Elevate Your AIQ

Jonathan Aberman — venture capitalist, entrepreneur, educator, and CEO of Hupside — joins Bob Pulver to explore why AI readiness is fundamentally a human potential problem. Hupside's Original Intelligence Quotient (OIQ) provides an objective measurement of human originality relative to AI output, giving organizations a clear signal of who can thrive in an AI-augmented environment, who needs development, and how to compose teams for transformation. Jonathan and Bob dig into the dangerous feedback loop that AI can create when misused, and why originality is the true competitive differentiator. The conversation spans higher education, venture capital, workforce design, and the future of digital credentials, all through the lens of keeping humans central to value creation.

Keywords

Jonathan Aberman, Hupside, OIQ, Original Intelligence Quotient, AI readiness, human originality, talent transformation, workforce design, higher education, venture capital, AI augmentation, digital credentials, collective intelligence, responsible AI, human-AI symbiosis

Takeaways

Hupside's OIQ objectively measures human originality against AI output, helping organizations identify who to develop, elevate, or support through AI transformation

AI creates a self-reinforcing feedback loop that debilitates when misused — but as a tool, it can powerfully accelerate human creativity

Originality equals novelty plus salience; AI can generate novelty, but humans remain essential for determining what's meaningful

Higher education's real challenge isn't cheating prevention — it's teaching students to reason well with AI, then measuring output quality

Misaligning high-OIQ talent with constrained roles leaves value on the table; matching autonomy to originality profiles is a key workforce design opportunity

The greatest long-term AI risk may be whether rising capability gradually excludes people from competing as knowledge workers

OIQ and AIQ scores are dynamic and improvable — making them well-suited for portable digital credential profiles

Quotes

"AI has a couple of limitations that make it different from every tool humans ever invented — it creates a self-reinforcing loop that can cause debilitation if not used properly."

"We're the umpire in a baseball game. We're not the players — you and your listeners are the players."

"AI is not a cheating problem, it's an education problem."

"Originality is novelty plus salience. As long as humans are the ones consuming, AI will always be at best a lieutenant."

"The more we [flood] society with sameness, the more people who stand out are going to be important."

"I'm not worried about whether AI becomes sentient. I'm more worried about whether it raises the bar and starts to exclude people."

Chapters

00:02 Welcome and introductions 

02:58 The founding of Hupside and the OIQ origin story 

05:35 AI readiness as a human potential problem 

07:53 OIQ in higher education and rethinking assessment 

09:11 K-12 considerations and bias mitigation 

11:20 VC and portfolio applications of OIQ 

15:11 Embedding OIQ into the talent lifecycle 

19:56 Autonomy, role design, and workforce orchestration 

24:42 Higher education, authenticity, and the value of originality 

27:04 Innovation management and organizational barriers to AI adoption 

34:52 Short-termism, Silicon Valley monoculture, and pushing back 

39:25 Can LLMs become truly original? Shared novelty vs. human originality 

43:20 Collective intelligence and the wisdom of crowds 

48:53 Digital credentials, OIQ in talent profiles, and data ownership 

54:43 What's next for Hupside and closing thoughts

Jonathan Aberman: https://www.linkedin.com/in/jonathanaberman

Hupside: hupside.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Juan Garcia, co-founder of Tuio, a fully digital insurance company based in Spain, joins Bob to discuss how Tuio is reimagining personal lines insurance for digitally-native consumers long underserved by traditional carriers. Juan shares how Tuio evolved its AI strategy from chasing operational efficiency to making smarter decisions across marketing, underwriting, and claims. Tuio built a proprietary AI claims agent that surfaces next-best-action recommendations with confidence scores, always with a human in the loop. The conversation also explores Tuio's grassroots approach to AI literacy, responsible design, and the organizational courage required to fundamentally rethink how a company works.

