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

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Cesar Carvalho is the co-founder and CEO of Wellhub, the corporate well-being platform connecting millions of employees to top-tier fitness, mindfulness, therapy, nutrition, and sleep partners across 18 countries. 

Since founding the company as Gympass in 2012, Cesar has raised nearly $900 million in venture funding, reached a $2.4 billion valuation, and grown Wellhub to serve over 50,000 corporate clients worldwide. 

In this episode, Cesar sits down with Dan to discuss why treating employee wellness and business performance as opposing forces is a false dichotomy. Tune in to hear his perspective on why AI should be leveraged to fund employee reskilling rather than justify job cuts, how Wellhub's AI wellness coach scales hyper-personalized care to millions of subscribers, why less than 10% of global healthcare spending goes toward prevention, and how pivoting during the 2020 pandemic transformed a near-death crisis into a multi-product wellness ecosystem.

In this conversation, we discuss:
Why framing corporate wellness as an adversary to business performance is a false dichotomy, and how employee health directly drives bottom-line execution.
How granting employees 30 minutes of paid work time daily to experiment with AI tools fosters a culture of innovation and continuous reskilling.
What the structural imbalance between preventive "well care" and reactive "sick care" reveals about the urgent need to redesign enterprise benefits.
How an AI-powered wellness coach expands personalized fitness and mindfulness guidance from hundreds of thousands to millions of corporate subscribers.
Why strict data minimization policies and phased beta testing provide a trusted framework for deploying AI in sensitive health environments.
What pivoting a global business model during the 2020 pandemic teaches founders about mission alignment, resilience, and turning near-death moments into catalysts for growth.

Explore the conversation:
00:00 Show Intro and Newsletter Shoutouts
02:07 AI Fun Fact: Chatbots and Mental Health Risks
04:01 Introducing Cesar Carvalho, CEO of Wellhub
05:03 From Harvard Dropout to Corporate Wellness: The Founding of Gympass
06:56 The "Team Human" Ethos: Making Well-Being Ubiquitous at Scale
09:14 Performance vs. Health: Why Employee Well-Being Directly Drives Execution
12:37 Calling Out AI Layoffs: Are Employees Expendable?
14:12 Reskilling Over Layoffs: Why Wellhub Invests in Existing Talent
16:34 Personalization at Scale: Expanding the AI Wellness Coach Across Millions
20:19 Responsible AI at Wellhub: Data Minimization and Governance Standards
22:36 Sick Care vs. Well Care: Quantifying a 20-35% Drop in Healthcare Costs
26:36 Eliminating Friction: Redesigning Employee Benefits Outside Open Enrollment
32:02 Human-First Design and Why AI Will Disrupt Legacy Companies
33:23 The Pandemic Pivot: Turning a Near-Death Event into Wellhub's Evolution
37:27 Advice to His Younger Self and the Best Time to Start a Company
39:45 Closing Thoughts and Sign-Off

Resources:
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Connect with Cesar on LinkedIn
AI Fun Fact
On how one good decision made Thomas Otter (venture capitalist at Acadian Ventures) an accidental HR tech pioneer
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See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant

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Todd Barr is the CEO of Axonis and has spent his career in high growth software infrastructure, living through the shift from Unix to Linux, the rise of DevOps, and the blockchain era before landing in AI. Axonis was built by technical founders with 25 years each in large scale infrastructure across government, defense and intelligence, where sharing the underlying data was never an option. 
Recorded live from the floor of Ai4 2026, this lightning round explores why you do not have to centralize your data to start doing AI, and what it takes to make a decision you can defend later.
Todd and host Dan Turchin dig into what an auditable decision actually records, how governance can live at the data node instead of the application layer, the distance between collecting sensor data and acting on it, and why Todd believes decisions themselves are about to become a category of data.
What You'll Learn
Why centralizing your data is not a prerequisite for AI, and how a federated architecture holds up when nodes go offline and come back
What an auditable decision captures: the data used, the model and its version, the reasoning, and the person who attested to it
How attribute based access control decides what each operator or agent is allowed to see, enforced at the data itself
The sensor to decision gap, and how a flood management team went from raw readings they could not interpret to acting on them in real time
Why collecting data and acting on it are two different problems, and what opens up once that distance closes
What becomes possible once decisions are stored as data, from the cost of each decision to who in the organization decides better
🎙️ Part of our Ai4 2026 compilation series. Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19816277  

Resources
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Connect with Todd on LinkedIn

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Daniel Chait is the co-founder and CEO of Greenhouse, the industry-leading hiring software platform designed to help enterprise organizations build fair, structured, and effective recruiting processes. He has been a technology entrepreneur in New York for more than 20 years.

He started Greenhouse about 15 years ago on a simple conviction: companies that follow structured hiring practices get better results, and job seekers deserve a process that is fair and transparent. Today he is leading the company through a reinvention for the AI era, including the acquisition of Ezra AI Labs to bring transparent, conversational AI tools to job seekers and hiring teams alike. 

