What if the biggest barrier to AI transformation isn’t technology at all, but the fact that most organizations don’t actually understand how work gets done?

In this episode of The Future of Less Work, host Nirit Cohen sits down with Vijay Swaminathan, co-founder and CEO of Draup, to explore what really breaks when AI meets industrial-age assumptions about jobs, roles, and headcount.

The conversation begins with a fundamental shift in strategic workforce planning. Once a headcount exercise buried inside HR, it is now being pulled into the center of enterprise strategy as organizations try to allocate work between humans, machines, contractors, and AI agents. Vijay explains why traditional job descriptions no longer reflect reality, how large portions of work remain hidden inside workflows and processes, and why this invisible layer holds the greatest opportunity for AI-driven productivity.

Together, Nirit and Vijay unpack how roles are fragmenting into builders, orchestrators, and synthesizers, why labor arbitrage is losing its power, and how leaders often underestimate the complexity of the human work that remains after automation. They also explore why metrics of power, control, and success built around headcount and org charts are starting to collapse, and what replaces them.

This episode is a deep dive into the uncomfortable truth behind AI transformation: before organizations can redesign jobs, they must first see the work itself. And that shift, from org charts to workflows, may be the hardest change of all.

If you’re trying to make sense of AI, skills volatility, and the future of workforce planning, this conversation offers a clear lens into what’s already changing beneath the surface.

https://youtu.be/zkSdBx8L8zM

Guest Information:

Vijay Swaminathan is the Co-Founder & CEO of Draup, an AI copilot that helps global enterprises make strategic talent decisions. A recognized thought leader in the talent space, Vijay brings deep expertise in product ideation, concept-to-product transitions, and platform enablement. His career is marked by a strong command of data analytics, operations research, and strategic management. Vijay has designed numerous quantitative models and heuristics focused on global talent dynamics, cutting-edge business analytics, and strategic business maneuvers. He is also the co-founder of Zinnov, a leading research & advisory firm, and TalentNeuron, which was acquired by CEB, a Gartner company (NYSE: IT). Previously, Vijay held senior positions at Hewitt Associates and KPMG Consulting.

Links:
https://draup.com/talent/ceo-newsletter/mastering-ai-readiness-for-hr-leaders

https://draup.com/talent/ceo-newsletter/the-hidden-work-in-hr-building-on-mits-project-iceberg

https://draup.com/talent/ceo-newsletter/tech-talent-strategies-of-2025-draups-annual-report

https://draup.com/talent/ceo-newsletter/the-new-frontier-of-strategic-workforce-planning

Chapters:

00:00 – How AI Is Changing Strategic Workforce Planning
01:25 – What Does Strategic Workforce Planning Mean in the Age of AI?
05:35 – Why Job Descriptions No Longer Reflect Real Work
07:48 – How AI Exposes Hidden Work Inside Organizations
09:25 – Can AI Read Process Maps and Redesign Workflows?
11:02 – Why Companies Struggle to Document Real Tasks
12:58 – Builders vs Orchestrators: Who Actually Uses AI in Enterprises?
15:38 – Where Leaders Oversimplify AI Workforce Transformation
17:25 – Why Human Verification Gets More Complex With AI
20:09 – What Happens to Work in an AI-Driven Organization?
22:36 – Why AI Forces Companies Beyond the Org Chart
24:23 – Rethinking Headcount Models in the Age of AI
26:21 – Should Workforce Planning Focus on Workflows Instead of Jobs?

When work breaks apart into tasks and AI steps in as a real participant, not just a helper, the familiar structure of jobs begins to unravel.

The real question becomes how work gets recomposed, who orchestrates it, and how people redefine their value when execution is no longer the core of the role.

In this episode of The Future of Less Work, host Nirit Cohen sits down with Carrol Chang, President of Andela, to explore what happens when the atomic unit of work shifts from jobs to tasks. Drawing on her experience leading global talent systems and marketplaces, Carrol explains why AI is forcing organizations to rethink not just productivity, but how work is allocated, priced, managed, and ultimately experienced.

