks, hallucinations and the volume of AI-generated work as reasons that adoption may not immediately save time.  Efficiency is only part of the opportunity. Mike says it is easier to frame AI as a way to reduce costs than to work out how people can use it to deliver new, distinctly human value to clients.  Treat AI as a workforce cost. Vinay says OneDigital assigns each AI coworker a salary to understand its operating cost. The guests discuss matching model capability and cost to the task, rather than using the most advanced model for everything.  Rethink how work is organized. Mike says organizations should look at the tasks that make up jobs, assign work to the right “unit,” and help employees adapt. He estimates the coming challenge will be mostly organizational change and adoption, rather than technology alone.  Human accountability remains important. Vinay argues that AI can make information more accessible, but human judgment, experience and accountability are what distinguish an organization.  Make AI learning part of education and work. Vinay encourages using AI to expand thinking, not just to get answers with less effort. He says people who avoid learning to use it may miss career opportunities.  People’s AI journeys differ. Mike describes AI as a source of new ideas and connections, while Vinay stresses that organizations need to understand what adoption means for individuals—not assume one approach suits everyone.  Names and resources mentioned  OneDigital — Mike and Vinay’s organization.  Work Carousel — episode sponsor; https://workcarousel.com/join/  AI tools and models: Claude, ChatGPT, Copilot, GPT-OSS, and open-weight, non-frontier and frontier models.  Hardware: NVIDIA DGX Spark.  Other platforms and organizations mentioned: Microsoft, Fiverr, Deloitte, Accenture, Instagram, Penn State.  Terms discussed: workforce intelligence, AI coworkers, centers of intelligence, tokens, and retrieval-augmented generation (RAG). 

The host catches up with Teri, an old friend, at HR Technology in Las Vegas. They look back at 2026 and ahead to 2027 for HR technology and AI. Teri says nearly everyone is using AI now, but companies still aren't seeing the bottom-line results. They also discuss rising AI costs, how hard it is to measure return on investment, and whether AI will give us more free time or just more work.  Key topics and takeaways  Teri's new podcast, The Pivot Effect. It's aimed at individuals (employees and candidates), not HR professionals. Guests share their career pivots and the skills they picked up along the way.  Growing the research. Teri is working to grow Sapient Insights' research on the HR technology market. People are keen to contribute data because they want the findings back.  2026 vs. 2025. Teri says it felt like "a lot of the same," with layoffs announcements and AI hype. The difference is that everyone now uses AI in some way, where companies once banned tools like ChatGPT.  Results are lagging. Organizations are building processes to automate more, but Teri says they aren't yet seeing the bottom-line impact. The host adds that prompting skill, choosing the right models and applications, and the AI learning how you work all make a difference.  AI is expensive.  Both speakers say tokens add up. The host describes monthly bills approaching $10,000, with one prompt costing about $13 once usage went over the plan.  The host's team bought two NVIDIA DGX Spark machines (about $5,000 each) to build its own retrieval-augmented generation (RAG) system on internal data.  Teri's team is exploring internal models and has multiple AI tools (Claude, ChatGPT, Copilot and Perplexity) compete on the same task.  Both note that memory and computing hardware prices have jumped, including Mac Minis and Mac Studios.  Predictions for 2027.  Teri expects efficiency gains to become real, and new jobs to appear that look and feel different. She doesn't believe jobs will "go and never come back."  She compares this to farming, where 75–90% of people worked in agriculture in the 1850s and only one or two percent do today.  She thinks 2027 may not bring a dramatic change, but "the wheels are turning."  Measuring ROI. Teri says nobody has figured out how to measure the return on AI in knowledge work. It's easier in industries with measurable output.  Robotics. Teri expects robotics to come back, especially for dangerous jobs, though it will be more expensive. The host notes manufacturing has used robots for decades.  Will AI give us time back? Both hoped AI would help them work smarter and improve wellness, but see it making people do more instead. They talk about the pressure of remote work and the benefit of breaks, such as a midday bike ride.  AI becoming everyday. Teri hopes we'll eventually stop calling it "AI" and it will just be part of life, like the phone. The host compares it to the arrival of the personal computer and notes that Siri, Alexa and Google Assistant have been around for about twelve years. He says consumer tools have raised expectations, so Apple, Google and Amazon are improving theirs.  Looking back next year. The host plans to revisit this year's predictions in 2027.  Resources and names mentioned  The Pivot Effect podcast (Teri's new show) : https://podcasts.apple.com/us/podcast/the-hr-huddle/id1583756892 Sapient Insights  Work Carousel: workcarousel.com/join (sponsor message)  Tools mentioned: ChatGPT, Claude, Copilot, Perplexity, NVIDIA DGX Spark, Mac Mini, Mac Studio  Companies mentioned: Apple, Google, Amazon, Tesla  Event: HR Technology, Las Vegas  Fun fact  Early in her career, Teri worked at a cemetery. She drew plot maps for the gravediggers from the deed book, which was kept in pencil at the time. She calls it one of her early pivots. 

