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

By Dan TurchinBusiness Entrepreneurship Technology Management

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

October 26411: Jeremy Burton, GM of Observability at Snowflake: The Data Layer Was Never a Commodity. It’s the Whole Game
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Jeremy Burton is the General Manager for Observability Business Unit at Snowflake following the acquisition of Observe, the developer-centric observability platform where he served as CEO. A veteran enterprise technology executive with a thirty-year career spanning Silicon Valley, Jeremy previously served as Executive Vice President of Marketing and Corporate Development at Dell, President of Products at EMC, and CEO of Serena Software, with earlier leadership roles at Symantec, Veritas, and Oracle. He has served on Snowflake’s board of directors since 2015 and sits on the McLaren Racing Advisory Board.
In this episode, Jeremy draws on watching customers go from collecting a petabyte of data in a decade to generating one every two days to make the case that without a real data foundation, enterprises will either get the wrong answer from their AI, or burn a fortune getting to the right one.

In this conversation, we discuss:
Why pointing AI agents at hundreds of terabytes of telemetry burns tokens fast, and what Jeremy says has to change first.
How an AI agent facing 10 sources of truth can deliver the wrong answer with total confidence.
Why Jeremy calls the LLM “a new animal in the zoo,” and what that means for anyone trying to monitor AI agents.
How AI agents are starting to build the knowledge graphs that once took human implementation teams to create.
Why evals are becoming essential to running an LLM, and what a single model release can do to existing applications.
What Jeremy would tell his younger self stepping off the plane to meet Mark Benioff, and the career superpower he undervalued.

Explore the conversation:
00:00 Intro and AI Fun Fact: Pope Leo XIV's Encyclical and Anthropic's Vatican Address
04:08 Introducing Jeremy Burton, GM for Observability at Snowflake and Former CEO of Observe
07:09 The Observe Origin: Pitching Observability as a Unified Data Problem Natively on Snowflake
10:20 Observability as a Data Problem: Metrics, Logs and Traces
13:39 Snowflake Culture and Leadership Eras
16:58 Joining Snowflake: Running Observe After the Acquisition
18:57 Data Foundation vs. Frontier Models: Balancing CPU and GPU Burn with Context
22:23 Snowflake's AI Strategy: Data Foundation and Sources of Truth
28:11 Non-Human AI Telemetry: Using Knowledge Graphs to Structure Machine Data
32:31 Probabilistic AI and LLM Observability: Why Evals and Harnesses Are Essential
36:14 Future of Work: The "LLM as Modern-Day Tractor" and Software Engineering Practices
41:18 Career Superpowers: The Value of Networks and Relationships in Silicon Valley
43:06 Closing: Where to Connect with Jeremy Burton and Explore Snowflake Observability

Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Jeremy Burton on LinkedIn
AI fun fact article
On How Ashu Garg, General Partner at Foundation Capital, finds and invests in the future of AI
Other episodes mentioned on the show: Automate the Work, Amplify the Humanity, with Snowflake's CPO Arnnon Geshuri
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Learn how Box connects secure enterprise content with AI to power smarter workflows. Visit box.com/ai to learn more.
45 min
October 19410: Johanna Jackman, Chief People Officer at Freshworks: Responsible AI Isn’t Slow. It’s Bold, With Human Judgment
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Johanna "JJ" Jackman is the Chief People Officer at Freshworks, the global cloud-based customer service and IT service management platform serving over 75,000 corporate clients worldwide. With an international career across six countries, JJ began her professional journey in the Australian mining industry before transitioning into high-growth technology.
Prior to joining Freshworks in 2023, she served as Chief People Officer at Airtable, Chief Human Resources Officer at Pure Storage, and Vice President of HR at LinkedIn during its formative scaling era, and currently sits on the Board of Directors at Grafana Labs.
In this episode, JJ sits down with Dan to discuss why modern employee experience requires transitioning from traditional organizational charts to workflow-centric platforms, how HR functions as Customer Zero to eliminate operational friction across enterprise IT and HR services, why executive leaders must share responsibility with employees for continuous AI fluency, and how the convergence of human judgment with digital teammates is redefining workforce planning and career mobility.

In this conversation, we discuss:
Why evaluating enterprise software transformation requires abandoning rigid organizational charts in favor of end-to-end, workflow-centric employee experiences.
How serving as "Customer Zero" allows internal people teams to co-design IT and HR service platforms that eliminate administrative friction for global workforces.
What the creation of dedicated AI enablement roles reveals about shifting corporate strategy from traditional headcount planning to dynamic capability modeling.
Why fostering organizational resilience requires a mutual commitment between employers and workers to maintain continuous AI fluency and career relevance.
How enterprise leaders can establish transparent guardrails to ensure autonomous algorithms inform decision-making without supplanting human judgment.
What a data-driven, structured job search framework teaches early-career professionals about asserting personal agency in an algorithmically filtered hiring market.