Together, Nirit and Carrol unpack why breaking work into tasks doesn’t eliminate the need for humans, but radically elevates it. As AI takes on execution, people move into roles that demand judgment, coordination,
feedback, and orchestration. The conversation explores why every individual contributor is becoming more like a manager, how professional identity evolves when tasks change faster than titles, and why leadership now depends on setting expectations for continuous role reinvention.

The episode also looks at what this shift unlocks beyond organizational boundaries. As work becomes more modular, highly specialized skills can be deployed across multiple projects, opening the door to new ways of earning, learning, and balancing life. Platforms, AI-enabled onboarding, and global talent networks emerge as the infrastructure that makes this possible, allowing work to scale without forcing everyone into a 40-hour week designed for the industrial era.

If you’re thinking about how AI reshapes careers, why flexibility is moving upstream into high-skill work, and what it really means to design work in a world where intelligence is abundant, this conversation offers a grounded and human-centered lens on what comes next.

https://youtu.be/nYkUjZBL0sE

Guest Information:
Serving as CEO of Andela since September 2024, Carrol Chang is committed to scaling the business while remaining true to its mission-driven approach of connecting brilliance with opportunity. She joined Andela from Uber, where she led efforts to improve work for nearly 7 million flexible workers around the world as the Global Head of Driver & Courier Operations.

Carrol has held positions with McKinsey Company, Portraits of Hope, and the administration of President Barack Obama.

She is passionate about expanding opportunity in all forms to underrepresented populations and making commerce more generous and kind for all stakeholders. She holds a BA from Harvard and both a JD and MBA from Northwestern University.

Chapters:
00:00 Why Jobs Are No Longer the Basic Unit of Work
01:36 What Does It Mean to Break Jobs Into Tasks With AI?
03:44 Can Task-Based Work Scale Inside Large Organizations?
04:10 How AI Turns Every Employee Into a Manager
05:40 Do Companies Need to Redesign Jobs After AI?
07:44 How Should Professionals Redefine Their Identity in the Age of AI?
09:39 Will AI Change Job Titles and Organizational Structures?
11:41 Do We Need to Rebundle Work Into New Job Structures?
13:29 Can Specialized Skills Be Deployed Across Multiple Projects?
15:51 How Can Organizations Manage Work Done by Fractional Talent?
17:00 Is This the Evolution of the Gig Economy for High-Skilled Work?
18:45 How AI Makes Platform-Based Work Scalable for Enterprises
19:36 What Happens to Culture When Work Is Unbundled?
21:49 Can AI Accelerate Employee Onboarding and Culture Fit?
23:42 How Company Email Norms Reveal Organizational Culture
24:30 Will AI Reduce the 40-Hour Workweek?
26:30 How Should Leaders Prepare for the AI Change Curve?

When AI stops being experimental and starts acting inside everyday workflows, the conversation about work changes completely. The question is no longer which tools to deploy, but who gets to redesign how work actually happens.

In this episode of The Future of Less Work, host Nirit Cohen sits down with Bhavin Shah, co-founder and CEO of Moveworks, to explore what happens inside organizations once AI moves beyond summaries and copilots into real action. Drawing on what he sees across large enterprises, Bhavin explains why the next phase of AI innovation is being driven not by executives or engineers, but by frontline employees who know exactly where friction lives.

Together, Nirit and Bhavin unpack why top-down AI strategies often stall, how non-technical teams are quietly rebuilding broken workflows, and why the most important metric for AI success is no longer outputs generated but actions completed. They explore the shift from fighting shadow IT to embracing “sanctioned autonomy,” where leaders provide guardrails and platforms, then step back and let innovation emerge from the work itself.

