Bob sits down with Cole Napper, VP of Research, Innovation & Talent Insights at Lightcast, to unpack the complex and rapidly evolving world of people analytics. From his eclectic career across industries to his recent book release and his co-hosting role on the very popular people analytics podcast, Directionally Correct, Cole shares practical insights and hard-earned wisdom on topics like AI readiness, org network analysis, and the intersection of data, influence, and leadership. Bob and Cole explore the paradoxes of the HR tech ecosystem, the stubborn persistence of unsolved problems, and why storytelling with data is really about persuasion. Cole also gets candid about the ethical responsibilities facing those who wield data, and why the future of workforce planning demands a complete rethink of how we study work itself.

Keywords

people analytics, talent intelligence, workforce planning, organizational network analysis, Lightcast, HR tech, Gen AI, quality of hire, job analysis, data storytelling, ethical AI, talent metrics, innovation, influence and persuasion, data infrastructure, Directionally Correct podcast

Takeaways

People analytics is only valuable when it influences decisions.

Evolution of HR tech is moving from digitization to “value-first” intelligence.

Effective storytelling with data is about persuasion and influence, not charts.

Despite its maturity, organizational network analysis (ONA) remains underutilized.

Most companies are underinvesting in data infrastructure, even as they chase AI initiatives.

A flexible framework for measuring quality of hire is more useful than a rigid definition.

Job analysis is having a renaissance as AI demands a deeper understanding of work.

Ethics in people analytics isn't just about governance — it's about virtue and trust.

Quotes

“People analytics that doesn't influence decision-making is just overhead.”

“We’re still digitizing HR — we haven’t even started to optimize it.”

“Smart people assume their conclusions are self-evident, but that’s not how decisions are made.”

“We need storytelling with data, but what we really need is persuasion with data.”

“AI’s biggest challenge in HR isn’t capability — it’s data infrastructure and context.”

“There’s no one watching the watchmen — ethics starts with the person in the seat.”

“The study of work isn’t sexy, but it’s suddenly essential again.”

Chapters

00:02 - Welcome and Intro to Cole Napper

00:55 - Cole’s Career Journey

03:29 - Patterns Across Industries and the Illusion of Uniqueness

06:51 - Community, Knowledge Sharing, and Power of Consortiums

08:57 - Why Smart People Still Struggle to Influence with Data

11:33 - From HR Tech to People Analytics: Digitization vs. Value Creation

13:51 - Data vs. Self-Interest: Why Decisions Get Blocked

15:49 - Untapped Potential of Org Network Analysis

18:54 - Use Cases: Building Teams, Referrals, and AI-Enhanced Sourcing

25:17 - Cole’s Book: Why Now, and What It’s About

28:13 - Shifting from Cost Center to Profit Center in People Analytics

32:22 - People Analytics Leading AI Adoption in HR

35:31 - Probabilistic Thinking, Determinism, and Predictive Pitfalls

36:55 - Measuring Quality of Hire: Frameworks vs. Definitions

40:41 - AI Assistants, Prescriptive Insights, and Reinforcement Learning

44:26 - Data Infrastructure as the Real AI Unlock

48:25 - Strategic Work Planning in an AI-Enabled World

52:25 - Who Will Watch the Watchmen? Ethics and Virtue in Analytics

55:28 - Predictions vs. Deductions and Parting Thoughts

Cole Napper: https://www.linkedin.com/in/colenapper

Directionally Correct: https://wrkdefined.com/podcast/directionally-correct

"People Analytics": https://www.colenapper.com/book

For advisory work and marketing inquiries:

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

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

In this wide-ranging and thought-provoking conversation, Bob Pulver sits down with Steve Levy — recruiting veteran, technologist, and self-proclaimed “truth-teller” — to explore how talent, technology, and transformation intersect in today’s world of work. From the early days of expert systems and green-screen mainframes to the complexities of generative AI, Steve brings a rare blend of historical context, critical thinking, and humor. Together, they tackle topics like the ethics of candidate AI, bias in hiring platforms, skills-based hiring, the need for AI literacy, and why every recruiter needs to be more curious — and more human. Steve also shares lessons from his decades as a lifeguard at Jones Beach, and how that role shaped his instincts for protecting and empowering people — a theme that carries through everything he does in talent acquisition.