Keywords 

Juan Garcia, Tuio, insurtech, digital insurance, personal lines, Spain, AI strategy, claims automation, Watson, human in the loop, AI literacy, responsible AI, subscription insurance, underwriting, organizational transformation, vertical AI, bottom-up innovation

Takeaways

Tuio identified a digitally-native consumer segment structurally unprofitable for traditional insurers and built a model around serving them through simplicity and transparency

Most AI pilots focus on the wrong 10%: cost-to-serve efficiencies. Real value lies in improving decisions across marketing and claims, which represent ~85% of an insurer's cost base

Watson processes multimodal inputs and generates next-best-action suggestions with confidence scores — routing complex ones to human reviewers

Tuio never automates negative customer decisions — not just due to EU regulation, but because human empathy is irreplaceable in those moments

By subsidizing any AI tools employees want to explore, Tuio unlocked bottom-up innovation — including a veterinarian who independently proto-built Watson's logic for pet health claims

The real barrier to enterprise AI transformation is organizational courage: reworking processes and structures around AI requires strong leadership

Quotes

"AI is something that makes you rethink the way you do your whatever you do — and that's going to be different industry per industry, even company per company."

"We switched from chasing cost-to-serve efficiencies to using AI to make better decisions — growing efficiently, underwriting smarter, and managing claims more effectively."

"We will never automate negative decisions. If you start from the standpoint that your customers are your most valuable resource, you want to give them the most humane treatment you can."

"If you don't give people these tools, you'll miss all the bottom-up ideas from the people actually in the trenches every day."

"Even if you can build it, it doesn't mean you should. Just because AI can do something doesn't mean you should deploy it there."

Chapters

00:02 Welcome and introductions 

00:44 Juan's background: from telecom engineer to insurtech co-founder 

03:31 Horizontal vs. vertical AI value — where the real opportunity lies 

06:41 Tuio's target market and the underserved digitally-native consumer 

12:54 Rethinking insurance: digital simplicity as competitive advantage 

16:03 Tuio's AI evolution: from chatbot to decision intelligence 

20:54 Watson: Tuio's AI claims agent and the shift to next-best-action 

23:24 Human in the loop: why some decisions will never be automated 

28:53 Building AI literacy through empowerment, not training mandates 

32:52 Bottom-up innovation and the veterinarian who built Watson's prototype 

40:31 AI readiness, responsible design, and knowing what not to build 

45:15 Organizational courage and why AI transformation is harder than those before it 

53:30 Closing reflections and what's next for Tuio

Juan Garcia: https://www.linkedin.com/in/juanga2/

Tuio: https://tuio.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver sits down with Russ Fradin, Founder and CEO of Larridin, to explore what it really takes for organizations to move from AI experimentation to measurable impact. They unpack the tension between AI excitement and enterprise reality, focusing on ROI, workforce readiness, responsible adoption, and the cultural shifts required to unlock productivity gains. Russ outlines why measurement and visibility are the missing pieces in most AI strategies and makes the case that high-agency professionals who embrace AI will shape the future of work. The conversation reframes AI not as a job eliminator, but as a force multiplier—if leaders build the right scaffolding to support their people.

Keywords

Russ Fradin, Larridin, AI ROI, AI readiness, AI maturity, workforce transformation, CIO strategy, CHRO strategy, CFO decision-making, productivity measurement, high-agency professionals, AI adoption, responsible AI, enterprise AI, organizational change

Takeaways

AI adoption without measurement leads to experimentation without accountability.

CIOs, CFOs, and CHROs need visibility into what tools are actually being used—and whether they drive real productivity.

The future of knowledge work is humans working with AI tools alongside agents.

High-agency professionals who embrace AI will dramatically amplify their output and career trajectory.

Organizations must move beyond individual productivity metrics toward team and enterprise-level effectiveness.

Responsible AI adoption requires training, policy scaffolding, and clarity around secure, enterprise-grade usage.

Companies that reinvest AI-driven productivity into growth will outperform those focused solely on short-term margin gains.

Quotes

“You can’t possibly understand the ROI of these tools without understanding what’s being used in your organization.”

“Having great technology is necessary, but not sufficient to drive change.”

“The future of work is humans using AI tools, working alongside agents.”

“There’s no such thing as a knowledge worker five years from today who isn’t using AI in some part of their job.”

“We’re effectively redefining what it takes to succeed in a lot of these roles—in real time.”

“The companies that don’t partner with their employees on this transformation will get left behind.”