The conversation also looks ahead at what this means for trust, leadership, and careers. As agents take on routine work, roles begin to level up, managers become designers rather than approvers, and influence starts to flow from those who improve systems rather than those who control them.

If you’re wondering who becomes the architect of work when automation is accessible to everyone, and how organizations move from AI that talks to AI that truly changes outcomes, this is a conversation you won’t want to miss.

https://youtu.be/qv0_pozxfP0

Guest Information:

Bhavin Shah is the CEO and co-founder of Moveworks (recently acquired by ServiceNow), the agentic AI assistant platform for the enterprise. He’s spent his career building technology that actually solves problems for people at work. Raised in Silicon Valley and shaped by early exposure to tech pioneers, Bhavin’s journey took him from collaborating with Dr. Sally Ride at UC San Diego to leading impactful projects at LeapFrog, where he helped bring educational tech to children worldwide, extending its impact with a prenatal health education program for women in Afghanistan. He later founded Refresh.io, which was acquired by LinkedIn in 2015, before launching Moveworks in 2016 to help organizations automate workflows and boost productivity using AI.

Today, over 350 enterprises, including 10% of the Fortune 500, and over 5.5 million employees rely on Moveworks.
Bhavin holds a B.S. in Computer Science from the University of California, San Diego and a Master’s degree in Education, Technology, and Business from Stanford University.

Chapters:

00:00 — Who Should Drive AI Transformation at Work?
01:29 — Why AI Innovation Is Coming From the Frontline
03:29 — Can Employees Redesign End-to-End Workflows With AI?
05:30 — How Agentic AI Connects Fragmented Enterprise Systems
07:46 — Is Shadow IT Becoming a Competitive Advantage?
10:06 — What Does “Sanctioned Autonomy” in AI Really Mean?
11:37 — Why AI Summarization Is No Longer Enough
13:30 — Can Organizations Trust AI That Takes Action?
15:31 — How Guardrails Replace Control in AI-Driven Work
17:27 — Will AI Fool Us or Make Us Smarter at Work?
18:45 — How Agentic AI Is Changing Non-Technical Jobs
19:49 — Does Automation Actually Level Up Human Work?
21:54 — How Much Work Can AI Really Eliminate?
23:47 — Why Companies Are Scaling Faster Than Ever With AI
25:29 — What Happens When Innovation Cycles Speed Up?
26:54 — What Question Should We Be Asking About the Future of Work?

Why do meetings feel like the place where work goes to die—and what would it take to finally fix them?

In this episode of The Future of Less Work, host Nirit Cohen sits down with Dr. Rebecca Hinds, organizational researcher, founder of Asana’s Work Innovation Lab, founder of the Work AI Institute at Glean, and author of Your Best Meeting Ever, to unpack why meetings became one of the most broken systems in modern organizations.

Together, Nirit and Rebecca explore why organizations default to meetings even when asynchronous tools exist, how unclear communication norms fuel meeting overload, and what it means to design meetings for the people in the room rather than the organizer. Rebecca introduces practical frameworks from the book, including the “4D test” for deciding when a meeting should exist, how to shorten meetings without losing impact, and why status update meetings are one of the biggest drains on organizational time. They also examine the role of AI in meetings—where it genuinely helps and where it quietly makes bad meetings worse by masking deeper design problems. The episode closes with a broader reflection on the future of work, calm technology, and the responsibility leaders have to use AI in ways that amplify human potential rather than replace it.