Explore The Conversation
00:00 Intro and listener mailbag: Allison in Trenton on special episode 21 and WEF global job trends
02:35 Introducing Johanna "JJ" Jackman, Chief People Officer at Freshworks
04:09 From mining underground to tech executive: Formative lessons in human-centric leadership
06:22 The Freshworks culture trifecta: Manager support, peer collaboration, and goal clarity
08:47 From org charts to workflows: Framing "People Platform as a Service" with IT leadership
12:08 HR as customer zero: Streamlining Lives HR and eliminating friction across the employee journey
15:32 Rewriting the employment contract: Executive role-modeling and shared AI fluency
21:45 Capacity over headcount: "AI in Motion" days and hiring an AI enablement leader
29:48 Responsible AI in HR: Safeguarding human judgment in promotion and performance decisions
33:34 Empowering early-career professionals: Agency, unlearning, and Josh's mathematical job hunt
41:52 The 2031 vision: Digital employee IDs, merging CPO-CIO roles, and remote leadership
45:01 Closing: Where to connect with Johanna "JJ" Jackman and explore Freshworks

Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Johanna "JJ" Jackman on LinkedIn
Other episodes and research mentioned on the show:
Special Episode 21 featuring Charlene Li, Daphne Jones, Patty Hatter, Mona Sabet, and Tess Posner on female leadership in AI
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See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant
47 min
October 12409: Ryan Gavin, CMO at Slack: AI Is Single-Player. Slack Is Betting on Multiplayer
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Ryan Gavin is Chief Marketing Officer at Slack, the global collaboration platform used by more than 200,000 organizations across 150 countries. Since joining Slack, Ryan has helped drive a 250% increase in revenue while championing the launch of Slack's AI-first capabilities and agentic integrations.

A seasoned technology executive, Ryan previously served as Chief Growth Officer at Convoy and held senior leadership roles at Amazon Web Services and Microsoft, where he managed multi-billion-dollar business units.
In this episode, Ryan draws on watching hundreds of enterprise AI rollouts up close to make the case that dropping agents into an organization without a strategy doesn't just fail to help, it actively backfires.

In this conversation, we discuss:
Why single-player AI tools fail to deliver enterprise productivity gains, and how deploying autonomous agents into collaborative, multiplayer environments unlocks hidden software value.
How a conversational interface connects unstructured team dialogue with structured CRM data, allowing employees to query enterprise systems without opening underlying software tabs.
What the concept of "headless software" reveals about democratizing access to sales and operational insights across non-technical departments.
Why transparent, step-by-step reasoning and strict permission inheritance are essential for building trust when introducing AI tools into enterprise workflows.
How leading organizations elevate Slack from a conventional IT collaboration expense into a core strategic driver for company-wide AI adoption.
What executive advice for emerging professionals highlights the enduring value of curiosity, creativity, and adaptability in a rapidly changing job market.

Explore the conversation
00:00 Show Intro, a Team Human Success Story, and Meet Ryan Gavin
03:44 Ryan Gavin's Path to Becoming CMO of Slack
04:57 Slack's New Job in the Age of AI Agents
07:53 Designing SlackBot to Strengthen Human Collaboration
12:31 Headless Salesforce and Slack as the New Front Door
16:50 Slack as 2% of Your AI Budget and the Problem With 'Work About Work'
21:37 Trust, Transparency, and the AI Black Box in SlackBot
25:28 From Slash Commands to Every Employee as a Builder
31:40 Winning Share of Wallet in a Zero-Sum AI Budget
35:54 Advice for Workers Who Feel Left Behind by AI
39:35 Where to Find Ryan Gavin and Slack