Chapters

00:02 Welcome and Introduction

00:31 Russ’s Background and the Vision Behind Larridin

01:32 Why AI Is a Generational Technology Shift

03:34 The Measurement Gap in Enterprise AI Adoption

06:17 Workforce Anxiety and AI Upskilling

10:33 The ROI Question and Productivity Metrics

15:10 Global Talent, Competition, and AI Parallels

20:17 Responsible AI and Security Considerations

26:20 Building the Scaffolding for Adoption

30:48 Understanding What “Great” Looks Like

34:55 Who Captures the Productivity Gains?

40:22 The High-Agency Advantage in the AI Era

46:09 Why Smart Companies Invest in Their People

52:04 What’s Next for Larridin

53:09 Closing Remarks

Russ Fradin: https://www.linkedin.com/in/rfradin

Larridin: https://larridin.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver is joined by Stephen Messer, serial entrepreneur and co-founder of Collective[i] and Intelligence.com, to explore how collective intelligence, social analytics, and contextual AI are reshaping how business gets done. Stephen challenges the limitations of traditional SaaS and language models, arguing that true AI value comes from modeling real-world systems — especially how trust, relationships, and buying decisions actually unfold. The conversation dives into economic foundation models, the hidden power of relationship graphs, and why activating trusted networks may be the missing link in sales, hiring, and enterprise decision-making. Together, they unpack how removing friction and restoring context can unlock warp-speed productivity and more human-centered outcomes.

Keywords

Stephen Messer, Collective[i], Intelligence.com, collective intelligence, economic foundation model, relationship graphs, trust networks, contextual AI, sales productivity, forecasting, CRM transformation, go-to-market strategy, weak ties, network intelligence, AI agents, decision-making

Takeaways

Collective intelligence enables AI to model real-world business systems, not just generate language or automate workflows.

Context — including relationships, timing, incentives, and market conditions — is the missing ingredient in most AI-driven decision-making.

Traditional SaaS stacks create “silos of intelligence,” limiting visibility and reducing the effectiveness of AI tools layered on top.

Relationship graphs built from verified interactions unlock faster, higher-trust introductions and better business outcomes.

Trust acts as an accelerator in commerce, reducing friction and enabling decisions at “warp speed.”

Economic foundation models can forecast deal outcomes and market shifts by observing patterns across organizations.

AI should remove internal friction so humans can focus on value creation, not administrative workflows.

The future of work depends on combining contextual intelligence with trusted human networks.

Quotes

“To the man with a hammer, the world looks like a nail.”

“You’re not modeling words — you’re modeling a system.”

“If I don’t understand the context, I can’t understand the outcome.”

“Trust enables transactions at warp speed.”

“Most AI today is predicting the next best word — not the next best decision.”

“The friction to leverage your own network is far too high.”

Chapters

00:01 Introduction and Stephen’s Entrepreneurial Journey

00:40 Founding Collective[i] and the Vision Behind It

02:22 Replacing the Traditional Sales Stack with Contextual AI

05:46 Why Context Matters More Than Prompt Engineering

09:18 Systems of Record vs. Systems of Understanding

16:01 The Limits of LinkedIn and Relationship Context

23:24 Introducing Intelligence.com and Verified Networks

36:39 The Origins of Collective Intelligence and Economic Modeling

48:20 Trust Networks, Hiring, and Weak Ties

55:52 Forecast Series and the Power of Long-Form Dialogue

1:00:58 Closing Thoughts and What’s Next

Stephen Messer: https://www.linkedin.com/in/stephenmesser

Collective[i]: https://collectivei.com/

Intelligence.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob sits down with Dave Vu, Co-founder of Ribbon, to explore how AI is reshaping high-volume hiring and the candidate experience. Drawing on his background in recruiting, venture capital, and scaling AI startups, Dave shares why the hiring funnel is breaking under application volume—and how AI interviews can help close the gap. They discuss human-in-the-loop design, responsible AI, regulatory trends, bias mitigation, and why transparency and feedback are critical to building trust in the future of work.

Keywords

Dave Vu, Ribbon.ai, AI interviews, high-volume hiring, candidate experience, responsible AI, human-in-the-loop, talent acquisition, hiring automation, bias mitigation, AI regulation, recruiter efficiency, quality of hire, generative AI

Takeaways

Application volume has grown exponentially while recruiter headcount has remained relatively flat, creating a widening efficiency gap.

AI interviews can reduce screening time by 50% or more while improving consistency and fairness.

