AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics

Eric Cheng is co-founder and CEO of Jobright, the AI career copilot serving more than 550,000 users. After building core backend systems at Box and scaling Fangcloud to acquisition, he turned his focus to fixing what’s broken in hiring. His perspective blends engineering depth with a human-centered approach to matching talent and opportunity.In this conversation we discussed:Why Eric created Jobright after interviewing 150 young professionals and discovering a gap in personalized job search support.How Jobright reframes hiring as a “matching” problem and uses AI to function more like a career coach than a job board.The limitations of keyword-based search tools and how AI enables more nuanced, human-like job matching.Why building trust matters in AI-powered hiring platforms and how Jobright balances efficiency with authenticity and accuracy.What the “learning loop” means for job seekers and why Eric believes the mindset shift matters more than the résumé.How emerging roles like AI operations and forward deployment engineers reflect deeper changes in how organizations adopt and manage AI.Resources:Subscribe to the AI & The Future of Work NewsletterConnect with Eric Cheng on LinkedInAI fun fact articleOn How to raise over $200 million to detect audio deepfakes

Kate O’Neill is a leading voice on AI and tech humanism, known for helping organizations build more meaningful, human-centered futures. She has been featured by outlets like BBC, NPR, and NBC, and serves on the United Nations AI advisory board. A CX Hall of Fame inductee and award-winning entrepreneur, Kate brings a unique blend of optimism and realism to conversations about AI, data, and the future of work. Her latest book, What Matters Next, explores how to make human-friendly tech decisions.In this conversation we discussed:How tech humanism explains the relationship between people, technology, and business, and how leaders can design AI systems that strengthen the alignmentWhy humans project intelligence and agency onto AI tools, and what it takes to build healthy, intentional habits around emerging technologiesPractical ways workers can use AI to elevate their roles rather than fear automationThe role of leadership in creating psychologically safe environments where employees can openly experiment with AI toolsThe risk of designing systems that lead to “automated bureaucracy,” and how organizations can embed meaning into automated experiences at scaleWhy meaning and purpose remain uniquely human, and how future workplaces can evolve by pairing human judgment with increasingly capable AI systemsResources:Subscribe to the AI & The Future of Work NewsletterConnect with Kate on LinkedIn or at KO InsightsAI fun fact articleOn How Unleashing Human Potential with AI

Sid Sheth is the CEO and co-founder of d-Matrix, the AI chip company making inference efficient and scalable for datacenters. Backed by Microsoft and with $160M raised, Sid shares why rethinking infrastructure is critical to AI’s future and how a decade in semiconductors prepared him for this moment.In this conversation, we discuss:Why Sid believes AI inference is the biggest computing opportunity of our lifetime and how it will drive the next productivity boomThe real reason smaller, more efficient models are unlocking the era of inference and what that means for AI adoption at scaleWhy cost, time, and energy are the core constraints of inference, and how D-Matrix is building for performance without compromiseHow the rise of reasoning models and agentic AI shifts demand from generic tasks to abstract problem-solvingThe workforce challenge no one talks about: why talent shortages, not tech limitations, may slow down the AI revolutionHow Sid’s background in semiconductors prepared him to recognize the platform shift toward AI and take the leap into building D-MatrixResources:Subscribe to the AI & The Future of Work NewsletterConnect with Sid on LinkedInAI fun fact articleOn How Mastering Skills To Stay Relevant In the Age of AI

In this special episode of AI and the Future of Work, host Dan Turchin looks back on what 365 conversations have revealed about how AI is reshaping the way we work.What themes have emerged most consistently? Which ideas connect founders, researchers, and operators across industries? And what have these discussions taught us about the evolving relationship between humans and intelligent systems?Featuring Guests:Mark McCrindle, Founder and Principal at McCrindle  - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/13014260 Pradeep Menon, CTO at Microsoft - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/13034974 Dave Kellogg, EIR at Balderton Capital - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/16665133 Alex Buder Shapiro, Chief People Officer at Jasper AI - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/17522593 Gary F. Bengier, Writer, philosopher, and technologist - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/12934217 Josh Bersin, Founder and CEO at The Josh Bersin Company - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/17863187 Bryan Power, Head of People at Nextdoor - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/16837259 Dave Treat, Chief Technology Officer at Pearson - Listen to the full conversation: https://www.buzzsprout.com/520474/episodes/17557154 💡 What You Will LearnWhy the future of work remains human-centered How AI amplifies human capability rather than replacing itWhy trust and transparency define successful AI-driven teamsHow workplace culture is evolving as organizations adopt AIWhy meaning, empathy, and lifelong learning matter more than ever💬 Inspired by this episode?Share your favorite insight on social media and tag us (https://www.instagram.com/aifutureofwork/) And remember to subscribe for more conversations with the leaders shaping the future of AI and work.Other special episodes:Lessons from Four Unicorn CEOs Disrupting Massive Markets with AI (Special Episode)Artificial General Intelligence: Can Machines Really Think Like Us? (Special Episode)Ethical AI in Hiring: How to Stay Compliant While Building a Fairer Future of Work (HR Day Special Episode)AI and the Law: How AI Will Change Legal Careers (Special Episode)AI and Safety: How Responsible Tech Leaders Build Trustworthy Systems (National Safety Month Special)Lessons from Leaders: How AI Is Redefining Work and the Human Experience (Labor Day Special Episode)

Darrick Horton is the CEO and co-founder of TensorWave, the company making waves in AI infrastructure by building high-performance compute on AMD chips. In 2023, he and his team took the unconventional path of bypassing Nvidia, a bold bet that has since paid off with nearly $150 million raised from Magnetar, AMD Ventures, Prosperity7, and others. TensorWave is now operating a dedicated training cluster of around 8,000 AMD Instinct MI325X GPUs and has already hit a $100 million revenue run rate. Darrick is a serial entrepreneur with a track record of building infrastructure companies. Before TensorWave, he co-founded VMAccel, sold Lets Rolo to LifeKey, and co-founded the crypto mining company VaultMiner. He began his career as a mechanical engineer and plasma physicist at Lockheed Martin’s Skunk Works, where he worked on nuclear fusion energy. While he studied physics and mechanical engineering at Andrews University, he left early to pursue entrepreneurship and hasn’t looked back since.In this conversation we discussed:Why Darrick chose AMD over Nvidia to build TensorWave’s AI infrastructure, and how that decision created a competitive advantage in a GPU-constrained marketWhat makes training clusters more versatile than inference clusters, and why TensorWave focused on the former to meet broader customer needsHow Neocloud providers like TensorWave can move faster and innovate more effectively than legacy hyperscalers in deploying next-generation AI infrastructureWhy power, not GPUs, is becoming the biggest constraint in scaling AI workloads, and how data center architecture must evolve to address itWhy Darrick predicts AI architectures will continue to evolve beyond transformers, creating constant shifts in compute demandHow massive increases in model complexity are accelerating the need for green energy, tighter feedback loops, and seamless integration of compute into AI workflowsResources:Subscribe to the AI & The Future of Work NewsletterConnect with Darrick on LinkedInAI fun fact articleOn How the new definition of work