Keywords

AI in recruiting, expert systems, generative AI, candidate experience, skills-based hiring, talent ethics, AI literacy, job applications, bias in hiring, strategic workforce planning, Jones Beach lifeguard, recruiting tech, AI governance, human-centered design, talent intelligence, responsible AI

Takeaways

AI isn't new — it's just louder now: Steve recalls early experiences with AI-like systems in the 1980s and draws parallels to today’s hype and fear cycles.

Recruiters need more curiosity, less fear: Avoiding AI won’t make it go away — recruiters must engage, experiment, and understand where AI fits.

The real problem? Poor inputs: Most job descriptions and resumes are terrible — AI can’t solve for that without better human collaboration.

Bias goes both ways: If employers can use AI to screen resumes, candidates can use it to write them — the key is transparency and integrity.

Quality of hire starts with better intake: Steve emphasizes the importance of understanding real business problems, not just scanning for keywords.

Candidate AI vs Employer AI: The current debate needs to move past gut reactions and toward practical, equitable frameworks.

We need new roles and metrics: From TA ethicists to agentic governance leads, the future workforce demands new capabilities.

Recruiting is about inclusion, not gatekeeping: Steve’s philosophy centers on humanizing the process and finding reasons to say “yes.”

Quotes

“If you can't audit it, don't automate it.”

“The real challenge is working to include someone rather than exclude them.”

“We're seeing artificial stupidity — not artificial intelligence.”

“Being afraid of the ocean because of sharks is like avoiding AI because of hallucinations. You’ve got to get in the water.”

“You can fight this, or you can plan for it. That’s it.”

“Most people don't write good resumes. Most recruiters don't write good job descriptions. AI's not going to save us from that.”

Chapters

00:00 – Opening & Reconnecting with Steve Levy

03:01 – Recruiting Before Computers & the Rise of Expert Systems

08:12 – What AI Is (and Isn’t): Fear, Hype & Progress

13:17 – Strategic TA in an Agentic Era

21:07 – AI Literacy, Education & Workforce Readiness

28:11 – Candidates Using AI vs. Employers Using AI

36:45 – Problems with Job Descriptions, Resumes & Gatekeeping

45:24 – Ethics, Transparency & Legal Implications in Hiring AI

54:10 – Talent Intelligence & Strategic Workforce Planning

1:05:33 – The SiriusXM Lawsuit & Candidate Frustration

1:15:57 – Lifeguard Lessons for the AI Age

1:20:12 – Final Thoughts on What Comes Next

Steve Levy: https://www.linkedin.com/in/levyrecruits

Steve’s Blog: https://recruitinginferno.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

What’s Your AIQ?⁠ Assessment interest form

In this lively and thought-provoking episode of Elevate Your AIQ, Bob Pulver reconnects with former collaborator and pioneering technologist Marshall Kirkpatrick. From their early work intersecting social data and influence to Marshall's latest AI-driven workflows, the conversation explores how human insight and machine intelligence are converging. Marshall shares real-world examples of using synthetic personas, market monitoring systems, and creative prompting strategies to uncover early signals, amplify strategic decisions, and reimagine everything from talent acquisition to environmental policy tracking. It's a conversation that navigates the emergence of machine learning for social insights to the frontier of AI innovation.

Keywords

AI-powered market monitoring, synthetic personas, talent acquisition, influencer marketing, social analytics, Claude, Perplexity, scenario planning, digital twins, quality of hire, Obsidian, strategic planning, generative AI, Delphi method, social capital

Takeaways

Marshall’s Journey: Marshall has spent his career identifying experts and building tools to surface valuable insights from social data.

Synthetic Personas in Action: Using tools like Claude to create synthetic expert panels that evaluate documents, surface perspectives, and even challenge his own thinking.

AI-Augmented Talent Scenarios: AI to simulate team compositions, evaluate candidates’ social behaviors, and even model potential collaboration outcomes.

Monitoring the Market with AI: Building systems that detect early signals in markets — including environmental policy — using a mix of RSS, generative AI, and good old-fashioned curiosity.