Candidate experience improves when applicants receive timely engagement, flexibility, and meaningful feedback.

Human-in-the-loop design ensures AI handles repetitive tasks while recruiters retain decision-making authority.

Transparency about AI usage builds trust and increases candidate adoption.

Regulatory clarity will accelerate enterprise adoption of AI in hiring.

Responsible AI implementation requires balancing innovation with bias mitigation and compliance guardrails.

Generative AI advancements are reshaping not only hiring, but content creation and digital trust more broadly.

Quotes

“Our long-term mission is to hire within 24 hours and make hiring faster and fairer.”

“Human-centricity doesn’t equate to anti-automation.”

“The recruiter and hiring manager are always in the driver’s seat.”

“It’s not about replacing humans—it’s about amplifying their capacity.”

“Great candidate experience comes down to respect for their time.”

“Regulations create certainty—and certainty accelerates adoption.”

Chapters

00:02 Introduction and Dave’s career journey in talent

02:55 Scaling an AI startup and identifying hiring challenges

05:02 The high-volume hiring problem and Ribbon’s mission

10:40 Designing a better candidate experience with AI

15:16 Rethinking resumes and screening inefficiencies

22:41 Human-in-the-loop and responsible AI principles

24:40 Regulation, transparency, and enterprise adoption

28:57 Candidate acceptance and AI interview adoption trends

34:28 Integration with ATS platforms and workflow evolution

43:01 Personal reflections on generative AI and digital trust

49:29 AI literacy, workforce disruption, and the future of hiring

Dave Vu: https://www.linkedin.com/in/dave-vu

Ribbon: https://ribbon.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver is joined by Tim Borys, a leader who wears many hats across executive coaching, workplace wellbeing, entrepreneurship, and podcasting. Drawing on Tim’s journey from elite athletics to advising leaders and organizations, the conversation explores sustainable human performance, burnout, adaptability, and leadership in times of constant change. Together, Bob and Tim examine why human-centric thinking is more critical than ever as AI reshapes work—and how individuals and organizations can thrive without losing sight of wellbeing, purpose, and agency.

Keywords

Tim Borys, Fresh Group, workplace wellbeing, human performance, burnout, executive coaching, leadership, adaptability, AI and work, human-centric AI, WRKdefined Podcast Network, Elevate Your AIQ

Takeaways

Sustainable performance requires focusing on human fundamentals like rest, recovery, and mindset

High-performing corporate cultures often neglect wellbeing until burnout occurs

Adaptability and learning are the most critical skills for thriving amid AI-driven change

Leadership and communication skills will be essential for managing both people and AI agents

Human performance, leadership, and business strategy must be addressed together

AI should augment—not replace—human agency and critical thinking

Quotes

“Corporate high performers seem to think the rules of human performance don’t apply to them.”

“Work sucks for a lot of people—and it doesn’t have to.”

“Every human has a human operating system, and most people never optimize it.”

“Adaptability is the number one human skill for thriving.”

“As technology becomes more powerful, the human side matters even more.”

Chapters

00:02 Welcome and introduction

00:43 Tim’s journey from elite athletics to executive coaching

02:39 Applying human performance principles to corporate work

04:32 Burnout, sleep, and sustainable performance

07:22 Human potential and wellbeing at work

09:05 The human operating system

12:06 Human-centric AI and the cost of efficiency

14:12 Adaptability, learning, and future skills

18:06 Fear, uncertainty, and career resilience

23:10 Leadership skills for managing AI agents

29:49 Performance-managing AI and responsible use

36:29 Frontline leaders vs. executive perspectives

43:52 Mindset, perception, and human agency

47:27 Personal AI tools and experimentation

51:30 The Working Well podcast and closing

Tim Borys: https://timborys.com/

Working Well podcast: https://wrkdefined.com/podcast/the-working-well-podcast

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver welcomes Lance Thompson, President of VIVI, a hospitality-focused AI company formerly known as SAVI. Lance shares his journey from luxury hospitality to tech entrepreneurship, highlighting how VIVI is bringing human-centered design to voice AI. They discuss the evolution of guest experiences, the importance of multilingual support, and how AI is being responsibly deployed to reduce friction for both guests and staff. From room service to HR to golf tee times, VIVI’s solutions demonstrate what happens when deep hospitality know-how meets cutting-edge AI.

