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Elevate Your AIQ

Elevate Your AIQ

By: WRKdefined Podcast Network
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Summary
 Bob Pulver is helping each of us navigate our respective journeys with artificial intelligence (AI) effectively and responsibly. Bob chats with AI and Future of Work experts, talent and transformation leaders, and practitioners who provide diverse perspectives on how AI is solving real-world challenges and driving responsible innovation.All rights reserved by WRKdefined Economics Management Management & Leadership
Episodes
  • Ep 143: Building AI Fluency and Establishing Ownership of Work Design with Phil Kirschner

    Ep 143: Building AI Fluency and Establishing Ownership of Work Design with Phil Kirschner
    Nov 6 2026
    Phil Kirschner, founder of PK Consulting, creator of The Workline newsletter, and Transformation Partner at Lead with AI, joins Bob to unpack why so many workplace and AI transformations fail to stick. Drawing on a career that runs from cybersecurity at Credit Suisse to workplace strategy at WeWork and McKinsey, Phil explains why change management can’t just be communication, and why AI is a “resistible” change that demands a clear why and a North Star. They explore why leaders must build their own AI fluency, and admit what they don’t know, before guiding others. Phil also makes the case for a Chief of Work, an independent owner of the end-to-end employee experience, and shares how AI could make teams and careers more fluid. Keywords Phil Kirschner, PK Consulting, The Workline, Lead with AI, McKinsey, WeWork, Credit Suisse, change management, AI fluency, AI readiness, North Star, resistible change, Chief of Work, employee experience, workplace strategy, manager behavior, Charter AI Pulse, Parkinson’s Law, forward-deployed black belt, work redesign, flash teams, internal mobility, psychological safety Takeaways Change sticks when leaders define what’s broken, why it matters, and where they’re headed before they start communicating and training. AI adoption is a resistible change: employees can resist it or simply go through the motions, so the groundwork matters even more. Leaders can’t transform their teams until they’ve transformed their own work, and admitting what they don’t know builds trust. Set a personal North Star for the time AI saves, or Parkinson’s Law will fill it with more low-value work. A Chief of Work, independent of HR, IT, and real estate, can read signals across the employee experience and fix friction no single function owns. Organizations need more than forward-deployed engineers; they need independent process experts who redesign the work itself. Real change requires letting go of the old way before the new one is secure, which takes psychological safety. AI could ease the coordination that makes fluid teams, short engagements, and portfolio careers so hard today. Quotes “I don’t think you can get people to transform whatever is in their little empire, which could just be them or my team or my department or my company until they have gone through it personally.” “Everybody thinks of change management is communication.” “It all comes down to individual fluency at every level is the gateway to every other level of transformation, ultimately.” “I believe we need some kind of independent body to act as a little bit of the sort of like Fitbit of the organization to just say, I hoover up all these signals.” “A forward-deployed engineer is only successful if they have something to engineer.” “The person who you know is most likely to eat your lunch is not the person you think of as your peer now. It’s someone who’s gonna do it from the ground up using the kind of operating system that we’re talking about.” Chapters 00:01 Welcome and introductions 01:02 Phil’s path from computer science to workplace strategy 06:40 Why transformations fail to stick 12:37 AI fluency, readiness, and the limits of individual productivity 14:40 Transforming yourself before your team 24:11 Setting a personal North Star for reclaimed time 26:44 The case for a Chief of Work 32:12 AI transformation leaders and the forward-deployed black belt 37:31 The trapeze metaphor and letting go of the old way 40:38 Flash teams, internal mobility, and manager incentives 42:34 Consulting models, fluid teams, and portfolio careers 51:26 Closing thoughts and where to find Phil Phil Kirschner: https://www.linkedin.com/in/philkirschner The Workline: https://walktheworkline.com/ For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠
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    52 mins
  • Ep 142: Disrupting Ourselves for the Evolution of Work with Jess Von Bank