Digital Twins and Ownership: Exploring who owns the knowledge embedded in a “digital twin” of an employee — and how organizations might leverage them responsibly.

Strategic Planning Reimagined: Using AI to model outcomes based on actions and strategies offers new ways to engage in scenario planning — not just in workforce contexts, but in grantmaking and innovation networks.

Counterargument Workflows: Marshall shares his custom-built browser tool that generates counterarguments to online content using ChatGPT, promoting critical thinking and cognitive diversity.

Quotes

“I try to eat my own dog food — or drink my own champagne — when it comes to market monitoring.”

“There’s gold in that data. We just have to figure out how to mine it responsibly and effectively.”

“Synthetic personas are fast, cheap, and good enough to get the conversation started.”

“What’s the strategy, what’s the output — and what’s the outcome? That’s where AI can help us model the messy middle.”

“You can’t just look at someone’s codebase or resume — you need context, behavior, and communication patterns.”

“I built a ‘counterargument bookmarklet’ to challenge the assumptions in what I’m reading online.”
Chapters

00:00 – Welcome & Reconnection: Marshall’s Background and Journey

03:12 – AI Systems for Market Monitoring and Early Signal Detection

10:58 – The Evolution of Social Analytics and Social Capital

16:39 – Talent Acquisition, AI, and the Value of Social Footprints

24:57 – Scenario Planning with Synthetic Personas

32:05 – Driving Innovation through Grant Monitoring and Project Pairing

40:41 – From Digital Twins to Ethical Implications of AI in the Workforce

50:15 – Counterargument Workflows and Critical Thinking with AI

58:21 – Closing Thoughts: Responsible AI, Community, and the Road Ahead

Marshall Kirkpatrick: https://www.linkedin.com/in/marshallkirkpatrick

Earth Catalyst: https://www.earthcatalyst.co/

For advisory work and marketing inquiries:

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

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Bob sits down with Colette Mason, a tech veteran with 40 years of experience in computing and a deep understanding of human behavior through her work in coaching and neuro-linguistic programming. Together, they explore the hype and reality around AI adoption, automation myths, and why “responsible by design” is more than just a catchphrase. Colette shares her perspectives on human-centric design, AI literacy, and how to keep authenticity intact in an AI-powered world. With warmth, humor, and real-world wisdom, this conversation brings clarity to an often-confusing landscape—and reminds us that technology should augment rather than replace what only humans can and should do.

Keywords

AI literacy, human-centric design, responsible AI, automation, digital assistants, content generation, neuro-linguistic programming, human-AI collaboration, ethical AI, digital tools, Colette Mason, trusted AI

Takeaways

AI ≠ Automation: Many tasks called "AI" are really just workflow automation. It's important to distinguish between the two.

Human-Centered Design Matters: AI tools should reflect human needs, limitations, and behaviors, especially when used in sensitive areas like hiring.

The Hype Is Real—and Misleading: Over-promising on AI capabilities can hurt trust and morale. Colette urges a more grounded, realistic view.

Use AI Where It Helps, Not Where It Hurts: Delegate the boring stuff, but don’t let AI speak in your voice without oversight.

Authenticity Still Wins: Whether it's writing, speaking, or building a personal brand, being transparent about AI involvement builds trust.

Responsible Use Is Everyone’s Job: From solo entrepreneurs to large enterprises, we all have a role in building and using trustworthy AI.

Design for Real People: Most users aren’t tech-savvy. Tools need to be intuitive, safe, and aware of different user needs—including neurodiversity.

Top Quotes

“I model people’s brains because I’m a hypnotherapist—and that’s actually a superpower in tech.”

“There’s a lot of AI that isn’t really AI. It’s just automation with lipstick.”

“The system has to read the room—it can’t just say ‘you didn’t give me all the info, mate.’”

“Regular people need AI that helps them make it to their kids’ school play—not impress YouTube bros.”

“Don’t replace yourself with AI. Do less, but make it more you.”

“We’re not in the early innings—we’re still in warmups when it comes to AI literacy.”