Keywords

Lance Thompson, VIVI, SAVI, hospitality tech, voice AI, multilingual support, hotel operations, HR automation, guest experience, AI adoption, Microsoft Azure, Kinetic Solutions Group, Four Seasons, Vail Resorts, Aspen Hospitality, AI in travel, shadow AI, responsible AI, agentic search, reservations automation, guest personalization

Takeaways

Lance's career spans luxury hospitality, including Four Seasons and Vail Resorts, before shifting into tech with the founding of SAVI, now VIVI

VIVI is leveraging AI voice agents to support hotel operations, from answering phones to making reservations and handling HR inquiries

Multilingual capabilities are critical in hospitality; VIVI agents can fluently switch between languages in real time

Lance emphasizes the importance of consistency in service delivery — AI can ensure high-quality, brand-aligned experiences across time zones and locations

Unlike traditional decision-tree systems, VIVI’s tools rely on conversational AI that listens, adapts, and can be interrupted mid-sentence

Shadow AI poses risks for companies — Lance urges leaders to develop clear internal policies for responsible use and governance

VIVI's architecture is designed with data privacy and security in mind, with each client having its own isolated knowledge base

The future of hospitality AI lies in scalable, personalized tools that blend human empathy with machine precision

Quotes

“I wanted to be in a space where I could help people have a better experience in life — and hospitality gave me that.”

“If it can’t be interrupted, it’s not a conversation. And that’s what real guest service is about.”

“We don’t want to replace Janet in Reservations — we want to scale her.”

“Guests don’t want a link. They want an answer — fast, accurate, and in their language.”

“People aren’t afraid of AI. They’re asking when they can start using it to be more effective at their jobs.”

“We’re not building a static product. As the models improve, our tools do too.”

Chapters

00:00 - Intro and background from Carmel to Colorado

02:47 - Lance’s early passion for hospitality

05:09 - Discovering the limits of legacy systems

07:10 - The spark behind founding SAVI (now VIVI)

08:48 - Early demos, use cases, and multilingual potential

11:36 - Why real conversational AI matters

14:59 - Shadow AI and responsible adoption

17:54 - Building secure, client-specific AI agents

23:33 - Creating community through consistent service

26:39 - Managing real-time updates and seasonal accuracy

29:39 - Rethinking apps and improving discoverability

32:19 - The magic of humanlike conversations

36:02 - Delivering 5-star experiences through AI

39:30 - Personalizing brand voice (yes, even “absolutely”)

41:09 - Customizing user experience in real-time

43:03 - Transparency, trust, and guest empowerment

46:25 - What’s next for VIVI and hospitality AI

48:00 - Expanding into HR, golf, and reconciliation tools

51:06 - The travel planning use case

53:19 - New challenges in AI-driven SEO

53:23 - Final reflections and what’s ahead

Lance Thompson: https://www.linkedin.com/in/lance-thompson-92a5476

VIVI: http://www.vivi.bot/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

In this insightful and forward-looking conversation, Bob Pulver speaks with Adam Gordon, co-founder and CEO of Poetry, about the rise of hiring enablement and how AI can be used to create consistency, speed, and scalability in talent acquisition. Adam reflects on his entrepreneurial journey from Candidate.ID to Poetry, unpacks the MOLT framework (Marketing, Operations, Learning, Tools), and explains how Poetry integrates AI to support recruiters and hiring managers with streamlined processes and guardrails to ensure quality and compliance. They also explore deeper workforce challenges like trust, burnout, and AI’s societal impact—especially in the context of shrinking employee tenure and the future of work.

Keywords

Adam Gordon, Poetry, hiring enablement, recruiter enablement, AI agents, MOLT framework, Candidate.ID, talent acquisition, recruiter productivity, ATS integration, AI guardrails, employer brand, candidate experience, AI governance, trust in leadership, DEI, burnout, workforce automation, staffing industry, responsible AI, talent intelligence

Takeaways

Adam Gordon’s journey from recruiting to tech entrepreneurship has been shaped by the need to empower recruiters with better tools and processes.

Poetry was created as a hiring enablement workspace to reduce reliance on fragmented point solutions and to streamline recruiter workflows.

The MOLT framework (Marketing, Operations, Learning, Tools) organizes recruiter needs in a way that supports end-to-end hiring activity.