In this episode, Daniel draws on two decades of building companies where every hire lands directly on the bottom line to ask what candidates and employers both need answered: can AI make hiring more human when it is already making it feel less so?
In this conversation, we discuss:
Why candidates and employers using AI at the same time is creating a doom loop that shuts real humans out.
Why AI-led interviews worry so many job seekers, and what it takes for a conversation with an AI to feel fair.
Why using AI to automatically reject most applicants is tempting, and why Greenhouse said no to itWhy AI-polished resumes are making every candidate look the same, and how hiring can move beyond the resume.
How AI can replicate human bias at light speed, and why Daniel says no vendor should ask you to take their word for it.
What Daniel tells anxious workers, from new grads to senior leaders, about disruption, opportunity, and reinventing a career with AI.

Explore the Conversation
0:00 Welcome Back and This Week's AI Fun Fact
4:48 Meet Daniel Chait, Co-Founder and CEO of Greenhouse
7:55 From a Soulless Consulting Job to Founding a Company
10:43 Reinventing the Applicant Tracking System
15:23 How AI Has Already Reshaped Hiring and Job Seeking
21:11 What the Candid AI Interview Report Reveals About Trust
24:25 Why Auto-Rejecting Candidates With AI Backfires
26:08 Sorting Through the Flood of AI-Generated Applications
30:46 Confronting Bias in AI-Powered Hiring Tools
36:46 Reframing AI Anxiety Into Opportunity
40:11 Time Capsule: Advice to His Younger Self
42:14 Where to Find Greenhouse and Closing Thoughts

Resources
Subscribe to the AI & The Future of Work Newsletter
Connect with Daniel on LinkedIn
AI fun fact article
On How Paolo Ardoino, CEO of Tether, is exploring whether decentralized AI can fix banking, crypto, and the future of finance

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Andrew Rabinovich is the former CTO of Upwork and has spent 25 years in machine learning and computer vision, long before AI was fashionable. After a PhD in computer vision at UCSD, he worked at Google. He then spent five years at Magic Leap building mixed reality devices before founding Headroom, a video conferencing company that Upwork acquired. 
Recorded live from the floor of Ai4 2026 in August, this lightning round explores what happens when you actually measure how much of a real job an AI agent can finish.
Andrew and host Dan Turchin dig into Upwork's shift from a matching marketplace to a work delivery platform, the meta agent that breaks a job into atomic units of work, how the platform proves a freelancer is human, and more. 
What You'll Learn
How Upwork is evolving from a matchmaking marketplace into a work operating system, and how its meta agent decomposes a single job into atomic units of work
What Upwork's AI productivity index revealed when agents were tested against real jobs already completed by human freelancers
Why every agent on the platform is paired with a human expert, and how that pairing changes both the speed and the quality of the result
How proof of humanness works in practice, from identity verification to AI video interviews, and what happens when the system gets it wrong
Why agents may soon become the demand side of the marketplace, calling human experts in real time to verify what they cannot

🎙️ Part of our Ai4 2026 compilation series. 
Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19816277 

Resources
Subscribe to the AI & The Future of Work Newsletter
Connect with Andrew on LinkedIn

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Mahe Bayireddi is the CEO and co-founder of Phenom, the global HR technology platform he launched in 2011 with the mission to help a billion people find the right job. 
Under his leadership, Phenom has raised over $160 million, achieved unicorn status, and consistently ranked among the Inc. 5000 fastest-growing private companies. A serial entrepreneur with a deep technical foundation, Mahe previously co-founded SnipSnap and Bijol Health. He holds BE and MS degrees in computer science.
In this episode, Mahe sits down with Dan Turchin to unpack why "AI is taking your job" is the wrong framing, and why the real question is where you sit, what you do, and how deeply you understand the business around you.
In this conversation, we discuss:
Why replacing jobs and replacing the job you'll have tomorrow are two very different things, and why irreplaceability comes down to understanding the business, not just being intelligent.
Why raw machine intelligence falls short in enterprise HR, and why true workforce alignment requires AI systems built on deep business understanding.
How culture, structure, and strategy form a company's "organizational DNA," and why most companies fail at execution, not strategy.
How a five-dimensional rubric of talent zones, industries, roles, locations, and culture creates hyperpersonalized workflows instead of one-size-fits-all automation.
Why frontline workers and specialized knowledge practitioners experience AI as an amplifier of capability rather than a displacement force.
What enduring over 100 venture capital rejections teaches founders about developing "cockroach" resilience and leading through persistent industry skepticism.

Explore the Conversation
00:00 Intro & AI Fun Fact
04:27 Meet Mahe Bayireddi, Phenom CEO
06:36 AI Is Your Ally, Not Enemy
09:29 What Hiring Got Wrong
10:43 Culture as Organizational DNA
12:26 Why Agent Interviews Won't Scale
16:47 Bias and AI Responsibility
19:00 Fraud Agents by Region
24:23 Frontline vs. Desk-Based AI
28:53 A Billion People, Right Jobs
31:24 Lessons From the Founder Journey
33:01 100 Rejections, One Cockroach
35:39 Where to Find Mahe and Phenom

Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Mahe on LinkedIn
AI fun fact article
On using AI to make hiring more fair and eliminate human bias