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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Jake Saper is a General Partner at Emergence Capital, one of the most iconic venture firms in enterprise software, with a portfolio that includes Zoom, Gusto, Veeva, and Together AI. Emergence has backed some of the most category-defining B2B companies of the last two decades, and Jake has spent nearly 12 years at the center of that deal flow.
What sets Jake apart is a life lived on both sides of the creativity question: he backs the companies building AI but also performs across genres from blues to metal as a working musician.
In this episode, Jake brings that rare combination of investor rigor and artist instinct to one of the hardest questions AI is forcing us to face, and whether you leave reassured or unsettled may depend entirely on how much of your identity is wrapped up in the work you create.
In this conversation, we discuss:
How AI will democratize the creation of art but commoditize its execution, ultimately causing the value of live, dynamic human performances to skyrocket.
The stunning acceleration of startup growth, with top-quartile B2B software companies now scaling from zero to $1 million in ARR in just four months.
How the flood of AI-generated content is turning attention into the real bottleneck, and why curation and point of view become the new competitive advantage.
Why Jake believes the market will self-regulate the anthropomorphization of AI agents in the workplace, and where that logic has a hard limit.
What Geoffrey Hinton said about building AI "like a mother," why it was both comforting and deeply unsatisfying, and what it reveals about AGI risk.
Why Jake argues disclosure matters during this transition period, but what he actually wants people to ask about art as AI becomes a normal creative tool.
Explore this conversation:

00:00 Why AI Makes It Easier to Build a Demo and Harder to Build a Moat
05:25 From Cell Towers to Venture Capital: Jake Saper's Path to Emergence
08:53 How AI Is Compressing Startup Growth: From 18 Months to 4 Months to $1M ARR
18:05 What Art Actually Is: Compressed Human Experience and the Act of Making Meaning Shareable
23:30 How AI Can Unlock Latent Creativity in People Who Don't Think of Themselves as Creators
26:55 Why Disclosure Matters When Trust and Authenticity Are at Stake
30:19 Navigating a Post-Truth Era: When Everything Looks Synthetic, What Do We Believe?
32:14 Why the Value of Live Performance Is About to Skyrocket
35:58 As Soulless Entities Multiply, Soul-to-Soul Human Connection Becomes More Valuable
40:38 What Geoffrey Hinton Said About Building AI "Like a Mother" and Why It Was Unsatisfying
43:04 Why the Most Enduring Art Has Always Been About Transfer, Not Authorship

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On How AI Is Revolutionizing Creativity in Art, Music, and Education

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Daniel Lereya is Chief Product and Technology Officer at monday.com, the AI work platform trusted by 60% of the Fortune 500 and valued at approximately $8 billion. He joined the company when it had 30 people and $4.5M ARR, and has since grown his team from 5 to nearly 900 people as monday.com crossed $1 billion in ARR.
In this episode, Daniel draws on nearly a decade of scaling one of the world's most adopted work platforms to share what it actually takes to rebuild product thinking from scratch when AI changes everything you thought you knew.
In this conversation, we discuss:
Why the instincts that made monday.com successful are the exact ones Daniel says had to be dismantled to build AI-first products.
What the critical difference is between building a demo that impresses and an agent that actually works in production, and where most teams get it wrong.
Why Daniel believes wrapping AI inside rigid workflows produces better results than giving agents full discretion, and what monday.com learned the hard way.
What happened when 2,000 of 3,000 monday.com employees started building their own apps in just two weeks, and what it revealed about the future of who gets to build software.
Why Daniel argues that when an AI agent makes a mistake, the real question leaders should be asking has nothing to do with the technology.
Why the biggest barrier to AI adoption is not the technology itself, and what Daniel says companies must stop waiting for before they start.
Explore:

00:00 Why AI Adoption Is Harder Than It Looks
00:53 Introduction + AI Commerce Standards: Google, OpenAI & Visa
04:30 Daniel Lereya's 9-Year Journey Scaling monday.com to $1B ARR
09:00 How AI Forces a Complete Reset in Product Thinking
12:25 The "AI Month" Initiative: Pausing R&D to Rebuild from Scratch
14:57 Building AI Products When the Output Is Non-Deterministic
20:47 What 250,000 Customers Taught Us About AI in the Real World
25:38 Responsible AI: Guardrails, Governance, and Data Control
31:28 Who Is Responsible When an AI Agent Makes a Mistake?
37:04 The Future of Work: Humans, Agents, and What Comes Next
Resources:
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Connect with Daniel on LinkedIn
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On How we can take back control from Big Tech
https://peoplereign.io/podcast/