Poetry emphasizes product design simplicity and consistency, integrating AI without exposing users to the risks of hallucination or inconsistent prompts.

Recruiters using Poetry can save up to 25% of their time per day, but there's concern about how organizations reinvest those gains.

Guardrails are built into Poetry to ensure a consistent employer brand, tone, and candidate experience—especially important given drops in organizational trust.

The move from “recruiter enablement” to “hiring enablement” reflects how recruiters and hiring managers must work together in today’s TA ecosystems.

A new Poetry workspace tailored for staffing companies is set to launch in Q2 2026, signaling the platform’s evolution and market expansion.

Quotes

“Recruiting is a team sport.”

“We’ve put such strong guardrails in place, it’s not possible for Poetry to hallucinate.”

“We wanted to eliminate recruiters having to log into 30 different tools to do their job.”

“I’ve described it as an age of employment brutality—CEOs don’t want more people on payroll.”

“The trust barometer is dropping, and without trust, the candidate experience and employer brand collapse.”

“Just because you can build something doesn’t mean you’ve built a technology company.”

Chapters

00:00 - Introduction and Adam’s Background

01:17 - From Social Media Search to Candidate.ID

05:32 - The Vision Behind Poetry

07:27 - Simplicity, Product Design, and AI Agents

09:16 - MOLT: Marketing, Operations, Learning, Tools

11:16 - ATS Integration and 25% Time Savings

14:05 - The Reinvestment Dilemma

18:34 - Talent Intelligence and Bite-Sized Research

22:01 - Guardrails Over Free Prompting

24:51 - Mitigating Risk and Ensuring Consistency

29:58 - From Recruiter to Hiring Enablement

33:40 - Empowering Employer Brand and Talent Attraction

37:50 - The Importance of Trust and Communication

43:25 - Turnover, Tenure, and the Workforce Equation

49:22 - Responsible AI and Societal Impact

54:35 - Creative AI Tools and Industry Disruption

56:44 - Building a Scalable Tech Company

59:46 - 2026 Preview: Poetry for Staffing Companies

Adam Gordon: https://www.linkedin.com/in/adamwgordon/

Poetry: https://www.poetryhr.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver talks with Vijay Swami, Co-Founder and CEO of Draup, a global leader in AI-powered talent intelligence. Vijay shares his journey from early roles in call center forecasting to founding a management consultancy and then TalentNeuron, later acquired by CEB. With deep roots in data science and a vision for empowering internal analytics teams, Vijay built Draup to tackle labor market complexity using advanced AI, unstructured data, and rich taxonomies. Vijay and Bob discuss building trusted, AI-powered talent intelligence platforms that bridge data complexity and business decision-making, and how human-centric, explainable AI is reshaping strategic workforce planning. They cover the growing importance of verification skills, ethical AI practices, the future of people analytics, the architecture of trusted and explainable AI systems, and the evolving role of humans and agents in enterprise workflows.

Keywords

Vijay Swami, Draup, AI in HR, People Analytics, Strategic Workforce Planning, verification skills, ethical AI, talent intelligence, agentic AI, skills-based hiring, cloud data, explainability, trust, synthetic data, digital twins, ETTER, Curie, job displacement, augmented intelligence, transparency

Takeaways

AI's value in HR lies in sense-making from complex and unstructured data, not just simplifying workflows.

Verification skills—like content and narrative validation—are emerging as critical in a world flooded with AI-generated data.

Draup’s AI agent Curie supports HR and analytics professionals with leadership-ready narratives and scenario planning.

The platform's ETTER model goes beyond job descriptions to assess real work through contracts, SLAs, and KPIs.

Transparency and traceability are foundational to building trust in AI systems; Draup compares its models against industry benchmarks.

Ethical AI practices include open documentation, interpretability, and empowering analysts to correct or clarify information.

AI should not be viewed solely as a job killer; clear, specific skills definitions in job postings can increase hiring and help target investments.

True transformation requires shifting from jobs to workflows and task orchestration, blending human effort, AI agents, and automation.

Quotes

“We want to tell the story—not just show the data—to help people analytics become a leadership engine.”

“Verification skills are the next battery of capabilities organizations must build for a trustworthy enterprise.”