David talks with Dr. Robyn Short about a Workplace Peace Institute study on what conflict costs US workplaces: about $3,200 per employee per year. They cover why emotions can't be left at the door, how curiosity leads to compassion, and why trust is hard when roles are unclear and AI is changing work. Robyn argues that the most valuable skills now are deeply human ones.  Key topics and takeaways  What the Workplace Peace Institute does. It is a systems design and research firm. It helps leaders design workplace systems that give people access to their basic human needs and dignity.  The cost of conflict. The study counted the hours per week each employee spends navigating conflict and applied them to the median income of the average employee. Nobody puts conflict in the budget, even though leaders and HR can be certain it's coming.  Emotions at work. Robyn says we are "feeling creatures who think," so leaving emotions at the door is biologically impossible. Crying is a natural nervous-system response to stress and needs no apology.  Curiosity before compassion. Ask "What would have to happen for me to behave this way?" When someone's behavior seems out of proportion, "act as if" they are having a hard time. That lets you see it as not being about you.  Fear as a tool. Robyn says that when people are afraid of one another, they can't build the connection and collaboration that lead to systems change.  Trust amid uncertainty. She cites research that power reduces empathy, and Gallup research that a worker's manager is the most influential person in their working life. Build a real relationship with your manager, or manage up if they don't.  AI and your job. AI will replace some jobs and radically change others. Robyn's advice is "evolve or die": take responsibility for your own upskilling, and stay close to what your work exists to produce.  Being more human. Now that machines do much human work, the people who evolve will be those who lean into deeply human skills.  Resources and names mentioned  The Matriarch Effect by Dr. Robyn Short: www.TheMatriarchEffect.com  Workplace Peace Institute  Ken Cloak, one of Robyn's teachers  Margaret Wheatley, Who Do We Choose to Be?  Gallup research on managers' influence  Tracy Sponenberg, an HR friend of David's  Taylor Swift, whom Robyn calls a matriarchical leader  Sponsor: Work Carousel (workcarousel.com/join) 

David Turetsky talks with Nikki Stone, author of Architecting Resilience, about what it takes to build teams, leaders, and organizations that can handle relentless change without falling apart. Nikki shares how her work in startup and large holding-company environments shaped her thinking on resilience, communication, and the real skills managers need to lead humans well.  Key topics  Nikki Stone explains how Architecting Resilience came from decades of experience across startup and corporate environments, including leadership roles in ad tech and large holding companies.  In this episode, Nikki shares how advanced pattern recognition, especially as a neurodivergent leader, helped her spot repeatable structures behind successful teams and scalable organizations.  David and Nikki discuss why many strong individual contributors are promoted into people management without being equipped for the role.  They explore the importance of creating separate career paths for high-performing individual contributors who do not want to manage people.  Nikki recommends mental health first aid training for managers as a practical way to better support employees without trying to act as therapist or doctor.  The conversation examines how sandwich-generation realities, such as caregiving, parenting, divorce, and aging parents, affect employee performance and leadership needs.  David and Nikki dig into neurodiversity in the workplace and why leaders need to adapt communication styles for creatives, technologists, and other distinct working styles.  Nikki shares a Venn diagram method for identifying strengths, gaps, and bridge-building experiences when planning career growth.  They discuss how learning can happen through audio, books, lectures, social feeds, and intentionally reshaping what you consume to support your goals.  The episode closes with a strong case for replacing fear-based management with purpose-driven, human-centered leadership that improves retention and organizational resilience.  Timestamps  00:00 - Welcome to the podcast and introduction to Nikki Stone  00:58 - Nikki’s current work: author, founder, podcast host, and executive leader  03:01 - The unexpected nervous habit: dancing and movement as regulation  04:11 - Music as a tool for shifting mood, focus, and resilience  06:58 - Why Nikki wrote Architecting Resilience  07:19 - Early exposure to business through her mother’s meetings  08:08 - Pattern recognition as a superpower in scaling organizations  09:20 - Why scaling inside large organizations is an art form  10:31 - The IQ, EQ, and CQ framework in ad tech and team building  13:40 - Managers need better tools to lead resilient teams  14:30 - Why not everyone should be pushed into people leadership  15:27 - Mental health first aid as a leadership tool  16:26 - Leading people through life complexity, not just output  18:55 - Why neurodivergent talent matters in modern organizations  23:53 - A Venn diagram method for finding strengths and growth gaps  25:31 - Using bridge experiences like nonprofit board service to build skills  27:32 - Learning late, learning differently, and building from audio first  29:53 - Reshaping social algorithms to support curiosity and growth  31:34 - Everyone has deficits, including managers  33:13 - Leadership training must include values, guardrails, and human context  35:09 - Fear-based employment and why paycheck-only motivation is unsustainable  36:41 - AI gives averages, but humans provide context and excellence  38:02 - Replacing return-to-office fear with purposeful gathering  39:26 - Retention, soul, and the cost of losing institutional memory  40:08 - Friction is not the enemy - it can reveal billion-dollar ideas  41:48 - Closing thoughts and a shared interest in continuing the conversation  Key frameworks  IQ, EQ, CQ - Intelligence, emotional intelligence, and contextual intelligence as the mix needed for effective leadership and team performance.  Venn diagram career mapping - A way to compare current strengths with future-role requirements and identify bridge skills.  Gather with purpose - Nikki’s approach to intentional in-person team time focused on connection, learning, and shared context.  Friction as signal - Reframing recurring friction as an opportunity to identify and solve meaningful business problems.  Notable quotes  “There is no such thing as normal.”  “You are working with humans and the humans are the actual parts.”  “Friction is not something to be feared; it's something to be embraced.” 