If you’ve ever questioned why your calendar feels full but progress feels slow—or wondered how meetings could become a lever for better work instead of a blocker—this conversation offers both a diagnosis and a way forward.

https://youtu.be/sR1c9d982gI

Guest Information:

Rebecca Hinds is a leading expert on organizational behavior and the future of work. She holds a BS, MS, and PhD from Stanford University. Rebecca founded the Work Innovation Lab at Asana and the Work AI Institute at Glean, first-of-their-kind corporate think tanks dedicated to conducting cutting-edge research on the future of work. Her research is consistently featured in publications like Harvard Business Review, The New York Times, The Wall Street Journal, Forbes, Fast Company, Wired, TIME, CNBC, Bloomberg, Axios, and the Washington Post. Rebecca has been invited to speak on major stages including Dreamforce, SXSW, INBOUND, Ai4, Cloudfest, and the Gartner Digital Workplace Summit. She regularly appears on podcasts and programs, including Adam Grant’s Worklife podcast, Deloitte’s Capital H podcast, and as an instructor for CNBC’s Make It Masterclass, “How to Use AI to be More Productive and Successful at Work.” She is a trusted advisor to companies navigating challenges of modern work—from meeting overload and hybrid dysfunction to the realities of AI adoption.

YOUR BEST MEETING EVER: 7 Principles for Designing Meetings That Get Things Done By Rebecca Hinds, PhD| On-Sale: February 3, 2026

https://www.simonandschuster.com/books/Your-Best-Meeting-Ever/Rebecca-Hinds/9781668067482

Chapters:

00:00 — Why Do Meetings Feel Like They Get Nothing Done?01:11 — What Is a “Good Meeting” and Why Are Most Meetings Bad?02:54 — Why Do We Default to Meetings Instead of Asynchronous Work?04:55 — How Broken Communication Systems Create More Meetings06:54 — What Is the 4D Test for Deciding If a Meeting Should Exist?08:44 — Which Decisions Actually Require a Meeting?09:52 — Why Do Meetings Always Last an Hour?10:40 — How Shorter Meetings Can Be More Effective12:25 — Can Running Better Meetings Help Advance Your Career?14:22 — How to Design a Meeting Agenda That Actually Works16:07 — Which Agenda Items Should Never Be in a Meeting?17:37 — How to Measure If a Meeting Is Worth the Time19:09 — Why Some People Find Meetings Valuable and Others Don’t20:56 — Does AI Make Meetings Better or Worse?23:01 — Should You Attend a Meeting If You’re Sending a Bot?24:36 — Which Meetings Should We Stop Having First?26:11 — Why Cancelling One-on-One Meetings Is Dangerous27:58 — How Should Leaders Think About AI and Human Potentia

What happens when AI agents stop assisting work and start reshaping how value moves through an organization? And what does that mean for people, roles, and leadership when velocity matters more than productivity?

In this episode of The Future of Less Work, host Nirit Cohen sits down with Tim Sanders, Chief Innovation Officer at G2, to explore how agentic AI is changing the very mechanics of work. Drawing on G2’s large-scale enterprise data and Tim’s experience across platforms like Upwork, the conversation moves beyond hype to examine what’s actually happening inside organizations adopting AI agents.

Together, Nirit and Tim unpack why jobs should be understood as collections of tasks and judgment, how agents are removing repetitive work while elevating human contribution, and why the real competitive advantage lies in augmentation rather than substitution. They explore the shift from productivity to velocity, why organizations stall when they overload “human-in-the- loop” approvals, and how trust—not technology—is the true gate
to scaling AI autonomy.

Tim shares concrete examples from industries like banking to show how management decisions, not technical limits, determine success with agents. The discussion also dives into emerging roles such as agent designers, auditors, and managers, and why judgment, taste, and goal-setting—not technical expertise—will define the most valuable work in an AI- driven world.

If you’re wondering how AI agents will change careers, leadership, and what it means to do meaningful work when machines handle the grind, this conversation offers a grounded and deeply human perspective on what comes next.

https://youtu.be/GFnDi7L3Aog

Guest Information:
Tim Sanders is the Chief Innovation Officer at G2. He’s also an executive fellow at the Digital Data Design Institute at Harvard and a New York Times bestselling author of five books, including Love is the Killer App.