    Ep 142: Disrupting Ourselves for the Evolution of Work with Jess Von Bank
    Oct 30 2026
    Bob sits down with Jess Von Bank, co-founder of Now to Next and author of Mother of Disruption: Reshaping the Human Contract in the Age of AI, fresh off emceeing the Skills stage at Unleash Paris and on the eve of her book launch. Jess argues that the humanization of work is not a new idea, it’s just more urgent, and that organizations should invest at least as much in workforce transformation as in AI tools. They discuss why most companies are using AI to perfect old ways of working, why skills strategies stall without clear use cases, and why only a small share of companies pursuing growth and innovation are seeing real returns. Jess also shares how raising three teenage daughters keeps her grounded, and why she wrote a book about AI that is really about what people should demand and deserve. Keywords Jess Von Bank, Now to Next, Mother of Disruption, human contract, workforce transformation, AI transformation, skills-based organization, skills passport, internal mobility, learning organization, hands heads hearts, human judgment, humans in the lead, AI ROI, augmentation vs. automation, responsible AI, AI governance, systems thinking, Unleash Paris Takeaways Invest as much or more in workforce transformation as in AI tools, and measure capacity and value created, not tool adoption. People are not an obstacle to transformation; they are the transformation. Most organizations are in a “fad diet” phase of AI: green adoption dashboards without real organizational change. Skills architecture only pays off when it serves clear use cases like mobility, redeployment, and succession. The organizations that win will be learning organizations that can move talent to work on demand. Use AI fully for routine work, as a thinking partner for complex work, and keep decisions about people firmly human. Redesign core processes from first principles; legacy steps should earn the right to be carried forward. Governance can enable experimentation through safe pilots instead of blocking it. Quotes “People are not in the way of transformation. They are the transformation.” “You should be investing more in workforce transformation than you are in AI transformation, meaning the tools and the technology.” “I think we have used AI to perfect the way we used to work.” “I like to say if it’s a no-brainer, give it to AI.” “Judgment is what you apply when the rules run out.” “I wrote a whole book about AI without ever talking about AI. I talked about what people need to demand and deserve in this time as we’re designing the future of work.” Chapters 00:02 Welcome and recovering from industry conferences 00:52 From small-town North Dakota to the future of work 03:26 Raising three teenage daughters and seeing the world through their eyes 06:46 Uncertain predictions and holding the steering wheel 09:55 Why the humanization of work is not a new conversation 16:19 Zooming out to the purpose of a business 21:13 Rethinking teams, the employment contract, and skills architecture 27:30 Skills passports, internal mobility, and learning organizations 31:51 Moving past the fad diet phase of AI 36:20 Playing the long game on AI returns 40:29 Hands, heads, and hearts: deciding where AI belongs 45:13 Earning the right to be carried forward 50:18 Governance as a hero and safe ways to start 52:30 Mother of Disruption and what people deserve Jess Von Bank: https://linkedin.com/in/jessvonbank/ Now to Next: nowtonext.ai Jess’s Substack: https://jessvonbank.substack.com Mother of Disruption: https://motherofdisruption.ai/ For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠
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    56 mins
  • Ep 141: Boosting Signals for Talent Discovery and Keeping Humans Accountable with Sharawn Tipton

    Ep 141: Boosting Signals for Talent Discovery and Keeping Humans Accountable with Sharawn Tipton
    Oct 23 2026
    Sharawn Tipton, Chief People Officer at Greenhouse, joins Bob to discuss how AI can widen access to opportunity in hiring when it’s built with fairness and accountability. Drawing on a career spanning recruiting, compensation, and diversity leadership, Sharawn explains why the resume has become a weak signal, how AI voice interviews can give more candidates a fair shot, and why every hiring decision must trace back to a human owner. They explore cognitive diversity as a driver of innovation, using AI to find and fix pay gaps, and why HR leaders now sit at the center of AI transformation. Sharawn closes with advice for HR peers and job seekers. Keywords Sharawn Tipton, Greenhouse, Chief People Officer, talent acquisition, AI interviews, voice AI, Ezra AI Labs, resume signal, candidate trust, transparency, explainability, structured hiring, responsible AI, inclusion by design, employee resource groups, cognitive diversity, pay equity, AI fluency, AI readiness, change management, learning agility, dream job Takeaways AI-polished resumes have diluted the signal, while AI interviews can bring more candidates into the conversation. Closing the candidate trust gap requires authentic experiences and clarity about where AI is used and where humans decide. Every AI-assisted decision needs a named human owner, and every outcome should be explainable. Testing tools with employee resource groups helps ensure products work for people with different accents and communication styles. Diverse perspectives in decision-making lead to better products, new markets, and stronger innovation. AI can surface pay outliers faster, but it scales existing inequities if no one applies judgment. Leaders must model AI use openly, including their missteps, for adoption to take hold. Job seekers should get clear on what they want, apply early, and keep learning while they look. Quotes “AI has allowed everyone to create an amazing resume, but what it also does is it waters down the signal that you get from that resume.” “Every decision has to have an owner. And every outcome has to be traced back to a human decision.” “Yes, AI is gonna give you the recipe, but we still need you to cook.” “We want to make sure your pay is not based on your ability to negotiate.” “If you’re a good steward of DEI, you’re a good steward of AI because you’re inherently going to know that there could be bias.” “Now you’ve got agents, right? And so it’s also who you managed and what did you build.” Chapters 00:01 Welcome and introductions 00:57 From recruiter to Chief People Officer 03:13 Responsible innovation and Greenhouse as customer zero 05:01 AI voice interviews and the weakening resume signal 07:21 Closing the candidate trust gap 10:59 Explainability, accountability, and inclusion by design 16:28 Building AI fluency and discernment across the company 20:08 Cognitive diversity and innovation 26:13 Using AI to advance pay equity 30:26 Why AI scales existing inequities 33:09 HR’s seat at the AI transformation table 37:05 Leaders modeling AI readiness 41:35 Easing AI anxiety and reinvesting freed capacity 48:28 Advice for HR leaders and job seekers Sharawn Tipton: https://www.linkedin.com/in/sharawnconnors Greenhouse: https://greenhouse.com For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠
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    50 mins
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