This episode looks at where HR technology is today and where it may be heading by 2027, with a focus on AI’s real impact on HR teams. David Turetsky is joined by Jay Polaki, CEO of HR Geckos, to unpack why so many organizations have access to AI tools but still lack the data, governance, and skills to use them well.We discuss the growing gap between AI enthusiasm and operational readiness, why HR is still unclear on its role in AI strategy, and why the conversation needs to shift from hype to use cases, trust, and measurable outcomes.  Key topics  Jay Polaki, CEO of HR Geckos, explains that HR Geckos is a people-centric co-pilot for HR operations, built by HR for HR.  The episode opens with a lighter note about Jay’s unexpected appearance on MTV during a Russell Peters event clip.  The central theme is that AI access is no longer the main problem — scaffolding is.  Jay shares findings from HR Geckos’ “AI Ready or Not” roadshow, based on conversations with about 55 HR and business leaders across multiple sessions.  Many organizations have AI tools, but data quality, governance, ownership, and funding remain unclear or incomplete.  David raises concerns about security risks, especially employees using consumer AI tools with sensitive HR and PII data.  The discussion highlights a split in AI maturity:   Some HR teams have no access and no training.  Others are forced to use AI with little or no education.  ROI is a major sticking point, with both speakers arguing that most organizations are measuring the wrong things or measuring too early.  Jay says the best way to deploy AI in HR is by starting with a specific use case, not a broad enterprise rollout.  HR service delivery and the HR service desk are identified as one of the most likely near-term AI investment areas.  The conversation repeatedly returns to trust, especially around governance, role clarity, and employee anxiety about job loss.  David and Jay agree that AI is more likely to augment workers than replace them, and that people who know how to use AI will outpace those who do not.  Jay argues that HR should stay central to reskilling, learning and development, recruiting, and re-engineering processes.  The episode ends with a strong warning against using AI for sensitive compliance work without human oversight.  Timestamps  (00:00) Opening the HR technology conversation with Jay Polaki (01:12) Jay introduces HR Geckos as a people-centric HR ops co-pilot (02:17) Jay’s unexpected MTV cameo and the Russell Peters story (04:42) Why 2026 feels chaotic for HR technology and AI (05:23) Roadshow findings from 55 HR and business leaders (06:21) AI access is widespread, but scaffolding is missing (07:47) Why data, ownership, and governance are still unresolved (09:18) Security concerns around employees using consumer AI tools (10:29) Two extremes of AI readiness in HR teams (11:26) Large organizations vs. smaller firms in AI adoption (12:23) Trust is the biggest barrier to AI deployment (13:14) Why AI desktop tools raise privacy and control concerns (14:11) Why AI was often used as a cost-cutting tool before HR was ready (15:22) Why ROI is hard to define for AI in HR (16:46) The real friction is data readiness and skills readiness (18:09) Why the best AI deployments start with a single use case (18:34) Why the HR service desk is a likely next AI investment (20:30) Start with why, then move to how (21:57) Why AI should be deployed in baby steps (22:56) Centralizing siloed HR data before scaling AI (24:21) Why leaders are unsure about HR’s role in AI strategy (26:08) Mixed views on HR’s AI future: curious, transformational, undefined (27:29) Where HR can lead: skills, learning, recruiting, and re-engineering (28:32) AI in talent management and the future of interviewing (29:30) Governance gaps, risk levels, and access controls (30:28) HR’s role in managing worker anxiety about AI (31:47) Trust and governance as urgent CEO, CHRO, and CTO issues (33:27) AI as a tool, not a replacement for people (34:04) Why the doomsday narrative is overstated (35:12) Why AI is still “pretty dumb” without human training (36:04) Augmented intelligence and human judgment in tandem (38:12) Why AI still cannot handle HR compliance on its own (39:12) Government scrutiny and accountability risks (39:50) Wrap-up and HR Tech conference frustrations for service providers  Notable quotes  “Technology should elevate people, not replace them.”  “We’ve solved the AI access issue — ownership, funding, data, governance, all of that is still in flux.”  “People who know how to use AI will replace people who don’t know how to use AI.”