Chapters

00:00 – Intro and Colette's Background

02:00 – AI Hype vs. Reality: What’s Really Happening

06:00 – Automation ≠ AI: Breaking the Misconceptions

10:30 – Building Human-Centered Tools and Workflows

17:00 – Responsible AI and “Designing for Safety”

24:00 – Fairness in Hiring and Interviewing with AI

30:00 – The Quality of AI-Generated Content

38:00 – Being Transparent About AI Use

44:00 – Ethics, Reputation, and the Court of Public Opinion

50:00 – Global Perspectives on AI Regulation

54:30 – Favorite Tools and Real-World Applications

01:00:00 – The Future of Personality in AI Models

01:03:30 – Closing Thoughts

Colette Mason: https://www.linkedin.com/in/colettemason

Clever Clogs AI: https://www.cleverclogsai.com/

Ditch Rework, Build Teamwork: https://www.amazon.com/Ditch-Rework-Build-Teamwork-Principles-ebook/dp/B0FBL4C6ZP

For advisory work and marketing inquiries:

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

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Bob sits down with Dan Stradtman, Chief Marketing Officer at Bloomfire, to explore the evolving landscape of knowledge management (KM) in the age of AI. Dan brings a wealth of experience from Fortune 500 giants like Walmart, GE, and Lubrizol (Berkshire Hathaway). They discuss how often tacit and institutional knowledge is undervalued and underutilized. Bob and Dan unpack Bloomfire’s concept of “Enterprise Intelligence” and its new framework for treating knowledge as a measurable, strategic asset. They also cover the risks of overlooking tacit knowledge, how AI adoption is changing who leads knowledge initiatives, and the crucial role of ethics, trust, culture, and human-centricity in the enterprise AI journey.

Keywords

Enterprise Intelligence, Knowledge Management, Tacit Knowledge, Bloomfire, Enterprise AI, Digital Assistants, Leadership, Strategic Workforce Planning, Culture, Cognitive Diversity, Collective Intelligence, Human-Centricity, Trust, Future of Work, Ethical AI

Key Takeaways

Knowledge is an asset: Companies often fail to treat knowledge—especially tacit knowledge—as a formal asset on the balance sheet.

AI elevates knowledge management: The rise of AI has pushed KM into the C-suite, with a growing emphasis on enterprise-wide integration.

Tacit knowledge loss is costly: Orgs lose significant institutional knowledge without realizing its overall impact.

Trust drives knowledge sharing: Cultural factors, psychological safety, and leadership behavior directly impact how willing employees are to share knowledge.

Remote work challenges knowledge flow: For early-career professionals, the hybrid environment can inhibit mentorship and exposure to institutional wisdom.

Digital advisors & AI agents are rising: As digital personas and assistants become more advanced, organizations must consider the ethical implications.

SWP evolution: Strategic workforce planning should evolve into strategic work planning, balancing both digital and human contributions.

Measuring value requires new KPIs: Bloomfire’s framework ties knowledge value to tangible outcomes like revenue per employee, onboarding speed, and OKR attainment.

Cognitive diversity is crucial: Varied perspectives and experiences within teams lead to better problem-solving and innovation.

AI is integral to the future of work: It will require a blend of human and AI capabilities and should remain human-centric.

“Tacit knowledge is going out the door, and companies are underestimating how consequential that is.”

“AI systems are only as good as the quality of the knowledge you feed them. It’s still garbage in, garbage out.”

“Organizations need to think of themselves as ecosystems, where people and digital agents work together.”

“Cognitive diversity is going to be critical—otherwise everyone’s just prompting the same chatbot.”