Links:

• G2's AI Agents Insight Report "AI Agents are Winning Hearts and Wallets"
• Tim's 5 Bold Predictions on the Rise of Agentic AI and the $30B Orchestration Boom

Chapters:
00:00 — What happens when AI starts doing the work?
01:20 — If AI takes the tasks, what do humans do?
03:00 — Does automation actually make jobs more valuable?
05:06 — Is AI really replacing jobs or is that a myth?
07:26 — Why can’t companies shrink their way to greatness?
09:20 — Why productivity is the wrong metric in an AI world
11:35 — How AI changes business growth and velocity
13:37 — Why fear blocks AI adoption inside organizations
15:08 — Why leaders and employees see AI so differently
17:05 — How much should humans stay in the loop with AI?
19:03 — When does human oversight slow work down?
21:00 — Who actually decides how much AI autonomy to allow?
22:06 — How leaders misjudge risk when designing AI workflows
23:15 — How do you bring people along when AI changes work?
24:59 — Why trust matters more than technology for AI scale
26:38 — What new roles emerge when AI agents do the work?
28:18 — What makes someone a good manager of AI agents?
29:57 — What signals show where the future of work is heading?
31:30 — How do people build judgment if AI does the entry work?
32:47 — Is experience really what builds human judgment?
34:49 — How must education change for an AI-driven world?
35:45 — What question should we all ask about our work now?

What happens when competitive advantage no longer comes from having the right plan, but from how quickly you can adapt when the plan stops working?

In this episode of The Future of Less Work, host Nirit Cohen sits down with Arjan Singh, author of Competitive Success, to explore what strategy looks like in a world defined by uncertainty, AI, and constant disruption. As organizations move away from long-term planning cycles, the conversation reframes strategy as a living capability rather than a static document.

Together, Nirit and Arjan unpack why traditional planning assumptions collapse in volatile markets, how corporate war games help leaders surface blind spots before they become costly mistakes, and why preparing for unlikely but high-impact scenarios matters more than predicting the future. They discuss how AI is reshaping decision-making by making data abundant while elevating the importance of human judgment, context, and cultural awareness.

The conversation goes beyond strategy teams and into the future of work itself. Arjan explains how continuous preparedness is changing leadership roles, why middle management must shift from reporting to decision quality, and what happens to early-career roles when routine analytical work can be automated in minutes. They also explore the risks of over-optimizing for efficiency and underestimating the nuanced human contributions that differentiate organizations in an AI-saturated world.

If you’re trying to understand how leaders, organizations, and individuals can stay relevant when certainty is gone and advantage is temporary, this episode offers a powerful framework for thinking, deciding, and competing in the future of work.
https://youtu.be/uAJvbPT7DYk

Guest Information:
Arjan Singh, author of Competitive Success: Building Strategies with Corporate War Games, is an expert in helping companies develop data-driven strategies through war games, strategic and competitive analysis, scenario planning and building business early warning systems that deliver significant impact. He has advised 68 of the top 100 companies in the Fortune Global 500 list in building winning strategies. Singh is an Adjunct Professor of Marketing and Global Consulting at Southern Methodist University (SMU) COX School of Business.

Chapters:
00:00 – How Do You Build Strategy When You Can’t Predict the Future?
01:21 – What Are Corporate War Games and Why Do Companies Use Them?
02:30 – How Do You Plan When Markets Are Unstable and Assumptions Break?
03:20 – Can You Prepare for Events That Seem Impossible or Unlikely?
05:20 – What’s the Difference Between Scenario Planning and War Gaming?
07:32 – Why Long-Term Strategic Planning No Longer Works
08:51 – What Is Continuous Strategy and How Is It Different from Annual Planning?
11:10 – What Decisions Should Humans Make When AI Handles the Data?
13:19 – How Do Leaders Balance Data, Judgment, and People Impact?
15:20 – Why Do Organizations Ignore Bad News and Worst-Case Scenarios?
17:15 – How Do You Challenge Leadership Assumptions Without Getting Shut Down?
19:33 – How Can Companies Identify Blind Spots Before Competitors Do?
21:20 – Is Being Prepared a Competitive Advantage?
23:22 – How Is AI Changing Management and Middle-Management Roles?
25:48 – Which Jobs and Skills Are Most at Risk from AI Automation?
27:44 – Are Companies Overestimating What AI Can Replace?
28:56 – How Do You Build Comfort With Ambiguity and Uncertainty?
30:14 – What Question Should We All Be Asking About the Future of Work?