“Transparency is about giving customers the right to know—even if they don’t ask.”

“HR has the opportunity to become heroes in this AI wave by unlocking the true nature of work.”

“We should be therapists for data anxiety—helping organizations see what’s real versus what’s a myth.”

“I’m a net AI job creator guy—because there’s no shortage of work, just a need to match skills and workflows more intelligently.”

Chapters

00:05 - Introduction and Vijay’s background

00:57 - From forecasting analyst to AI-powered platforms

03:18 - Rethinking labor intelligence beyond job descriptions

05:39 - Building a sense-making engine from complex data

07:42 - Storytelling, context, and executive alignment

11:15 - The rise of verification skills

14:04 - Creating a trusted and transparent AI ecosystem

19:31 - Unlocking the true nature of work through ETTER

22:44 - Ethical AI and human-centric design

32:19 - How data becomes a therapeutic tool

35:14 - AI’s real impact on jobs and skills demand

45:25 - Strategic work planning beyond job roles

49:19 - Optimism, augmentation, and future-proofing teams

50:34 - Closing thoughts and appreciation

Vijay Swami: https://www.linkedin.com/in/vijay-swaminathan-a44101/

Draup: https://draup.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

In this milestone 100th episode, host Bob Pulver reflects on the journey of Elevate Your AIQ, sharing why he started the podcast, what he's learned from nearly 100 conversations, and what’s ahead for the show and its community. He revisits recurring themes such as AI literacy, responsible innovation, and human-centric transformation—connecting them to his personal experiences, professional background, and passion for empowering others. This solo conversation is both a look back and a call to action for individuals and organizations to embrace AI thoughtfully and elevate their AIQ together.

Keywords

AIQ, AI literacy, responsible AI, human-centric design, talent transformation, skills-based hiring, human potential, CHRO of the future, work redesign, education reform, podcasting, Substack, transformation leaders, automation strategy, AI readiness, AI ethics, trust, transparency, fairness, lifelong learning, community, AI-powered workforce

Takeaways

Podcasting is a powerful outlet for exploring curiosity, storytelling, and continuous learning—especially for neurodivergent thinkers.

Human-centric AI readiness is not just about tools or tech—it’s about mindset, adaptability, and lifelong learning.

AIQ exists on three levels: individual, team, and organizational—each requiring a blend of skills, tools, and ethical judgment.

Responsible AI is central to modern transformation—touching on transparency, fairness, ethics, and explainability.

CHROs and people leaders have dual responsibilities as strategic architects of work and catalysts for responsible innovation.

Hiring for skills and potential—rather than pedigree—is crucial to unlocking hidden talent and countering bias.

Education and talent development must evolve to equip students and workers with the durable skills of the AI-powered future.

Communities of practice and peer generosity are vital to collective learning and resilience in this era of rapid change.

Quotes

“Use AI where you should, not wherever you can.”

“We’ve always adapted to new technologies—this time is no different.”

“Human-centricity and human potential are key overarching themes of this show, and of the future of work.”

“AIQ isn’t just about literacy—it’s about readiness, judgment, and mindset.”

“If you are a DEI advocate, you are now a responsible AI advocate.”

“You can control your own destiny—you’re capable of more than you think.”

Chapters

00:00 Welcome and Gratitude for Episode 100

00:50 Human-Centric AI and the Purpose of the Show

02:32 Authenticity, Creativity, and Focus

04:35 My Background: Corporate to Independent

07:18 Early Exposure to AI at IBM and Personal Stakes

09:55 Start with Processes and Business Challenges, Not Tech

11:48 Three Levels of AIQ: Individual, Team, Org

13:45 Beyond Prompting: Augmenting Capabilities

15:20 Responsible AI: Use and Design

17:30 The Role of Trust, Transparency, and Fairness

19:50 DEI and Responsible AI Are Inseparable

21:10 Skills-Based Hiring and Hidden Potential

23:00 Designing Work for Human + AI Partnership

25:40 Lifelong Learning and the Future of Education

27:20 CHROs as Architects and Innovation Catalysts

29:30 Offense and Defense in Responsible Innovation

31:00 A Call to Action for Listeners and the Community

32:10 What’s Next: Live Shows, Events, Writing, and Community

33:20 Closing Gratitude and Future Outlook

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