Chapters

00:00 – Welcome and Guest Introduction

02:00 – Dan’s Career Journey and Road to Bloomfire

05:00 – What Bloomfire Does and the Rise of Enterprise Intelligence 08:30 – The Evolution of KM

12:00 – AI’s Role in Driving KM to the C-Suite

15:00 – Tacit Knowledge: The Hidden Asset

18:30 – The Value of Human-Centric Design in AI Strategy

24:00 – Skills Atrophy and the Impact of Remote Work

27:30 – Cognitive Diversity in the Age of AI

30:00 – Capturing Institutional Knowledge Through Tech

35:00 – Lessons from Early Expertise Discovery Tools

38:00 – Digital Advisors and the Risk of Redundancy

44:00 – Meeting Intelligence and Ethical Knowledge Capture

47:00 – Trust, Culture, and the Role of Leadership

55:00 – Experimentation, Risk, and AI Governance

59:00 – Innovation, Strategy, and the Future of Work

Dan Stradtman: https://www.linkedin.com/in/danstradtman

Bloomfire: https://bloomfire.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

What’s Your AIQ? Assessment interest form

Bob Pulver and Casey Fox discuss the evolution of Tekletics, a company focused on bridging the gap between untapped talent and technology careers. Casey shares his journey from a business major to the CTO of Tekletics, emphasizing the importance of work ethic, innate human skills, and the role of AI in talent acquisition and development. They explore the challenges and opportunities presented by AI in the workforce, the need for a culture of responsibility, and the importance of human potential in the age of automation and AI.

Keywords

Tekletics, AI, workforce development, talent acquisition, future of work, technology, coding bootcamp, human potential, automation, career transition

Takeaways

Tekletics aims to bridge the gap between untapped talent and technology careers.

The evolution of Tekletics reflects the changing landscape of work and technology.

Work ethic and a strong interest in technology are crucial for success in tech roles.

AI is transforming talent acquisition and development processes.

Organizations need to foster a culture of AI responsibility and ethical use.

The future of work will involve collaboration between humans and AI.

There are untapped talent pools that organizations can explore for hiring.

Training programs should focus on real projects rather than traditional boot camps.

AI tools can enhance productivity but must be used with caution.

Building a diverse and skilled workforce is essential for the future. 

Sound bites

"We need to tap into untapped human potential."

"We want to build a culture of AI responsibility."

"We have to help build the next generation of SMEs."

Chapters

00:00 Introduction to Tekletics and Casey Fox's Journey

03:23 The Evolution of Tekletics and Its Mission

08:46 Understanding the Future of Work and Career Pivots

16:02 Identifying Talent and Building Skills for the Future

20:00 Adapting to Changing Client Demands and AI Integration

25:09 Navigating the Talent Ecosystem and Future Opportunities

33:27 Navigating the Dystopian Path of AI

34:20 Fostering Curiosity in the Age of AI

36:22 The Evolution of Learning: Libraries vs. AI

38:32 Empowering Employees with AI: Trust vs. Control

40:33 The Human Element in AI Adoption

42:01 Building Trust in AI: Data Privacy Concerns

44:41 The Role of AI in Coding: A Double-Edged Sword

47:50 The Future of Junior Roles in a Tech-Driven World

51:17 Building a Foundation for Future Generations

55:28 AI Literacy: Understanding Risks and Opportunities

59:25 The Future of Work: Humans and AI Collaboration

01:02:55 Tekletics: Bridging the Gap for Future Talent

Casey Fox: https://www.linkedin.com/in/foxcase

Tekletics: https://www.tekletics.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

What’s Your AIQ? Assessment interest form

Bob Pulver sits down with Siadhal Magos, CEO and Co-founder of Metaview, to explore how AI can unlock a more structured, scalable, and insight-rich approach to hiring. Siadhal brings deep experience from the world of product and people to unpack why interviews—despite being central to business success—remain one of the most inconsistent and intuition-driven processes in organizations.

The conversation spans the origins of Metaview, the real cost of poor hiring decisions, and the gap between what hiring teams think they’re evaluating versus what they’re actually reacting to. They also discuss the difference between feedback and insight, the value of AI as an interview companion rather than a replacement, and why structured processes don’t have to come at the expense of candidate experience.

Siadhal Magos, Metaview, interview intelligence, hiring decisions, quality of hire, feedback loops, AI in recruiting, structured interviews, candidate experience, decision-making, hiring bias, interview analytics, talent strategy, hiring intelligence, decision intelligence, summarization

Hiring is high-stakes—but under-instrumented. Most teams still rely on memory, gut feel, and incomplete notes.