What happens when artificial intelligence meets work that can’t be fully documented, standardized, or abstracted?

In this episode of The Future of Less Work, host Nirit Cohen sits down with Shin Nakamura, President of ONE to ONE Holdings, to explore the limits of AI through the lens of manufacturing. Drawing on his experience leading factories across Japan and Vietnam, Shin offers a grounded view of why much of today’s work still depends on human judgment, cultural context, and knowledge that lives in people rather than systems.

The conversation moves beyond the familiar blue-collar versus white-collar debate to examine a deeper divide: work that can be reduced to tasks versus work that requires adaptation, situational awareness, and tacit expertise. Together, Nirit and Shin unpack why low-volume, high-variation environments resist automation, how language and culture quietly shape whether AI succeeds or fails, and why so much critical knowledge has never been written down in the first place.

They also reflect on what Gen Z’s career choices reveal about this shift, why career security is being redefined around capability rather than job titles, and how AI risks widening gaps by making some forms of work visible while leaving others invisible.

If you’re trying to understand where AI delivers real value, where it falls short, and what kinds of work are likely to endure in an automated world, this conversation offers a rare, on-the-ground perspective from the factory floor.

https://youtu.be/WupIMAo_G7g

Guest Information:

Shinichiro (SHIN) Nakamura, President of one to ONE Holdings:

Shin is a manufacturing and global thought leader in the secondary steel processing industry. He is the President of ONE to ONE Holdings, which operates steel tube-making factories in Japan and Vietnam and provides inline galvanizing technology to tubing companies worldwide. His original family business, Daiwa Steel Tube Industries, is one of the largest producers of inline-galvanized steel tubes in East Asia.

From leading cross-border operations to overseeing factory-level development, Shin works directly within the type of blue-collar workforce that younger professionals are increasingly gravitating to. This gives him a close view of how job preferences are shifting, why some young workers are choosing skilled manufacturing roles over traditional office careers, and what industries like his are doing to attract and retain new talent.

Shin is a past Regional Chair of the YPO North Asia region and currently serves on the Board of Governors at the Asia School of Business. He previously worked as a consultant at Bain & Company and received his MBA from MIT Sloan, specializing in New Product & Venture Development.

Chapters:
00:00 — Why Gen Z Is Choosing Manufacturing Over Office Jobs
01:31 — Why Young Workers See the Future of Work Differently
03:08 — How Income Inequality Is Reshaping Global Career Choices
04:59 — How Automation and Robotics Are Changing Factory Jobs
06:00 — Why Some Manufacturing Jobs Cannot Be Fully Automated
07:33 — What Young Workers Expect From Modern Factory Jobs
09:44 — Are White-Collar Job Losses Pushing Talent Into Manufacturing?
10:36 — How Manufacturing Must Change to Attract Skilled Talent
12:40 — How AI Adoption in Manufacturing Depends on Economics
13:58 — Does AI Work Equally Well Across Languages and Cultures?
15:35 — Why AI Struggles With Tacit and Cultural Knowledge
17:26 — Why Japanese Manufacturing Knowledge Is Hard to Digitize
19:17 — Where AI Stops Working in Craft-Based Industries
20:52 — Why Shorter Careers Threaten Knowledge Transfer
21:55 — How Manufacturers Make Blue-Collar Jobs More Attractive
22:56 — The Most Important Question About the Future of Work