Elevate Your AIQ

Noelle London, founder and CEO of Illoominus, returns to Elevate Your AIQ just over a year after her first appearance to chat with Bob about what has changed and what Illoominus has built in response. The conversation covers how decision cycles inside organizations are compressing, why AI adoption has accelerated but also created new governance risks, and how the gap between individual experimentation and enterprise-ready deployment has become the defining challenge for people leaders today. Noelle details the launch of Illoominus Agentic Workforce Intelligence, a capability already in production with customers that delivers proactive, AI-generated insights directly into executive workflows rather than waiting for someone to go find them in a dashboard. The discussion closes on the importance of governed, secure AI environments as organizations move from pilots to scale, and why data alignment across HR, finance, and operations remains the foundation everything else depends on. Keywords Noelle London, Illoominus, workforce intelligence, agentic AI, people analytics, HR data, workforce planning, talent acquisition, data governance, AI adoption, decision support, workforce transformation, future of work, data literacy, AI readiness, responsible AI, executive reporting Takeaways Decision cycles across HR, finance, and operations are compressing rapidly, making real-time workforce data no longer a nice-to-have but a business requirement The gap between AI experimentation at the individual level and governed, enterprise-ready deployment is where most organizations are getting stuck right now Illoominus Agentic Workforce Intelligence delivers proactive, contextualized insights directly into executive inboxes, shifting the model from reactive dashboarding to continuous intelligence Data alignment across functions, getting HR, finance, and ops working from a single trusted source, is the prerequisite for any meaningful workforce analytics initiative Governed, secure AI environments are essential as agentic tools scale, particularly around access levels, data privacy, and agent-to-agent communication Consultants are increasingly embedding Illoominus as the analytical backbone of engagements, shifting their own value toward change management and strategy Quotes "The puzzle pieces weren't talking, and so that's first and foremost, it doesn't really help to have something very interesting if it's not connected together." "Every single week, every single person on their executive leadership team are getting AI-driven insights into their inboxes to help them understand what's going on." "You're not getting graphics, you're getting the full understanding on are we good, or is this something that we need to pay attention to." "HR doesn't have a different version of headcount than finance does. Those are very real examples of where we've seen some of these data initiatives stall." "How do you make sure if you're using AI within the organization, it's governed properly so that you're not using these tools as a pass through for people that shouldn't have access to information." "It's the end of everything as we've known it, and change management with the amount of technology that companies are adopting, that's a really interesting place for consultants to play." Chapters 00:02 Welcome and guest introduction 00:46 Illoominus origin story and the data connectivity problem 04:25 How Illoominus complements rather than competes with consultants 08:07 A year of change: compressed cycles, AI adoption, and new organizational pressures 15:12 Expanding self-serve insights across the leadership team 21:29 Launching Illoominus Agentic Workforce Intelligence 26:17 Accelerating business cases through data alignment across HR and finance 30:22 The full data picture: talent acquisition, skills, engagement, and beyond 36:51 Industry fit and the profile of an Illoominus customer 39:28 How executives interact with agentic insights 43:52 AI readiness, governance, and moving from experimentation to scale 49:52 Closing reflections and what comes next Noelle London: https://www.linkedin.com/in/noellelondon Illoominus: illoominus.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 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 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

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

Bob Pulver sits down with Ross Dawson, world-renowned futurist, serial entrepreneur, and creator of the Humans + AI community. With decades of foresight expertise, Ross shares his evolving vision of human-AI collaboration — from systems-level transformation to individual cognitive augmentation. The conversation explores why organizations must reframe their approach to talent, capability, and value creation in the age of AI, and how human agency, trust, and fluid talent models will define the future of work. Keywords Ross Dawson, Humans + AI, AI roadmap, ThoughtWeaver, AI teaming, digital twins, augmented thinking, talent marketplaces, future of work, systems thinking, AI in organizations, AI in education, trust in AI, AI-enabled teams, cognitive diversity, latent talent, fluid talent, organizational design Takeaways The “Humans + AI” framework centers on complementarity, not substitution — AI should augment and elevate human potential. AI maturity is not just technical — it requires cultural readiness, mindset shifts, and systems-level thinking. Trust in AI must be calibrated; both over-trusting and under-trusting limit value creation. AI-enabled teams will rely on clear role design, thoughtful delegation of decision rights, and frameworks for collaborative intelligence. Digital twins and AI agents offer different organizational advantages — one mimics individuals, the other scales domain expertise. Organizations must reimagine work as networks of capabilities, not boxes of job descriptions. Talent marketplaces are an early expression of fluid workforce models but require intentional design and leadership buy-in. The most human-centric organizations will be best positioned to attract talent and thrive in the AI era. Quotes “AI should always be a complement to humans — not a substitute.” “We live in a humans + AI world already. The question is how we shape it.” “Mindset really frames how much value we can get from AI — individually and societally.” “You know more than you can tell. That gap between tacit knowledge and what AI can access is where humans still shine.” “Start with a vision — not a headcount reduction. Ask what kind of organization you want to become.” “We can use AI not just to apply existing capabilities but to uncover and expand them.” Chapters 00:00 - Welcome and Ross Dawson’s introduction 01:10 - From futurism to Humans + AI: key focus areas 03:30 - How AI is shifting public curiosity and mindset 06:00 - Systems-level thinking and responsible AI use 08:20 - AI in education and enterprise transformation 11:10 - The rise of AI-augmented thinking 14:00 - Calibrating trust in AI and human roles in teams 17:00 - Designing humans + AI teaming frameworks 20:30 - Delegation models and decision architecture 23:20 - Digital twins vs synthetic AI agents 26:00 - The value of tacit knowledge and cognitive diversity 30:00 - Empowering individuals amidst career uncertainty 32:10 - Breaking out of job “boxes” with fluid talent models 35:00 - Talent marketplaces and barriers to adoption 38:00 - Human-centric leadership in AI-powered transformation 41:00 - Strategic roadmaps and vision-led change 45:30 - Ross’s personal AI tools and experiments 52:00 - Final thoughts on AI’s role in augmenting human creativity Ross Dawson: https://www.linkedin.com/in/futuristkeynotespeaker Humans + AI: https://humansplus.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