Resources
Subscribe to the AI & The Future of Work Newsletter
Connect with Ryan on LinkedIn
Other episodes mentioned on the show:
On How Silvio Savarese, EVP and Chief Scientist at Salesforce, navigated the real challenges of taking AI from the ivory tower to corporate labs (Episode 297)
On How Kai Nunez, Vice President of Research & Insights at Salesforce, shares the secret to making tech teams own responsibility for AI ethics (Season 2, Episode 47)
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See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant
42 min
October 08SE 31: Kartik Sakthivel, CIO at John Hancock | Live from Ai4 2026
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Kartik Sakthivel is the Chief Information Officer at John Hancock, the life insurer that turned 164 years old in April 2026 and is part of Manulife. Before joining, he spent eight and a half years at LIMRA and LOMA, the oldest and largest trade association in financial services, which gave him a view across carriers few technology leaders ever get.
Recorded live from the floor of Ai4 2026, this lightning round explores what it takes to bring AI into a company founded during the Civil War, and why he tells his teams that what they build today becomes the legacy for the next 164 years.
Kartik and host Dan Turchin dig into why he believes every technology leader should think of themselves as a business leader first, how a regulated industry decides what to fast track and what to slow down, and what he says to people who are watching a machine learn to do the thing that made them valuable.
What You'll Learn
Why uptime and mean time to repair are table stakes for a modern technology organization, and what Kartik measures instead
How a highly regulated business draws the line between internal AI that gets fast tracked and anything customer facing that does not
Why there are more AI pilots in insurance than planes at a major airport at peak hour, and how to find use cases that are neither too small to matter nor too large to finish
The question he asks every time the business brings him an AI idea, and why the answer is sometimes something far simpler
What he tells colleagues watching automation absorb part of their role, and where the time that comes back should be reinvested

🎙️ 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 Kartik on LinkedIn
36 min
October 05408: Cesar Carvalho, CEO of Wellhub: The Risk Isn't AI. It's How Fast You Grow.
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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:
Subscribe to the AI & The Future of Work Newsletter
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
41 min
October 01SE 30: Todd Barr, CEO at Axonis | Live from Ai4 2026
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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
Subscribe to the AI & The Future of Work Newsletter
Connect with Todd on LinkedIn
22 min
September 28407: Daniel Chait, CEO at Greenhouse: Inside the Doom Loop Where AI Screens AI-Written Resumes
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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
44 min
September 24SE 29: Andrew Rabinovich, former Upwork CTO | Live from Ai4 2026
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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
27 min
September 21406: Mahe Bayireddi, CEO of Phenom: AI May Be Replacing Your Job Right Now, But Not the One You'll Have Next
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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
38 min
September 17SE 28: They Might Be Agentic, But We Have Agency: Leaders from Upwork, Axonis, and John Hancock on Where the Human Belongs | Live from Ai4 2026
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Walk the floor at an event like Ai4 and most of the conversation is about what machines can now do on their own. The question that kept surfacing in our conversations was quieter, and harder: where do humans belong when machines can think?
In this special compilation episode of AI and the Future of Work, we bring you three conversations recorded live at Ai4 2026 in Las Vegas. This is the first episode of our four-part Ai4 series.
A talent marketplace, a data infrastructure company, and a 164 year old life insurer. Three businesses that could not be more different, and three leaders who arrived at the same answer from opposite directions.
What connects them is not caution about automation. All three are automating serious amounts of work. What they share is that the requirement was built in on purpose, because the outcome depends on someone being answerable for it.

Featured Guests
Andrew Rabinovich, former Upwork Chief Technology Officer. Full conversation: https://www.buzzsprout.com/520474/episodes/19855791
Todd Barr, CEO at Axonis. Full conversation: https://www.buzzsprout.com/520474/episodes/19890804
Kartik Sakthivel, Chief Information Officer at John Hancock. Full conversation: https://www.buzzsprout.com/520474/episodes/19925796

What You'll Learn
What happens when you measure how much of a real job an agent can actually finish, and why that number should change what you let it do unsupervised
The one line in hiring that should never be crossed, no matter how capable the technology becomes
Where human agency actually lives once the work itself is handed off, and why how it gets done may matter less than we assume
Why collecting data and acting on it are two different problems, and what opens up once that distance closes
The question worth asking before any AI project starts, and why the answer is sometimes something far simpler than AI
What to say to someone watching a machine learn to do the thing that made them valuable, and where the time that comes back should go

Inspired by something you heard in this episode?
Share your favorite insight about where people belong in the systems we are building, and tag us on social.
And don't forget to subscribe to AI and the Future of Work for more conversations with the leaders shaping the future of work.

Other special episodes:
SE 26: Designing AI for Accountability and Harmony with Leaders from Honeycomb, FieldAI, Archetype AI, and Zoom (Live from HumanX 2026 Special Episode)
SE 27: AI and the Next Generation: What We Can Learn from Them (International Youth Day Special Episode)
SE 19: AI and Education: How Artificial Intelligence Is Transforming Learning (International Day of Education Special Episode)
Lessons from Four Unicorn CEOs Disrupting Massive Markets with AI (Special Episode)
Ethical AI in Hiring: How to Stay Compliant While Building a Fairer Future of Work (HR Day 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)
27 min

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