AI can elevate—not replace—human judgment. Metaview focuses on supporting better decisions, not automating them away.
Interview feedback ≠ insight. Capturing what was said and how it was evaluated creates a far more useful learning loop.
Consistency doesn’t mean rigidity. Structured interviews can still be candidate-friendly and personalized.

Good hiring mirrors good product thinking. Siadhal shares how tight feedback loops, data, and clarity fuel both.

Curiosity is a superpower in early-stage building. The Metaview journey is a case study in iterating with empathy.

Top Quotes

“The way most interviews are run is far too fragile for the importance of the decisions being made.”

“We’re not trying to replace human judgment—we’re trying to give it better inputs.”

“Hiring is one of the most strategic things a company does, but it’s often the least measured.”

“It’s not just about the candidate’s answers—it’s about how the interviewer responded to them.”

“Great teams are built through consistent, reflective decision-making—not just instincts.”

Chapters

00:00 – Opening and Siadhal’s early career in product and people

06:45 – Why interviews are broken and how Metaview began

13:10 – Feedback vs. insight: a new lens on interview data

20:00 – The ethics and implications of recording interviews

26:35 – Human judgment + AI: striking the right balance

33:20 – Structured interviewing and candidate experience

40:50 – Building with curiosity: lessons from Metaview’s journey

47:00 – Final thoughts on quality of hire, trust, and team growth

Siadhal Magos: https://linkedin.com/in/siadhal

Metaview: https://metaview.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

What’s Your AIQ? Assessment interest form

Bob Pulver talks with Kristi Broom, Co-founder of Rising Tide Cooperative and a seasoned transformation leader. Kristi's career has spanned EdTech, L&D, operations, and HR. She shares her journey from building early learning platforms to leading organizational change at scale—all while staying grounded in her passion for helping people grow. The conversation explores what it means to be a generalist in an era of specialization, how to design systems that support behavior change, and the role of curiosity, structure, and storytelling in navigating innovation. Whether you’re working in HR, technology, transformation, or operations, this episode offers a fresh perspective on what it really takes to lead through complexity and build a future-ready organization.

Kristi Broom, transformation, L&D, EdTech, generalist career, operational leadership, organizational change, innovation, behavior change, people development, systems thinking, storytelling in business, AI readiness, future of work

Generalists are wired for transformation. Kristi explains how her generalist background allowed her to connect across silos and take on high-stakes change.

EdTech roots shaped a systems mindset. Building early online learning systems taught her how to think structurally while staying flexible.

Curiosity drives innovation. Kristi shares how being a “possibility thinker” has helped her evolve with each new challenge.

Real transformation requires structure and story. Without storytelling, even well-designed systems fail to resonate.

Growth is personal. Her work has always centered on helping people grow—whether through development programs, leadership models, or building intentional cultures.

Pacing matters. When leading transformation, knowing when to accelerate—and when to pause—is a crucial leadership skill.

“I’ve always been a generalist—wired to think across disciplines, across people, across possibilities.”

“Structure is important, but story is the engine that helps people move.”

“I’m obsessed with seeing people grow. That’s where the energy comes from for me.”

“You can't automate your way out of transformation—you still need leadership.”

“My curiosity is a superpower, and I’ve learned how to use it to help people and organizations evolve.”

00:00 – Opening and Kristi’s origin story in education and technology

08:15 – Becoming a generalist: curiosity, complexity, and change

14:30 – Early EdTech and learning platform design

20:45 – Making growth personal: L&D as a human imperative

27:10 – Leading transformation: structure, pacing, and storytelling

36:00 – Building future-ready systems without losing your people

42:55 – Final reflections on innovation, possibility, and what’s next

Kristi Broom: https://www.linkedin.com/in/kristibroom

Rising Tide Cooperative: https://risingtidecooperative.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

What’s Your AIQ? Assessment interest form

Bob Pulver welcomes Andrew Gadomski, Founder and Managing Director of Aspen Analytics, to talk about how AI and data science are reshaping the future of HR, talent, and organizational decision-making.