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Lisa Davis is a technology executive who has served as CIO and tech leader for some of the world's most complex organizations, including Intel, Blue Shield of California, the U.S. Marshals Service, and the Department of Defense. 
She is now focused on shaping the next generation of leaders and advocating for women and diverse talent in STEM through her board work, executive coaching, and her forthcoming book, The Only Woman in the Room: How to Win in a Workplace Still Built for Men.
In this episode, Lisa draws on 30+ years leading technology at the highest levels of government and enterprise to make the case that the future of AI depends on who gets to build it, and as long as women remain locked out of those rooms, we are getting it dangerously wrong.
In this conversation, we discuss:
Why women's representation in STEM has fallen from 34% in the mid-1980s to 22% today, and why that decline is a crisis for the future of AI, not just the workplace.
Why the real risk isn't the technology itself but the leadership teams making AI decisions without diverse voices at the table.
The structural systems that were never designed for women to thrive, and why redesigning them is a business imperative, not a social favor.
Why current corporate layoffs are being falsely attributed to AI, and what leaders need to start saying out loud.
Why girls begin dropping out of math and science as early as middle school, how cultural norms around "bossiness" suppress leadership potential, and what parents and organizations can do to intervene earlier.
What Lisa says women who finally reach the executive table must do differently, and why most don't.
Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Lisa on LinkedIn or visit her website to learn more about her book.
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James Cham is a Partner at Bloomberg Beta, the venture capital firm recognized by CB Insights as the #2 investor in AI. He has spent years backing the companies quietly building the infrastructure of tomorrow's economy, including Orbital Insight, Primer, Domino Data Labs, and AppZen. 
A Harvard CS graduate and MIT MBA, James brings a rare combination of technical depth, philosophical seriousness, and long-horizon investing perspective to every conversation. 
In this episode, he challenges some of the most popular  assumptions in enterprise AI adoption (including the idea that keeping humans in the loop is always the right answer) and makes a compelling case for why the moral and economic decisions we make right now will shape the nature of work for the next hundred years.
In this conversation, we discuss:
Why the people who benefit from AI models, not those impacted by them, should bear full legal and moral responsibility for the harms they cause
Why comparing AI to a flawless "Platonic ideal" is a mistake, and how the mathematical consistency of models is a massive advantage over noisy, unpredictable human decision-making
The case for pulling humans out of the loop and why romanticizing your role in the process is exactly how organizations miss the real opportunity
Why corporate America's "gold star" approach to AI adoption, tracking how many employees used AI once this week, is a dangerous distraction from what heavy users are already doing
How ancient wisdom and the biblical concept of creation in Genesis can help us navigate the moral responsibilities of building new technologies
James’s three massive investment theses, including the untapped market for AI tools with high emotional intelligence and why developers spending over $50 a day on tokens are already living in the future
Resources:
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Connect with James on LinkedIn
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On How AI Impacts Humanity

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Adrian McDermott is Chief Technology Officer at Zendesk, where he leads the company’s product management and engineering teams and helps shape the technology behind one of the world’s most widely used customer service platforms. He joined Zendesk in 2010 and has played a key role in guiding the company’s product and platform strategy as customer experience continues to evolve in the age of AI. Drawing on years of experience building enterprise software used by service teams around the world, Adrian brings a thoughtful perspective on how AI can help organizations deliver better customer service while allowing people to focus on the work humans do best.
In this conversation, we discuss:
How customer service evolved from a cost center with rigid scripts and binders into a strategic function where technology helps teams deliver better experiences.
Why customer service leaders shouldn't fear automation — and why everyone has a "service debt" that AI can finally help pay down.
The shift from traditional contact centers to AI-enabled service platforms that help companies respond faster while improving both employee and customer experience.
Lessons Adrian learned scaling Zendesk from a small product team to a global platform serving 100,000 customers and how product-led growth shaped that journey.
The critical challenge of moving from non-deterministic, creative AI models to deterministic, reliable solutions necessary for enterprise trust and safety
The future of context engineering and why the next major leap in AI won't be about superintelligence, but about building systems that capture and act on the knowledge created in every customer interaction.
Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Adrian on LinkedIn
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