Keywords

Andrew Gadomski, Aspen Analytics, workforce analytics, decision intelligence, data maturity, talent strategy, HR transformation, responsible AI, talent pipeline, future of work

Key Takeaways

The difference between using AI as a prediction tool vs. a decision-making tool—and why that matters

“Decision gravity” and how influence travels through an organization

Why most organizations aren’t “data mature” and how to assess where you really are

LLMs (like ChatGPT) aren’t ready to make decisions—they need guardrails, oversight, and smart humans

The myth of a linear talent pipeline and how hiring should actually work

Data-informed != data-driven: what smart decision-making really looks like

How to frame AI adoption around people, not just tools

Sound Bites

“Data is a tool for influence—not control.”

“If you don't trust the decision, you won't trust the data.”

“AI will tell you what it would do. It won't tell you what you should do.”

Chapters

00:00 – Welcome and Guest Intro Overview of Andrew’s role at Aspen Analytics and his approach to data-driven transformation.

05:10 – What “Data Maturity” Really Means Why most organizations overestimate their data capabilities—and what a mature approach actually involves.

12:40 – Decision Gravity and Influence Mapping How organizational decisions really get made and why influence—not hierarchy—is what drives outcomes.

21:25 – Prediction vs. Decision: The Role of AI Understanding how AI fits into human workflows, and why relying on LLMs for decisions is risky.

31:00 – The Limits of Large Language Models (LLMs) Where LLMs can be helpful, where they hallucinate, and how to set trust boundaries around their output.

40:30 – Hiring Myths and the Talent Pipeline Fallacy Why treating hiring like a “pipeline” misses the mark, and what a better model could look like.

52:15 – Building Trust Through Responsible AI How trust, transparency, and cultural readiness shape whether AI is embraced—or ignored.

63:00 – Reframing Success: Learning, Not Just Automation Closing reflections on how organizations can prioritize adaptability, curiosity, and practical value in the AI era.

72:30 – Final Takeaways and Where to Learn More Andrew’s parting thoughts on decision support, ethical data use, and leading with intentionality.

Andrew Gadomski: https://www.linkedin.com/in/andrewgadomski

Aspen Analytics: https://www.aspenanalytics.io/

For advisory work and marketing inquiries:

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

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Bob Pulver chats with Chris Maurio, Vice President of the Oracle solutions practice at Argano, about the evolution of HR technology, the role of AI in enterprise transformation, and the importance of human-centric approaches in AI governance and ethics. They discuss the need for AI literacy in education and the significance of community in fostering collaboration and learning. The conversation emphasizes the balance between technology and human interaction, the future of AI in education, and the importance of curiosity in learning AI.

Keywords

AI, HR technology, Oracle, automation, ethics, governance, education, community, human-centric, innovation, curiosity, creativity

Takeaways

Chris Maurio has a background in HR and technology implementation.

The HR tech space has evolved significantly over the past 20 years.

Oracle is a leader in enterprise transformation and innovation.

AI can enhance HR processes but requires careful governance.

Human-centric design is crucial in AI applications.

AI literacy should be part of onboarding and compliance training.

Community plays a vital role in AI learning and collaboration.

Education about AI should start early in schools.

Curiosity drives innovation and effective use of AI.

The future of work will involve a blend of human and machine capabilities.

Sound bites

"The innovation is incredible."

"Community is huge in this regard."

"Curiosity is key to learning AI."

Chapters

00:00 Introduction and Background

02:10 The Evolution of HR Technology

04:56 Oracle's Role in Enterprise Transformation

09:08 AI Integration in HR Systems

12:18 Governance and Compliance in AI

15:23 Human-Centric AI Design

19:19 AI Literacy and Training

22:19 Hands-On Learning with AI

27:28 The Future of AI Education

30:06 Closing Thoughts on AI and Education

30:45 Teaching Critical Thinking in the Age of AI

33:11 Integrating AI into Education

35:28 Balancing Screen Time and Learning

39:28 Fostering Curiosity and Critical Thinking

44:10 Navigating Trust and Ethics in AI

49:38 The Role of AI in Everyday Life

52:50 AI Literacy in Organizations

56:21 Community and Ethical AI Development

Chris Maurio: https://www.linkedin.com/in/chrismaurio

Argano: https://argano.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

What’s Your AIQ? Assessment interest form

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy.