What really happens after selling a business? Here’s my story of letting go, finding freedom, and building a new life by design.

I never started my company with the goal of selling it. In fact, for most of its life, the thought of letting go never even crossed my mind. I loved the work, loved the team, and loved the challenge of growing something from nothing.

But businesses, like people, have a lifecycle. My partners were older and started asking the hard questions: How does this end? What’s the plan? At first, my answer was simple: Why sell? We’re making money, we’re successful, I’m happy. Let’s just keep going.

Then reality hit me. At some point, it has to end. A business doesn’t run forever, and pretending it will is just self-delusion. So I began a new journey I hadn’t anticipated – preparing to scale myself out of the business.

Freedom > Money

When we started thinking seriously about an exit, one thing became crystal clear to me: I wasn’t going to stick around for an earn-out.

On paper, an earn-out can look appealing – more money dangled on the back end, a chance to “prove” the business continues to perform. But here’s the truth: I didn’t start my company for money. I started it for freedom.

The idea of selling my company only to turn around and ask permission to take a Friday off, submit expense reports, and work under someone else’s rules? No thanks. That would have been the exact opposite of why I became an entrepreneur in the first place.

For me, the real wealth was autonomy. The money just came along for the ride.

Culture by Design

If you ask most founders what makes their business valuable, they’ll point to revenue, margins, or growth rates. All important, of course. But for me, one of the things I was most proud of was our culture.

I’d spent years inside Fortune 500 companies as a consultant, walking into rooms where three out of four people clearly hated their jobs. The corporate dread was palpable. I swore I’d never build a company like that.

So I worked relentlessly to create a culture by design, not by default. We built a small but mighty team that genuinely enjoyed working together. Even though we were a remote company, we had camaraderie, trust, and a sense of fun.

That made the exit harder. Selling wasn’t just a financial decision – it meant handing over a group of people I cared about. I wanted to be sure they’d be treated well, that the company we’d built with intention wouldn’t get crushed under someone else’s bureaucracy.

Letting go of the numbers was easy. Letting go of the people was not.

The Letting Go

The funny thing about an exit is how quickly you become irrelevant.

At first, the transition period was busy – my inbox full, the team pinging me constantly with questions: Where do we keep this file? How do we handle that client? Who signs off on this contract? I was happy to answer, to ease them into the new reality.

But week by week, the questions slowed. Until, almost overnight, they stopped. No more pings. No more calls. No one needed me anymore.

At first, it felt liberating. After 20+ years of running a company, I could wake up at 10:30, pour a glass of wine, and call it a day if I wanted to. No pressure. No responsibility. No weight on my shoulders.

But that freedom carried a sting I hadn’t expected: the realization that I wasn’t important anymore. I fell into what so many founders warned me about but I hadn’t truly understood – the post-exit hole. When you’ve tied your identity to building, leading, and being “the guy” for decades, what happens when all of that is gone?

It’s not the money you miss. It’s the meaning.

Life After Exit

If I could do it over again, I’d have taken more time off. A real break. Not two months of wine-at-10:30 novelty, but a year on an island somewhere – time to reset, disconnect, and rediscover myself outside of business.

Instead, I slipped back into old habits. Within weeks, I was dabbling with new ideas, tinkering with projects, starting new ventures. It wasn’t because I had to – the pressure of payroll and revenue was gone. It was because building is what I know. It’s who I am.

The difference this time? I no longer needed to swing for the fences. Some of my new companies are profitable, others are loss leaders. But I enjoy them. I explore what interests me, experiment with AI, create projects that are fun and useful – without the crushing weight of “it has to work.”

I also realized something important: freedom without purpose feels hollow. The real challenge after an exit isn’t money management. It’s meaning management. What do you want your days to look like when you never have to work again?

That’s where I’ve landed. Less about chasing, more about choosing. Less about running a company, more about running my life with intent.

Life Today

These days, I’ve built a different kind of routine. My health has become my top priority. I train, eat well, and treat fitness like it’s my job – because in a way, it is. Longevity is the best investment I can make.

The travel bug I’ve always had is now fully unleashed. With London as our home base, Michelle and I can hop across Europe at will. A long weekend in Italy, a few days in Switzerland, a week in Crete – no guilt, no stress, no asking for permission. Technology makes staying connected easy, so being globally mobile isn’t a hurdle anymore. (That’s probably another blog entirely.)

I’ve also discovered passions I never had time for before. Fine art and collectibles have become both an indulgence and an investment – a mix of beauty and strategy that keeps me sharp and engaged.

In short: life is pretty darn good. Not perfect, not without its challenges, but designed with intent. And that’s exactly the point.

Reflections on Letting Go

Looking back, the exit wasn’t really about selling a company. It was about learning to let go – of control, of identity, of the belief that my worth was tied to the business I built.

The truth is, I’ll always be an entrepreneur. I’ll always build, tinker, and create. But I no longer feel chained to it. My days are mine to design now, whether that’s a workout, a trip, or simply sitting in front of a painting I love.

What I’ve learned is this: the goal was never money. It was freedom. And the real work starts after you achieve it – figuring out how to live with purpose when you no longer have to do anything at all.

I scaled myself out of the business. What I found on the other side wasn’t emptiness. It was the space to build a life that feels like mine.

The post Scaling Myself Out of the Business: Lessons From Letting Go appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

If there’s one reason my life is richer, calmer, and more productive than ever, it’s this: I stopped doing things that drain me, annoy me, or just don’t serve any real purpose. Many people chase happiness by cramming more onto their to-do list. I do the opposite. I got intentional about what not to do.

This idea isn’t new, but it hit home for me when I saw Greg Isenberg share his “things I’m not doing anymore” list. It was so simple, so obvious, and yet so rare. So I started my own. Every month, I review it, update it, and hold myself accountable. My not-to-do list is my blueprint for a happier, saner, more meaningful life.

Why a Not-To-Do List Matters (And How I Build Mine)

For most of my career, I bought into the lie that doing more equals living better. More goals, more hustle, more obligations. All it got me was a busier calendar and a mind that never shut off. Eventually, I realized that real productivity and happiness come from doing less – less of what drains me, distracts me, or keeps me stuck.

That’s why I started my not-to-do list. Every month, I sit down and review it. My criteria are simple, and I don’t make exceptions:

• If it drains my energy, it’s out.
• If it creates stress for no good reason, it’s off the table.
• If I’m only doing it to serve my ego, not my real life, it gets axed.
• If it doesn’t move the needle on my happiness, fulfillment, or impact, it’s gone.
• If I’m doing it out of guilt, habit, or “because I always have,” I scratch it.
• If it makes my life smaller or more resentful, it’s history.

This isn’t about running from challenges or hiding from reality. It’s about intentionally making space for the people, projects, and experiences that add real value and joy to my life.

What’s On My Not-To-Do List Right Now

Here’s where things get real. This list isn’t theory – it’s the choices I actually make, month after month, to protect my energy and design a life that works for me:

• I don’t schmooze with random strangers at networking events. I never enjoyed it and I’ve stopped pretending it’s valuable. If a connection matters, I rely on personal introductions from people who know me and who I respect, not roomfuls of business cards.
• I don’t prioritize work over workouts. My health is non-negotiable. If the calendar gets tight, the gym wins. Everything and everyone is just going to have to wait.
• I don’t defer trips until “things settle down.” Life never really slows down and there’s never the perfect moment. If I want to go, I book it.
• I don’t fly long-haul red-eyes in economy anymore. One day lost to feeling like shit isn’t worth it. I value my health and my time too much.
• I don’t connect with random strangers on LinkedIn anymore. If there isn’t a clear, mutual, long-term benefit, I don’t hit accept. I just got rid of 80% of my LinkedIn connections and am not about to start collecting random faces or meaningless digital acquaintances again. My network is now intentional, curated, and valuable – quality over quantity, every single time.
• I don’t let guilt or pressure force me to respond to calls or emails immediately. I’ll get to it when I’m good and ready. My time, my rules.
• I don’t ignore health issues or procrastinate on self-care. I’m proactive, even if it means paying out of pocket for scans, tests, or treatments. Health before wealth.

Some of these might sound blunt or even ruthless. That’s the point. Every “no” on this list creates space for a bigger, better “yes.”

The Results – What Actually Changed When I Started Saying No

This isn’t theory or wishful thinking. The moment I started enforcing my not-to-do list, everything shifted. It’s all part of my Life by Design approach.

• More time and energy: I don’t waste hours on small talk, inbox ping-pong, or soul-sucking obligations. That space is now filled with the stuff that actually moves my life forward – workouts, trips, meaningful work, actual downtime.
• More clarity: By stripping away the noise, it’s obvious what (and who) is worth my attention. Decision-making is faster and less emotional.
• Less stress: Fewer pointless commitments means fewer drains on my mental bandwidth. I don’t let FOMO, guilt, or other people’s priorities run my day.
• Stronger relationships: With a curated network and more intentional connections, every conversation is higher-value, more enjoyable, and far less transactional.
• Better health: By refusing to put work, travel, or social obligations ahead of my well-being, I’m in the (almost, but not just yet) best shape of my life – mentally and physically.
• Real freedom: Saying “no” by default gives me the space to say “hell yes” to the right opportunities, people, and experiences.

The best part? None of this required superhuman discipline. Just the guts to put my happiness and priorities first.

Your Turn – Build Your Own Not-To-Do List

If you’re tired of feeling busy but unfulfilled, maybe it’s time to try subtraction instead of addition. Start by creating your own ‘not-to-do’ list. Write down every obligation, habit, or “should” that drains you, bores you, or keeps you stuck. Audit it ruthlessly. Then start by simply saying ‘no, thank you’, or just by quietly letting things go.

You’ll be surprised how quickly clarity and freedom show up when you stop doing what no longer serves you. Remember: every “no” is just space for a better “yes.” It’s your life – design it accordingly.

The post My Not-To-Do List: What I’ve Stopped Doing to Start Living appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

My Mantra – Launch Early, Fail Fast, Iterate Often

If there’s one lesson that’s followed me through every venture – from building my previous company into a SaaS leader, to launching experiments at Tomco Capital, to bottling my own gin – it’s this:

Launch early, fail fast, iterate often.

I didn’t invent the phrase, but I’ve lived it for decades. When we pioneered online SAP training, there was no roadmap, no “proven” model. We went first, took small calculated risks, and figured it out as we went. Not everything worked – some things crashed hard – but the point was, we didn’t wait for perfect. We shipped, we learned, and we did it again.

That same mentality is exactly what led me to gin. Not because I had a big business plan or dreams of building a spirits empire – but because I was curious, a little bored, and wanted to see how far I could get by just starting.

The Beefeater Epiphany – You Don’t Need a Giant Team

Not long ago, I took a tour of the famous Beefeater distillery in my neighborhood in central London. Here’s what blew my mind: the entire global supply of Beefeater gin is made in a plant about the size of a modest apartment building. The operation is run by a master distiller and two apprentices. That’s it.

Every excuse about “needing a huge team,” “millions in capital,” or “perfect infrastructure” fell apart right there. If three people can supply the world with one of the best-known gins, what was really stopping me – or anyone else – from launching something on a smaller scale?

That visit didn’t just demystify the gin business. It became a metaphor for entrepreneurship: scale isn’t about headcount or resources. It’s about focus, process, and the guts to do things differently.

I walked out thinking, if the big guys can do it lean, so can I. And so can you.

Just Start – How Tom’s Gin Came to Life

Armed with nothing but curiosity (and a newfound respect for simplicity), I decided to try making my own gin. No pedigree, no “plan” – just a willingness to get started and figure it out as I went.

I sourced a base spirit, ordered botanicals, and started distilling in embarrassingly small batches. The first try – Tom’s Bathtub Gin – wasn’t exactly world-class, but it was a start. Each round, I learned what worked (and what didn’t), tweaked the process, and kept iterating. That’s how Tom’s Blindmaker Edition was born, followed by Navy Strength and Gunpowder Gin. Some tasted great. Some were barely drinkable. All of them taught me something new.

Here’s the point:
You don’t need a perfect recipe, massive resources, or even a clear endgame.
You just need the guts to take the first shot, the humility to learn quickly, and the discipline to try again. Most people never get started because they’re waiting for permission, a plan, or some magical moment of certainty. That moment never comes.

What Tom’s Gin Really Is (and Why That’s the Point)

Let’s get real: Tom’s Gin isn’t a revenue machine, and I have zero plans to take on Tanqueray. Right now, it’s a passion project – a hobby with a label. Most of what I make gets “quality tested” (read: drunk) by me, and whatever’s left goes to friends and family. I’m not bottling dreams of global domination; I’m bottling curiosity.

And that’s exactly the lesson:
You don’t need grand ambitions, massive budgets, or an airtight business plan to start something.
You just need to be willing to move, to experiment, to accept that it might not work out (and to laugh when your first batch tastes like pine cleaner).
Anyone can start a gin brand – or any project, business, or side hustle – if they stop overthinking and just begin.

The only thing that separates you from the people doing the work is action.

The Real Lesson – Stop Waiting, Start Making

If you take anything from my gin experiments (or three decades of building companies), let it be this: The winners aren’t the ones with the best plan – they’re the ones who move first, learn fast, and aren’t afraid to look foolish along the way.

Stop waiting for permission, capital, or the “perfect” idea.
Start with what you have, launch early, fail fast, and iterate often.
You’ll never regret trying. You’ll only regret sitting on the sidelines, watching someone else bottle their own version of success.

What could you start – today – that you’ve been overthinking for years?
Chances are, you’re closer to your first batch (and your next breakthrough) than you think.

Want to stop overthinking and actually launch your next project or business? That’s exactly what I work on with my coaching clients. If you’re serious about taking action and want a partner who’s done it all, failures included: book a call with me.

The post How to Start a Gin Brand (and Why You Should Stop Waiting for Perfect) appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

The Turning Point – Choosing Intentional Living

Let’s get something straight: I’ve never been unhappy or stuck in a rut. My life, especially during my New York years, was full – travel, friends, business, experiences, you name it. But even in the middle of all that momentum, I couldn’t shake the feeling that much of it was happening to me, not by me. There was plenty of activity, but not enough intentionality.

That’s when I met Jack Daly and discovered his Life by Design philosophy. Jack isn’t your average self-help guy – he’s lived intentionally for decades, and it shows. His message was simple but powerful: if you don’t architect your life, it’ll get built by accident.

It wasn’t about fixing a broken life – it was about trading autopilot for intentional living. Jack’s approach pushed me to go beyond “busy” and start asking what I actually wanted from my days, my years, my experiences. It challenged me to become the designer, not just the passenger, of my own story.

Jack Daly’s Blueprint – What Living By Design Really Looks Like

Jack Daly’s approach is brutally pragmatic. Forget vision boards or vague resolutions – he’s all about taking control and living with intent. Jack’s “Life by Design” means identifying what you want more of (and less of), mapping it out, and then tracking your progress like your life depends on it – because it does.

Intentional living isn’t about micromanaging every minute or sucking the spontaneity out of your days. It’s about refusing to drift. It’s the difference between coasting through another year on autopilot and consciously building a life that actually lights you up.

When I first saw how Jack tracked everything – his workouts, adventures, relationships, milestones – I realized this wasn’t about control. It was about making sure the stuff that matters most actually happens. If you don’t make space for it, the rest of life will crowd it out. Simple as that.

Adopting intentional living means putting purpose at the center, and being ruthless about what you allow on your calendar. That’s not rigid – that’s freedom.

How I Practice Intentional Living – My Real Tracking System

I took Jack’s idea and stripped it down to something brutally simple. No complicated apps or color-coded dashboards – just a running note on my iPhone. This is intentional living with teeth.

Each year, I set clear, measurable targets for the things that actually matter to me:

• Strength training: 80 sessions
• Cardio: 40 sessions
• Swimming: 40 sessions
• Yoga/Pilates/Stretching: 40 sessions
• Sauna/Steam: 50 sessions
• Massage: 12 sessions
• Average daily steps: 8,000–9,000+
• Blood pressure: Keep average <135/85
• Events (concerts, shows, experiences): 12 minimum
• Date nights: 12 minimum—each one planned, not left to luck
• Trips, vacations, adventures: Every single one logged by month and year

Whenever I knock out a workout, book a trip, or do something memorable, it goes in the log. Some categories are ahead of schedule, others fall behind – but there’s no guessing and no hiding from the truth. That’s the beauty of intentional living: you always know exactly where you stand and what needs to change.

My Mid-Year Reality Check

So how’s it working? At the halfway mark, my log tells the truth – no room for ego, no place to hide. Some targets (strength training, sauna, events, travel) are right on track or ahead. Others – like cardio, stretching, or massages – could use more focus. That’s not failure; that’s the point.

The power of intentional living isn’t in perfection. It’s in the awareness and the ability to course-correct in real time. Instead of drifting and hoping I’m “doing okay,” I know where I’m crushing it and where I’m falling short. When I see a gap, I adjust. I book the trip, schedule the date night, call the trainer, or make the time for what matters.

This level of honesty and ownership means less regret, more momentum, and a sense of agency that just doesn’t exist when you leave your life to chance.

Why Intentional Living Matters (and What Actually Improves)

Here’s what’s changed for me: my life is less about “did I stay busy?” and more about “did I do what actually matters?”

I’m investing more in health, relationships, and real experiences. There’s less regret, less autopilot, and a hell of a lot more stories to look back on. Even when I fall behind in a category, at least I know and I can act, instead of just drifting.

Intentional living isn’t about squeezing joy out of life – it’s about squeezing more joy, meaning, and purpose into it. It’s about building a life worth remembering, not just letting the calendar fill itself.

Here’s my version of the classic Peter Drucker line:
Peter said, “What gets measured, gets managed.”
But I think it’s simpler: What gets measured, gets done.
If you don’t track what matters, you’ll fill your days with things that don’t.

Your Move – Design Your Own Year

Here’s my blunt challenge: Where in your life are you just hoping things will get better, instead of making sure they do?

Pick two or three things that actually matter – your health, your relationships, your adventures, your creativity. Track them for the next 90 days. No fancy tools. No perfection required. Just keep score, adjust as needed, and watch what happens.

You are always just one decision away from a totally different life.

That’s what Jack Daly’s Life by Design approach has given me: not a perfect blueprint, but the permission to live intentionally, measure what matters, and build a year that’s actually worth living.

So what are you waiting for? Start living with intent and make the next chapter one you’ll actually remember. If you need a coach to help you with this, book a call with me.

The post Life by Design – How I built a Life of Purpose, Intent and Meaning appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

Landing in Slow Motion

Arriving in Crete was like stepping into a different time zone – one where nobody seems to care what day it is, let alone what hour. We checked into a five-star design hotel perched above the Mediterranean, tucked away in a village so small it barely shows up on a map. Forget the usual crowds; it’s mostly locals here, with a handful of other travelers blending in quietly.

On our first afternoon, we wandered down to a tiny beach taverna. No English menu, no pressure. Mama’s in the kitchen, Dad’s sitting at the counter, sipping raki with water. The son, Adonis, smiled and said, “Today, my mom cooked chicken and potatoes. That’s what’s for lunch.” No debate, no choices needed. Alongside came a fresh salad, warm pita, proper tzatziki, and a carafe of Cretan wine. The meal took two unhurried hours, capped with yogurt and honey for dessert and two tiny cups of coffee.

For a moment, it hit me: I hadn’t checked my phone since we sat down.
Heaven.

The Poolside Pace and the Pull of Old Habits

Back at the hotel, the contrast was impossible to ignore. The infinity pool was lined with sun loungers, all of them occupied, yet almost everyone seemed glued to a screen. Phones, tablets, even laptops in the blazing sun. I watched one guy spend the entire day typing away, never once looking up at the view.

I could see it in the faces around me: that familiar restlessness. The compulsion to check messages or scroll for updates, even in paradise. I recognized it because I’ve lived it – traveling halfway across the world only to chain myself to Slack or email out of habit, not necessity.

Here, everything operates at a pace I’ve started calling the Mediterranean hour. Drinks arrive when they arrive. Meals stretch out with no rush. The staff move with purpose, not panic. It’s not a lack of care – if anything, it’s respect for the moment. But for anyone raised on “hustle” culture or the instant reflexes of a New York minute, this kind of enforced patience is both uncomfortable and, eventually, strangely refreshing.

From Urgency to Ease

Crete’s rhythm couldn’t be more different from the hustle cultures I’ve lived and worked in. A few weeks ago, I was in Dubai, where the atmosphere crackles with energy and every conversation feels like a pitch or a deal in motion (see my Dubai reflections here). Before that, I spent years in New York, where the “New York minute” isn’t just a phrase – it’s a way of life. There, waiting even sixty seconds for a coffee or a crosswalk feels unreasonable, almost insulting.

But here, the Mediterranean hour is the law of the land. Nothing is urgent. Meals aren’t events to rush through – they’re rituals to savor. Service is friendly, never frantic. There’s a deliberate refusal to let time control the experience.

If you’re used to racing the clock, this kind of environment is more than culture shock – it’s a test. The truth is, slowing down is hard if your default mode is acceleration. It’s especially tough for founders and high achievers who define themselves by what they accomplish and how fast they can do it.

But what struck me, once I stopped fighting it, is that the real luxury isn’t a beachfront suite or even the food – it’s the chance to disconnect from urgency itself. To feel the anxiety of “doing nothing” fade and discover what happens when you finally let yourself settle into the moment.

The Founder’s Freedom Test

If you’re a founder, here’s a challenge that Crete threw right in my face: Can you disappear for a week without your business skipping a beat? No frantic calls, no emergency emails, no micromanaging from afar. If the answer is no, you haven’t built a business – you’ve built yourself a very demanding job.

I’ve lived both sides of this. In my early days, I was convinced everything would collapse without my direct oversight. The idea of an actual vacation, where I truly unplugged, was laughable. But over the years, I learned to build an autonomous team of talented individuals, to put real systems in place, and to step away without fear that the wheels would fall off.

The result? Real freedom. Not just the freedom to travel, but the freedom to be present – to slow down, enjoy long meals, and let my mind wander. In Crete, I saw how rare that actually is. Most people are still tethered to their inbox, even by the pool. But if you build your company right, you get to experience what most only dream about: genuine time off, with nothing urgent hanging over your head.

What You Gain by Letting Go

Here’s what no one tells you: when you finally let go and trust your business to run itself, you don’t just get a break – you get your mind back.

You start to notice things you would’ve missed before: the way the sea breeze feels at lunch, the subtle differences in tzatziki from one taverna to the next, a conversation that drifts into unexpected territory simply because you have the time to let it.

Your best ideas don’t come from staring at a screen or racing to inbox zero. They arrive in the quiet, when you finally let your brain off the leash. And back home? Your team grows in confidence and skill, because you’re not hovering over their every move. Real leadership is about building something that works when you’re not watching.

This isn’t about laziness or checking out. It’s about creating the kind of autonomy that lets you live at least a little bit of life on “Mediterranean hour” – not just for a week in Crete, but every day.

The Real ROI of Slowing Down

So here’s the real test: Are you building a business – or a lifestyle – that lets you step away? Can you trust your team, your systems, and yourself enough to unplug for a week and truly live on your own terms?

If you’re still glued to your phone at the pool, still measuring your worth by how busy you are, maybe it’s time to reconsider what “success” really means. Anyone can fill their calendar. The real ROI comes from being present – long lunches, lazy afternoons, and letting life unfold at its own pace.

The Mediterranean hour isn’t just a slower clock. It’s a challenge to design your business (and your life) for freedom, not just for growth. It’s not about doing less – it’s about finally having the space to do what actually matters.

Here’s to building businesses that give you real time, real presence, and the option to disappear without everything falling apart.

The post Trading the New York Minute for the Mediterranean Hour appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

I just got back from a week in Dubai, and honestly, it’s hard to compare it to anywhere else. Two decades ago, this place was a forgotten Army outpost in the sand. Now? Everything is pristine, oversized, and built to impress. Skyscrapers popping up like weeds, islands shaped like palm trees, shopping centers that make American malls look like convenience stores. It feels a bit like Las Vegas (without the casinos) and a turbocharged Miami – but even bolder. And stepping outside? The heat and humidity are a full-on assault.

Years ago, I would’ve eaten it up. At 35, I was all energy – chasing the buzz, collecting achievements, convincing myself that busyness equaled worth. At 45, I was still grinding, still measuring myself by what I did, not who I was. But standing there now, at 56, I felt like an observer in someone else’s movie. The city’s energy is electric, but there’s anxiety humming beneath the surface, too.

The Hustle Capital

If you want to see hustle culture in its final form, go to Dubai. Every corner, every café, every conversation is about closing deals, pitching new ideas, landing the next big thing. It’s the Olympics of status and speed. There’s a sense that if you’re not moving, you’re losing. Everyone’s “on” – even the expats compete to see who’s living the bigger, shinier version of “success.”

It’s infectious, I’ll give it that. I had to check myself more than once – am I missing out? Should I be doing more, pushing harder, chasing after…what, exactly? But I caught myself, too. I’ve changed. The drive that once looked like ambition now sometimes feels like a subtle form of anxiety in disguise.

The Shift: What I Noticed About Myself

A week in this relentless environment left no doubt: I’ve opted out of the rat race. There was a time when I needed the chaos. I lived for the adrenaline rush, the endless to-do list, the validation that came from always having something “big” in the works.

After I stepped away from the CEO treadmill, sold my company, and finally gave myself permission to design my own days, I realized how much all that hustle had actually cost me: time with the people I love, clarity, peace, and genuine fulfillment. You can fill your calendar and still feel empty.

Now, I’m far more interested in depth over motion. I want to learn for the sake of learning, not just for the next LinkedIn brag. I want to spend afternoons practicing drums, reading, or walking – not chasing after whatever comes next.

Dubai made me face a simple truth: it wasn’t the grind that made me successful. It’s what I gained after I walked away from it.

Redefining Success – On My Own Terms

Dubai is the global headquarters for “more” – money, status, luxury. But after living it, and walking away from it, I can say with certainty: More is not better. Better is better.

My version of “winning” today?

• Waking up when I’m ready, reading something that actually stretches my brain.
• Prioritizing my health and moving my body because it feels good, not because it’s on my to-do list.
• Diving into new skills (even if I’m mediocre at them for a while).
• Taking my time over coffee with Michelle, instead of rushing into the next “important” thing.
• Having the guts to say “no” to things that don’t really matter to me.

I’ve been spending time with Marcus Aurelius and Stoic philosophy. The main lesson: focus on what you can control, and don’t waste your life performing for other people’s approval. In Dubai, you see exactly what happens when everyone’s playing by someone else’s scoreboard. It’s dazzling, but honestly, it looks exhausting.

Do I still like nice things, travel, ambition? Of course. But now it has to mean something to me, not just look impressive on Instagram. I’d rather feel rich than look rich – and there’s a massive difference.

The Real Flex

So here’s the question the Dubai hustle culture forced me to wrestle with, and maybe it’s a good one for you too:

Where in your life are you chasing “more” just because it’s what everyone else wants? When’s the last time you asked if it’s actually better, not just bigger?

You don’t need to buy a one-way ticket to Dubai – or fill your driveway with sports cars – to play the status game. Most of us are doing it unconsciously, whether it’s in business, health, relationships, or even our travel choices.

Here’s the counterintuitive truth: sometimes, the smartest move isn’t to push harder, but to slow down. Maybe the next level isn’t about flexing, but about appreciating what’s already good.

That’s not giving up. That’s what real ambition looks like after you’ve seen the other side.

Ready to talk about what “better” actually means for you? Let’s connect.
Book a call with me

The post The Mirage of More: Dubai, Ambition, and What Really Matters appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

A few weeks ago, I got back from drum camp – equal parts humbling and motivating, like always. I wrote about the experience here. My campmate Stephen read the blog. Then he sent me a book.

It was Mastery by George Leonard. Short book. Big impact. It’s basically a manifesto for anyone trying to get better at anything – drumming, business, health, anything, you name it.

One section stopped me cold.

Leonard describes a type of person he calls The Hacker. Someone who picks up a new skill, gets decent, then just…coasts. Doesn’t push further. Avoids the discomfort of being a beginner again. Doesn’t want to do the reps when the novelty wears off.

And yeah – that’s me. That’s been me. Not always, but more often than I’d like to admit.

Take drumming, for example. I took lessons, got good enough to join a jam band, even played a few gigs in some dive bars in Manhattan. But I never got good good. Because I didn’t put in the reps. I skipped the grind. I ignored the rudiments and just jammed to my favorite ’80s tunes. At drum camp, it shows – fast. You can immediately tell who’s done their homework and who’s just coasted. And let’s just say…it was clear which camp I was in.

Two Things Can Be True

Here’s the thing: I haven’t coasted through life. In fact, in business and investing, I’ve been on the mastery path for decades.

I’ve put in the hours (the years, really) building, optimizing, refining. I’ve stayed with businesses through the boring, unglamorous middle. I’ve seen the compounding returns of long-term thinking. I’ve felt what it’s like to suck at something, then grind through the plateau and emerge on the other side sharper and stronger. That’s where I’ve thrived.

So this isn’t some sweeping self-criticism. It’s not black and white.

People love to sort themselves into neat little categories: “I’m a grinder,” “I’m a dabbler,” “I’m all in or not at all.” But that’s nonsense. The truth is, you can be on the path of mastery in one domain and a total hacker in another. That was my blind spot.

I brought a mastery mindset to my companies – but not to the drum kit. I treated practicing like a hobby, not a craft. I expected results without reps. And that mismatch finally caught up with me.

The Shift to Mastery

These days, I show up differently.

I practice the boring drum stuff daily – the rudiments, stick control, clean strokes. Most days, it feels like I’m not making any progress at all. But then something shifts. Out of nowhere, I realize I can now play clean single strokes at 110 bpm – when just a month ago, 90 bpm felt like a struggle. That didn’t come from a breakthrough. It came from the grind. Quiet, unremarkable, and consistent.

I’ve started applying the same principle to my fitness routine. I’m not chasing PRs or looking for six-week transformations. I’m chasing the next rep. The next clean movement. The next day I show up. Small, steady gains. No fireworks. No dopamine hits. Just the work. And it’s working.

What I have learned is that consistency beats intensity. Every time.

“The plateau isn’t where progress dies. It’s where mastery is born.”

This Is the Work

If you’re feeling stuck right now – if you’re in the middle of something that used to feel exciting but now just feels flat – I want to offer a different take:

That might not be a problem. That might be proof you’re doing it right.

The plateau isn’t where progress dies. It’s where mastery is born. The reps that feel like they don’t matter? They’re the ones that matter most. And the boring stuff? That’s the stuff that builds you.

The world will keep selling you shortcuts and dopamine hits. But mastery? It’s slow. It’s quiet. It’s earned.

So if you’re not seeing the payoff yet, don’t quit. Don’t coast. Don’t jump to the next shiny thing. Just stay.

This is the work.

Right Book. Right Time. Right Friend.

After I wrote about drum camp, my campmate Stephen messaged me. He had read my blog, recognized something in it, and mailed me a copy of Mastery by George Leonard. No commentary. Just the book.

That gesture hit harder than any feedback or advice could. It wasn’t just thoughtful – it was accurate. He saw what I hadn’t fully admitted to myself: that I was straddling the line between dabbling and committing. And he gave me the nudge to pick a side.

The book didn’t tell me anything I didn’t already know. It reminded me of what I’d forgotten and what I still needed to do.

So now I keep it on my desk. Not as inspiration, but as a reminder.

A reminder that this isn’t about getting “good.”
It’s about showing up. Doing the reps. Staying on the path.
Even when it’s boring. Especially when it’s boring.

If you’ve read this far, maybe this is your nudge too.

Call to Action

Where are you coasting?
What skill, habit, or pursuit have you been hacking your way through – hoping to improve without putting in the reps?

Name it. Then recommit.
Not to intensity. To consistency. That’s the real flex.

If you’re a founder who’s ready to stop hacking and start mastering, let’s talk.
Book a call with me here →

The post The Hacker in Me appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

It sounds ridiculous until you realize this is exactly what most successful people stop doing – and why they eventually plateau.

Once a year, I travel to Folsom, California and go to a five-day drum camp hosted by Mike Johnston – one of the most gifted, passionate educators in the drumming world (and a really nice human being, too). Eight drummers. One house. Zero hiding. It’s brutal. It’s 5 days of humble pie. Also, it’s one of the most rewarding and growth-packed things I do all year.

This isn’t some jam-band vacation. It’s five days of nonstop failure – botched fills, seemingly impossible independence drills, and the kind of caring feedback that makes you question whether you’ve ever touched a drum before. And I keep going back.

Why do I do it?

Because this is the environment I wish more CEOs, founders, and leaders forced themselves into.

Let me explain.

Lesson 1: If You’re Not Sucking, You’re Not Growing

Most leaders unconsciously build lives that protect them from ever feeling like a novice again. They surround themselves with validation, avoid discomfort, and outsource difficulty.

At drum camp, there’s nowhere to hide. You’re on the kit in front of everyone, botching bar after bar of some advanced ghost note groove while the others cheer you on for surviving 10 seconds in tempo.

And then come the nightly sheds – the most terrifying part. You get on stage, pick a song you’ve likely never heard, and have to drum along live in front of eight other drummers and a livestream of the global drumming community. No rehearsals. No do-overs. Just you, the music, and the sound of your confidence evaporating in real-time.

It’s not about playing well – it’s about daring to suck.

Founder takeaway: If you can’t name the last time you were visibly incompetent at something that mattered to you, you’re stagnating. Adapt and grow, or die like the dinosaurs.

Lesson 2: Tiny Wins Deserve Applause

You watch Mike demonstrate a groove or fill – fluid, effortless, almost meditative – and think, “Okay, I’ve got this.” Then you sit down to play it and your limbs betray you, your timing collapses, and for a second you forget how to breathe.

When someone finally nails it, the room erupts. Not because it was perfect. But because it was progress.

Most companies obsess over moonshots and ignore the micro-victories that actually build momentum. At camp, the culture flips that completely. Every inch forward gets noticed. Every attempt earns respect.

Founder takeaway: Start treating 1% gains like they matter – because they do. Applaud your team’s smallest wins like they’re a Grammy nomination.

Lesson 3: You Need Environments That Push (and Protect) You

Drum camp works because it’s structured, safe, and unforgiving at the same time. There’s no judgment, but Mike doesn’t sugarcoat. It’s a place built for voluntary struggle with built-in support.

Most leaders either live in environments that are too soft (nobody challenges them) or too sharp (political, performative, and unsafe). Neither encourages real growth.

Founder takeaway: Design your environment with intent. Create friction, but pair it with applied and psychological safety.

Lesson 4: Camaraderie Accelerates Growth

The fastest accelerators at camp aren’t necessarily the most talented. They’re the ones most open to peer support, to feedback, to pushing each other with zero ego.

I’ve seen the same in boardrooms and startups. When the right group dynamics are in place, people move faster because they’re not afraid to fail in front of each other.

Founder takeaway: If your team isn’t hyping each other’s growth, your culture’s broken.

Final Thought: Growth Is a Skill, Not a Stage

I’m not going to become a professional drummer. That’s not the point. I go to drum camp to remember how to learn (and have a boatload of fun with really cool people). To practice being bad at something. To put myself back in the mindset of “I don’t know how – yet.”

It’s easy to coast once you’ve had a few wins. Easy to tell yourself that challenge is for the young and hungry. But mastery is a lifelong practice. The moment you think you’re done, you’re already decaying.

Suck. Struggle. Repeat.
That’s where the real growth lives. And I’m here for it.

? What This Means For You

You don’t have to be a drummer to make sense of this:

• Identify one thing that makes you feel like a beginner – and run toward it.
• Build feedback-rich environments where failure is normalized, not punished.
• Ditch the solo grind. Surround yourself with peers who cheer your effort, not just your outcomes.
• If you’re too comfortable, you’re probably falling behind.

? What This Has to Do With CEO Coaching

The same mindset I bring to drum camp is what I bring to my coaching clients:
Blunt honesty, relentless feedback, and a no-bullshit environment built for growth.

I don’t coddle founders, I challenge them. I help them design better environments, make sharper decisions, and show up like leaders who are still learning – because the best ones always are.

Whether you’re scaling your company, preparing for exit, or rebuilding after burnout – what you really need is a space that stretches you.

I’ve built that. You can join it – if you’re ready.

→ Schedule an intro call

Image © 2025 Mike Johnston

The post Suck. Struggle. Repeat: What Drum Camp Taught Me About Growth as a Former CEO appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

Most people treat LinkedIn like a Rolodex – collecting connections, chasing vanity metrics, and hoping “reach” translates into real opportunity. I did the exact opposite. One afternoon, I exported every single connection – 3,800 in total – and handed the list to ChatGPT with one simple mission: ruthlessly separate the signal from the noise. The result? I deleted over 3,000 connections in under eight hours and gained more clarity (and relief) than any “networking event” ever delivered.

The Problem: A Network That No Longer Served Me

For two decades I lived by the creed “your network is your net worth.” As founder of an SAP training business, coach, advisor, and investor, I collected thousands of contacts – former clients, SAP consultants, conference acquaintances, recruiters, opportunists, and perfect strangers alike. But my career has evolved:

• SAP training is behind me and I am not looking back.
• My new focus areas include coaching other tech entrepreneurs, nano-PE investing, contemporary art and global lifestyle ventures.
• My feed was flooded with irrelevant posts: entry-level job openings, random sales pitches, and memories of deals I’d long since closed.

I wasn’t curating an asset. I had built a digital graveyard.

The Catalyst: A Desire for Radical Reinvention

I realized that if I wanted my LinkedIn to reflect who I am today, I needed a clean break. This wasn’t a cosmetic spring-clean; it was a radical digital rebirth. But manually auditing 3,800 profiles? No founder has time for that. I needed scalpel-sharp objectivity and speed. So I did what any good AI entrepreneur would have done: asked ChatGPT to help with this endeavor.

The Playbook: AI-Powered Purge

1. Export & Ingest
   I downloaded my Connections export (CSV).
2. Prompt ChatGPT
   I asked: “Based on everything you know about me, audit this list and flag anyone I’d never call about a serious investment deal or founder-to-founder coaching. Filter out legacy SAP contacts, random recruiters and sales reps, people whose names I don’t recognize, and low-impact roles.”
3. Define the Filter
   My brutal litmus test:
   • Would I pick up if they called me? Would I even recognize their name?
   • Would they answer if I called them?
     If the answer was “no,” they didn’t make the cut.
4. Review & Approve
   ChatGPT returned a list of ~3,200 names. I scanned for obvious false positives, colleagues, friends & family, made a handful of manual keeps, and finalized the purge list.
5. Automate the Kill
   Using a bulk-remove tool called Phantombuster, I deleted all flagged connections in one long afternoon. After the culling I went in and manually pruned a few more contacts.

The Purge: What Really Happened

• 3,200+ connections removed (≈ 85% of my list). Just over 400 contacts left now and I know every single one of them personally.
• Time spent: Less than 8 hours total (exporting, prompting, reviewing, bulk-removal).
• Emotional curve:
  • Guilt & hesitation at hitting “remove,” even for names I’d never recognize.
  • Surprise when zero people noticed.
  • Relief and pleasant surprise as my feed cleared within minutes.

Immediate Aftermath: A Sharper Feed

• Silence, then clarity. My timeline went from chaotic noise to a curated stream of posts from mentors, co-investors, active founders, and real friends and cherished colleagues.
• Relevance reboot. Industry insights, deal announcements, and art-world news – no more generic “sales tips” or “apply now” blasts.
• Engagement spike. Comments and meaningful DMs surged (since every interaction now came from someone who actually knows me or my work).

Unexpected Wins

• Better mental focus. I reclaimed 10–15 minutes daily that I’d spent scrolling past irrelevant posts.
• Higher signal-to-noise. I now spot true opportunities – introductions, partnerships, co-investment pitches – without having to scroll through the rubbish bin of LinkedIn posts.
• Rebooted confidence. A leaner network reminded me that quality always beats quantity.

Key Takeaways

1. Curate, don’t hoard. Your network should serve a purpose – fueling your current goals – not inflating a vanity metric.
2. Let AI do the heavy lifting. Objective, data-driven filters cut through bias and nostalgia.
3. Embrace digital minimalism. Sometimes the simplest reset – deleting 80% of your connections – yields the biggest gains.
4. Your goals will change over time, just like mine did. When that happens, your network should change accordingly.

Your Turn

Is your LinkedIn network a strategic asset – or an emotional anchor to the past? If you’re drowning in noise:

• Ask yourself: Would you really call these people tomorrow? Would they answer your call or email? Do I even know these people?
• Consider AI: Use it to pinpoint your true allies.
• Take action: The only thing you’ll lose is clutter, and your next opportunity might be waiting in the new silence.

Want my exact prompts and tool recommendations?

DM me for the full playbook. In my next post, I’ll share the real-world opportunities and mindset shifts that followed my network purge – and how less truly became more. Stay tuned.

The post ChatGPT Audited My LinkedIn – and I Deleted 3,000 Connections in One Afternoon appeared first on Thomas Michael - Founder Coach & Strategic Advisor.

Jobs Most Likely to Disappear

Advances in artificial intelligence are expected to eliminate many routine jobs within the next 10 years. Roles that involve repetitive, predictable tasks are at highest risk of early automation (What Jobs Will AI Replace by 2030? – Hypotenuse AI). Several job categories stand out as the first likely to disappear or shrink significantly due to AI:

• Clerical and Administrative Workers – Office support roles are projected to decline sharply. Data entry clerks, administrative assistants, executive secretaries, and other clerical staff face replacement by AI-driven software (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum). For example, automation of data processing means tasks like form entry, bookkeeping, and scheduling can be done faster by algorithms, reducing demand for human assistants (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum).
• Retail Cashiers and Ticket Clerks – Checkout automation and self-service technologies are already cutting into these jobs. Cashiers, ticket clerks, and similar point-of-sale roles are among those expected to see large declines by 2030 (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum). AI-powered kiosks and computer vision systems (as seen in self-checkout or “grab-and-go” stores) can handle many transactions without human cashiers.
• Bank Tellers and Postal Clerks – Routine service jobs in banking and mail handling are rapidly being digitized. The fastest-declining roles in coming years include bank tellers and postal service clerks (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum). Online banking, ATMs, and automated sorting systems can perform much of the work these workers once did. Indeed, these roles are specifically forecast to decline by 2030 according to the World Economic Forum (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum).
• Manufacturing and Assembly Line Workers – Factory automation using robots has been replacing assembly and production jobs for years, and this trend will continue. By 2030, up to 20 million manufacturing jobs worldwide could be lost to robots and AI-driven machines (Robots will kill 20m manufacturing jobs by 2030). Robots excel at repetitive assembly, welding, packing, and warehouse tasks, directly substituting for human labor. Many low-skill, repetitive production and warehouse roles are thus likely to vanish as AI-enabled robotics become cheaper and more capable (Robots will kill 20m manufacturing jobs by 2030) (What Jobs Will AI Replace by 2030? – Hypotenuse AI).
• Customer Service and Telemarketing – AI chatbots and voice assistants are automating customer support. Call center agents, telemarketers, and customer service representatives are at high risk of displacement as natural language processing lets machines handle basic inquiries and sales calls (What Jobs Will AI Replace by 2030? – Hypotenuse AI). Speech recognition and generative AI systems can already resolve common customer requests, potentially eliminating large numbers of entry-level service jobs.
• Routine White-Collar Jobs – It’s not only blue-collar work; AI will also target repetitive tasks in white-collar occupations. Clerical data processing roles in finance and law, such as accounting clerks, paralegals, and back-office staff, are vulnerable to automation (Jobs of the future: Jobs lost, jobs gained | McKinsey). Machine learning systems can process invoices, review contracts, or perform document analysis more efficiently, reducing the need for junior office workers. Even some junior programming and IT roles could be automated by AI code generators and agentic AI, which handle coding tasks that used to require entry-level developers (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?).
• Transportation and Delivery Drivers – While full autonomy may take time, strides in self-driving vehicles and delivery robots suggest that roles like truck drivers, taxi drivers, and couriers could begin to decline toward the end of the decade. One study estimates that automated trucks alone could reduce the demand for human drivers by 50–70% in the US and Europe by 2030, potentially making up to 4.4 million trucking jobs redundant (Driverless Trucks: New Report Maps Out Global Action on Driver Jobs and Legal Issues | ITF). Even if adoption is gradual, driverless technology is expected to steadily erode employment in freight transport and logistics.

In summary, jobs composed of routine manual or cognitive tasks – from factory work and retail checkout to basic administrative and support duties – are the ones most immediately threatened by AI-driven automation (What Jobs Will AI Replace by 2030? – Hypotenuse AI). In contrast, roles that are non-repetitive, unpredictable, or require a human touch (creativity, empathy, complex judgment) are relatively safer in the near term (Robots will kill 20m manufacturing jobs by 2030). But even those jobs may be redefined rather than completely safe, as AI takes over sub-tasks and augments human workers instead of outright replacing them.

Industries and Demographics Most Impacted

The impact of AI will not be uniform – certain industries and groups of workers will feel the disruption sooner and more deeply than others. Key factors include the nature of the work (routine vs. non-routine), skill levels required, and geographic and economic conditions.

Industries poised for early and significant AI disruption include:

• Manufacturing and Warehousing: As noted, industrial automation is set to eliminate millions of jobs in factories and warehouses (Robots will kill 20m manufacturing jobs by 2030). Industries with assembly lines or repetitive production processes (automotive, electronics, textiles, etc.) will see substantial job losses. Regions heavily dependent on manufacturing may be hit hard – for instance, many rural and small-town communities that host factories could relive the economic pain of past industrial automation waves (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty). A report by Oxford Economics warns that poorer regions with lower-skilled workforces are most vulnerable to robot-driven manufacturing job loss (Robots will kill 20m manufacturing jobs by 2030). This suggests that areas with less diverse economies and a high share of routine factory jobs (for example, parts of the U.S. Midwest or industrial hubs in developing countries) will experience disproportionate displacement.
• Retail and Food Service: The retail sector (stores, supermarkets) and fast-food/restaurants are adopting self-service kiosks, AI-driven inventory management, and even robotic kitchen equipment. This could rapidly reduce demand for roles like cashiers, sales attendants, and fast-food preparers. Large retail chains are already experimenting with cashier-less stores and automated order-taking. Food service jobs involving simple, repetitive preparation may be among the first to be automated in that industry (e.g. robotic burger flippers or beverage dispensers), though customer-facing roles may persist longer for their human element.
• Transportation and Logistics: Trucking, ride-hailing, and delivery services stand to be disrupted by autonomous vehicles and delivery drones/robots. Long-haul trucking in particular is a large occupation in many countries (e.g. truck driver is a top job for non-college-educated men in the U.S.), so automation here could have wide impact. If self-driving tech matures by the 2030s, professional drivers could face massive layoffs – up to 50–70% of driver jobs in advanced economies might disappear in that scenario (Driverless Trucks: New Report Maps Out Global Action on Driver Jobs and Legal Issues | ITF). Related logistics jobs, like warehouse pickers or forklift operators, are also threatened by AI-guided machines. The shipping and delivery industry (postal workers, couriers) will likewise automate package sorting and last-mile delivery where possible, continuing a trend of declining postal service employment (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum).
• Finance, Accounting, and Law: White-collar industries that involve processing large amounts of data or paperwork are increasingly using AI. For example, banks and insurance companies can use AI for loan processing, fraud detection, and customer service, which may reduce roles in back-office operations and call centers. Accounting and bookkeeping tasks can be handled by intelligent software that automates entries and reconciliations. In the legal field, AI document review tools can perform contract analysis or e-discovery, potentially reducing the need for paralegals and junior lawyers for those tasks (Jobs of the future: Jobs lost, jobs gained | McKinsey). These industries won’t vanish, but entry-level and routine support roles within them are at risk of shrinking.
• Customer Service and Support: Many industries (from e-commerce to telecom) rely on large customer support teams. AI chatbots and virtual assistants can handle basic inquiries, troubleshooting, and FAQs, enabling one agent to oversee multiple AI interactions. This efficiency means fewer human service reps might be needed in sectors like tech support, banking customer service, airline reservations, etc. (What Jobs Will AI Replace by 2030? – Hypotenuse AI). The call center industry, which employs millions globally (particularly in countries like India and the Philippines for outsourcing), could see a decline as AI takes over frontline customer interaction.
• Technology Sector (Entry-Level Roles): Paradoxically, even the tech industry itself will see AI automation. Tools like generative AI coding assistants mean that junior programming and IT jobs could be reduced (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?). One analysis points out that AI “agents” can handle basic coding tasks, which might displace junior developers and make senior engineers far more productive (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?). So while tech will create many AI-related jobs, it may simultaneously cut some traditional programming roles. The net effect is that even well-educated, skilled workers in tech hubs need to adapt continuously – their jobs are not completely immune to automation of repetitive aspects of coding or testing.

In terms of worker demographics, those most affected by AI-driven job losses will likely be:

• Lower-Skilled and Less-Educated Workers: People with lower levels of formal education are over-represented in the routine jobs most at risk (Jobs of the future: Jobs lost, jobs gained | McKinsey). Automation threat is highest for roles that don’t require advanced degrees – think of manufacturing operatives, clerical workers, retail clerks, drivers, etc. A U.S. government analysis found that workers with a high school education or less, performing routine tasks, face the greatest exposure to automation (Which Workers Are the Most Affected by Automation and … – GAO). Conversely, highly educated workers in roles requiring complex problem-solving or social intelligence face lower immediate risk. Education thus serves as a buffer: for instance, one study showed that holding a bachelor’s degree dramatically lowers a worker’s automation risk compared to someone with only a high school degree ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ) ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ).
• Workers in Lower-Wage Positions: There is a correlation between lower wages and higher automation susceptibility, partly because if a job is low-paid, it’s often a sign the work is low-skill and can be codified. Also, employers have strong incentive to automate to save labor costs when wages rise. Many lower-wage service jobs (cleaning, food preparation, basic admin) are on the cusp of automation through AI or robotics. However, it’s worth noting a paradox: in very low-wage regions or countries, the incentive to invest in automation is weaker (since human labor is cheap). This means the pace of job loss to AI might be slower in some developing economies compared to advanced economies. Indeed, McKinsey research suggests a larger share of the workforce will require retraining in wealthy countries than in developing ones, because automation adoption will be faster where labor is expensive. Up to one-third of workers in the U.S. and Germany, and nearly half in Japan, may need to transition to new jobs by 2030, compared to a smaller fraction in emerging economies (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute).
• Certain Age Groups: Older workers nearing retirement may be disproportionately affected for two reasons. First, they are often employed in roles vulnerable to automation (e.g. an older factory worker doing repetitive tasks). Second, they may find it more difficult to upskill or switch careers at a late stage. Younger workers might adapt more easily or have skills in tech, whereas older employees in declining jobs (like truck driving or assembly work) could struggle to find new employment. This dynamic could lead to earlier-than-planned retirements or long-term unemployment for some older workers, whereas younger entrants face a changing job landscape but can be trained for emerging roles. That said, young people can also be vulnerable if entry-level positions (their typical career starting points) are cut off by AI – for example, it’s harder to “get your foot in the door” as a bank teller or junior accountant if those jobs are largely automated by 2030.
• Racial and Ethnic Minorities (in some countries): Job automation risk can vary along racial/ethnic lines due to occupational patterns. In the United States, for instance, Black, Hispanic, and Native American workers (especially men) are statistically more likely to hold automatable jobs than white workers. A recent analysis found that, holding other factors constant, Black, Hispanic, and Native American males face higher automation risks (5.8%, 3.9%, and 2.8% higher respectively) than white males ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ). This is because these groups are often overrepresented in manufacturing, transportation, and low-wage service roles. Without interventions, AI could thus widen economic inequalities among demographic groups ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ) ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ). Women in aggregate may face slightly less automation risk than men because more women work in education, healthcare, or other roles requiring social skills that are harder to automate ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ). However, certain groups of women (e.g. Hispanic and Asian women in the U.S.) also face above-average risk ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ), and globally, any worker in a routine job is vulnerable regardless of gender.
• Geographical Disparities: Different regions will experience AI’s impact at different times. High-tech urban centers and advanced economies are adopting AI fastest, which means major cities might see white-collar job disruption sooner than expected. Notably, the rise of generative AI could affect a lot of knowledge work concentrated in cities. A Brookings Institution analysis indicates this wave of AI will hit large metropolitan areas that rely on white-collar industries the most (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty). For example, tech hubs (Silicon Valley, Seattle), financial centers (New York, London), and other big cities have a high share of jobs (like software coding, marketing, legal research) that generative AI can partially automate (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty). This is a contrast to earlier automation eras which devastated primarily industrial towns and rural communities (e.g. the decline of coal mining or steel mills hurt small towns) (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty). Those manufacturing-centric regions will still be affected by robotics, but now in addition, AI may squeeze employment in service-sector and professional occupations in the cities. On a global scale, countries with aging populations and high labor costs (Japan, South Korea, parts of Europe) are aggressively pursuing automation to fill labor shortages, which could make them early adopters of AI in the workforce. Meanwhile, countries with abundant cheap labor might see a slower uptake, delaying the impact on jobs. Even within one country, regional economies that cannot attract new industries may suffer prolonged unemployment, whereas dynamic regions could create new jobs to offset losses. This uneven geography of AI disruption means policymakers will have to tailor responses to local conditions – what works to help a Rust Belt town might differ from what a big city needs.

In summary, sectors with routine tasks (manufacturing, retail, transport, clerical work) will bear the brunt of early AI automation, and the workers most impacted will be those with less education, lower incomes, and those in regions or communities that rely on at-risk industries. However, unlike past automation which mostly hit blue-collar jobs, this AI revolution will also encroach on white-collar professions in tech and services (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute). Virtually every occupation will be touched in some way – the scope of AI is broader than previous waves, reaching both the factory floor and the office cubicle. This broad reach is why the coming decade could bring simultaneous disruptions across diverse job types, challenging many different groups of workers.

Challenges for Displaced Workers

As AI displaces jobs, a crucial question arises: what happens to the workers who are automated out of work, especially those who cannot easily retrain for new positions? The transition will not be easy for many. While some workers will successfully upskill or change careers, others – due to skill mismatch, age, or limited opportunities – will struggle to find a foothold in the new job market.

Studies suggest a significant share of workers might fall into this hard-hit category. For example, a recent analysis of the United Arab Emirates (which is rapidly automating) found that about 10% of the workforce could become entirely redundant, unable to be upskilled for future roles (56% of current jobs in UAE will undergo substantial change in next 5 years: WEF report – Aletihad News Center). In that scenario, 10% of workers would effectively be left without relevant jobs to transition into. Globally, we could see a similar pattern where a certain fraction of displaced workers are not readily absorbable into new jobs, even as other workers do retrain.

Displaced workers who cannot be upskilled face serious risks to their financial stability. Historically, when industries collapsed (such as coal mining or manufacturing in various regions), many displaced workers experienced long-term unemployment or left the labor force altogether. Some ended up relying on social assistance or disability benefits when no new jobs materialized. We may see a repeat of these trends with AI-related displacement, absent strong interventions.

Likely outcomes for these individuals include:

• Prolonged Unemployment or Underemployment: Workers whose jobs vanish may spend months or years looking for new work. If they lack the advanced skills that growing industries demand (like tech or healthcare skills), they may only find part-time gigs or sporadic contract work. For instance, a factory worker replaced by robots might only find a low-paying service job, if anything. This can lead to underemployment (working fewer hours than desired or in roles far below one’s experience level) and income loss.
• Early Retirement or Workforce Exit: Older workers in particular might simply exit the workforce if retraining proves too difficult. An assembly-line worker in their late 50s might decide to retire early (if financially feasible) rather than start a new career from scratch. Others may drop out of the labor force in frustration after repeated unsuccessful job hunts, even if they haven’t reached retirement age. This shrinkage of the labor force was observed in some regions hit by automation in the past, and could happen on a larger scale with AI.
• Reliance on Social Safety Nets: Those unable to secure new employment will likely need to rely on government support or family networks. Unemployment insurance, welfare benefits, or disability insurance claims could rise as more people find themselves without work. In regions with minimal safety nets, this situation could lead to increased poverty and hardship. In better-protected economies, it will put pressure on the social support systems to expand. During the COVID-19 pandemic, many governments provided emergency income support (stimulus checks, furlough payments, etc.), which demonstrated how direct financial assistance can help individuals through sudden job loss (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute). We may see similar large-scale assistance programs for AI-driven unemployment if the problem becomes acute.
• Career Downgrading to “Last-Resort” Jobs: Some displaced workers might take jobs in areas that are harder to automate but often low-paying, as a last resort. For example, roles in elderly care, childcare, or other personal services are not easily done by AI (due to the human touch required), so they may still be abundant. A laid-off warehouse worker might retrain minimally to become a home health aide or a landscaping laborer. While this provides some income, it often comes with a pay cut and possibly tougher working conditions. Essentially, we could see a migration of workers from middling industrial or clerical jobs to lower-wage service jobs that survive – a form of downward mobility if no better options exist.
• Informal and Gig Work: In the absence of stable jobs, many may turn to the gig economy or informal work to make ends meet. This could include gig driving (if vehicles aren’t fully autonomous yet), freelance manual tasks, day labor, or online micro-tasks. Gig platforms (like delivery apps, freelancing sites) might see an influx of labor. However, these gigs typically lack benefits and security, leaving workers in a precarious position financially. It’s essentially a fallback rather than a solid long-term career – a way to generate some income if traditional employment isn’t available.

The psychological and social toll on these displaced individuals shouldn’t be overlooked. Long-term unemployment or underemployment can lead to stress, loss of self-worth, and community decline in areas with concentrated job losses. Past examples (such as former industrial towns) show spikes in problems like depression, substance abuse, or other social ills when good jobs vanish en masse. Society may need to support not just the financial, but also the emotional well-being of those who find themselves without work in an AI-transformed economy.

Crucially, the fate of workers who cannot be upskilled will depend heavily on policy responses and support systems. With the right measures (discussed next), governments and communities can provide alternative pathways or safety nets. Without such support, we risk a scenario where millions of people languish without stable incomes – a serious social and economic challenge. The next section explores what can be done to address this, including ideas like universal basic income and new job creation models to catch those left behind.

Policy Responses for Large-Scale Unemployment

To mitigate the impacts of AI-induced job losses, a range of policy responses and alternative economic models are being proposed. The goal of these interventions is to ensure that workers who lose their jobs to automation can still maintain financial stability and that society can adapt to a future with possibly less human labor demand. Here are several key strategies under discussion:

• Universal Basic Income (UBI): UBI is one of the most widely discussed solutions for supporting people in an era of automation. Under a UBI, the government provides regular, unconditional cash payments to all individuals, regardless of employment status. This would guarantee a baseline income floor even if one is out of work. Proponents argue UBI could be a vital safety net for those displaced by AI, giving them financial security when jobs are scarce (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute) (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?). In practice, UBI pilots (such as trials in Finland and some U.S. cities) have shown improved well-being for recipients, though funding a permanent UBI at scale is challenging. Some experts suggest financing UBI through taxes on automation – for example, taxing companies that heavily utilize AI and robots, and using those funds to pay for the basic income (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?). This way, the productivity gains from AI would be partially redistributed to the public. While UBI won’t create jobs, it would at least ensure no one is left penniless due to tech unemployment, and it could support people while they retrain or pursue other endeavors.
• Retraining and Lifelong Learning Programs: A classic response to technological disruption is investment in education and training. Governments and businesses can ramp up programs to reskill workers for new careers in growing fields (for example, training laid-off factory workers to become solar panel installers or coders). Continuous upskilling will be critical as the job market evolves – the World Economic Forum estimates 44% of workers’ skills will need updating within just five years (4 ways to achieve a smooth transition to the digital economy | World Economic Forum) (4 ways to achieve a smooth transition to the digital economy | World Economic Forum). Effective retraining can help some displaced workers move into emerging jobs that AI is creating (like data analysts, AI maintenance technicians, or care economy jobs that are increasing in demand). However, retraining has limits – not everyone can easily jump into a high-tech job, and it requires time and support. Thus, training must be paired with other safety nets for those who struggle to transition. Still, making education more accessible, flexible, and aligned with future skills is a core piece of most policy frameworks for the future of work.
• Shorter Workweeks and Job Sharing: Another approach to fewer jobs is to redistribute work among more people. The idea is that if AI boosts productivity, society could afford to have humans work less. For example, moving to a four-day workweek (32 hours) with no pay cut has been proposed and even trialed in some companies/countries. By reducing working hours, employers could avoid layoffs and instead have the existing work spread across existing staff or new hires. Historically, working time reduction has been used to reduce unemployment by distributing available work (We Need Five Days’ Pay for Four Days’ Work). In the AI era, a 4-day week or 6-hour day could become more common, supported by productivity gains from automation (A 4-Day Workweek? AI-Fueled Efficiencies Could Make It Happen). This would give workers more leisure/family time and maintain employment levels (albeit each working a bit less). Policy can encourage this through incentives or even regulations (for instance, lowering the standard full-time hours). Job sharing arrangements (where two people split one full-time job’s duties and pay) are another mechanism. These models require a cultural shift and buy-in from employers, but if successful, they can mitigate mass layoffs by simply having everyone work a little less instead of some people not at all.
• Public Employment and Job Guarantees: Governments might directly create jobs for those left behind by the private sector. A job guarantee program would mean the government offers a public service job to anyone who wants one, ensuring full employment. These jobs could be in infrastructure projects, environmental conservation, community care, education support, etc. – tasks that improve society but are underprovided by the market. By implementing a job guarantee, even if AI shrinks private employment, people could still work (and earn) in public initiatives. This was conceptually similar to programs in the past like the New Deal’s public works or public employment schemes during recessions. It ensures no one willing to work is idle. However, it requires government funding and organization on a large scale, and the jobs must be meaningful and not displace other workers.
• Strengthening the Social Safety Net: Aside from UBI, there are more traditional measures to help the unemployed. Expanded unemployment insurance, longer duration of benefits, and more generous welfare programs can cushion the blow of job loss. Subsidized healthcare (decoupling it from employment, as losing a job also often means losing health insurance in some countries) is another important aspect – ensuring people don’t lose access to essentials when they lose work. Some propose wage insurance – if a worker has to take a lower-paying job after displacement, the government could temporarily pay the difference to soften income loss. Portable benefits frameworks are also suggested, so gig workers or freelancers (who may form a larger share of the workforce) can have retirement and health benefits that aren’t tied to a single employer. In short, modernizing labor laws and the safety net to fit a world with more frequent job changes or periods out of work is key.
• Incentivizing New Job Creation: Policymakers can encourage sectors that are likely to grow (and are labor-intensive) to create new employment opportunities. For instance, the green economy (renewable energy, retrofitting buildings, climate resilience projects) could generate many jobs that are harder to automate, effectively absorbing displaced workers. Care industries (healthcare, elder care, childcare, education) are expected to grow due to aging populations and human services demand – these fields rely on empathy and human contact, so they can employ people who leave more routine jobs. Governments can subsidize these sectors or provide grants/tax breaks for businesses that create jobs in them. Additionally, supporting entrepreneurship and small businesses can help – if large corporations are automating, perhaps individuals can create their own jobs through startups, crafts, or local services. Removing barriers to starting a business and providing capital to underrepresented groups can channel some displaced workers into self-employment ventures.
• “Robot Tax” or Automation Dividend: A more radical policy idea is to explicitly tax automation. This could mean, for example, a company has to pay a fee for every robot or AI system it deploys that replaces a human worker (as once suggested by Bill Gates). The rationale is to slow down automation where it’s done purely to save costs without societal benefit, and to generate revenue that can fund retraining or UBI. Another concept is an “AI dividend” – if AI increases productivity and profits, a portion of those gains could be distributed to citizens (perhaps as a sovereign wealth fund or public dividend). This ensures the wealth created by AI doesn’t just accrue to shareholders and tech owners, but is shared broadly, compensating for job losses. Such policies are still speculative and would be complex to implement (we’d have to define which technologies get taxed and how to measure displacement), but they reflect the growing conversation around ensuring the benefits of AI are widely shared.
• Regulating the Pace of Automation: Some have suggested policies to manage how fast AI is adopted in workplaces, to avoid sudden shock. For instance, requiring companies to provide notice and transition plans when implementing AI layoffs, or even having a quota of human workers for certain tasks. The idea of a “permit system” for automation has been floated, where companies might need approval to replace large numbers of workers with machines, allowing society time to adjust (Driverless Trucks: New Report Maps Out Global Action on Driver Jobs and Legal Issues | ITF). An example comes from the transportation sector: a report on driverless trucks recommended considering temporary limits on deployment to give truck drivers time to transition (Driverless Trucks: New Report Maps Out Global Action on Driver Jobs and Legal Issues | ITF). While outright blocking technology is unrealistic long-term, these measures could smooth the transition and ensure we don’t have entire occupations wiped out virtually overnight without preparations in place.

It’s likely that a combination of these strategies will be needed. No single policy is a silver bullet. For instance, UBI can prevent poverty but doesn’t give people purpose or engagement that a job might; job guarantees give work but require big government programs; retraining works for some but not all. Governments might implement UBI or enhanced welfare for immediate relief, invest in education and new industries for long-term adaptation, and encourage work-hour reductions or other labor market innovations to spread the benefits of automation. The common thread is that doing nothing – leaving it entirely to market forces – could lead to extreme inequality and social strain. Thus, proactive policies are crucial as AI reshapes the job landscape.

Adapting to an AI-Driven Economy

The broader question is how governments and societies as a whole will adapt if AI causes large-scale unemployment. History has seen technological revolutions disrupt labor before, but AI’s breadth and speed pose unique challenges. Here are some insights into how adaptation might occur:

1. Rethinking the Value of Work and Leisure: Societal attitudes toward work may need to shift. In many cultures, one’s job is tied to identity and purpose, and the standard expectation is that adults work full-time to “earn a living.” If AI enables an economy where not everyone needs to work to produce the goods and services we need, we might decouple income from traditional employment. Societies might place greater value on leisure, creative pursuits, caregiving, education, and volunteer work as legitimate ways to spend one’s time, supported by mechanisms like UBI. This is a profound cultural change – moving from viewing unemployment as a personal failure to seeing it as a logical outcome of increased productivity. Communities could adapt by providing more opportunities for people to engage in meaningful non-work activities (arts, sports, civic participation) to maintain social cohesion and personal fulfillment even if formal jobs are scarce.

2. Government’s Role as a Safety Net and Facilitator: Governments will likely become more involved in ensuring economic security for citizens. This might mean expanding welfare programs, providing UBI (as discussed), or guaranteeing services like healthcare, housing, and education so that even those without jobs can live decently. During the pandemic, many governments intervened with direct payments and job retention schemes on an unprecedented scale (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute), which could serve as a model for future automation shocks. In addition, governments can facilitate adjustment by tracking the impact of AI on employment and responding quickly. For example, creating an “AI displacement task force” to monitor which sectors are losing jobs and coordinating the response (retraining programs, economic aid to affected regions, etc.). Policymaking might also include incentives for companies to retain workers or redeploy them in new roles rather than simply laying them off – perhaps tax breaks for companies that retrain internal staff for tech roles instead of firing them. The public sector may also lead by example by adopting technology in a way that augments public employees rather than replaces them, showcasing models of human-AI collaboration.

3. Education and Curriculum Overhaul: To prepare the next generation, educational systems will need to adapt to the skills of the future. Schools and universities might emphasize skills that AI can’t easily replicate – creativity, critical thinking, interpersonal communication, and adaptability. Coding and AI literacy could become as fundamental as reading and math, so that people can work alongside AI effectively. We might see a stronger push for STEM education, as well as training in trades that are in demand (like electricians, plumbers, healthcare technicians – many of which are not easily automated). Additionally, the concept of lifelong learning will be ingrained: governments and employers could provide continuous training credits or sabbaticals for workers to re-skill throughout their careers. Societies that create a robust ecosystem for adult education and re-skilling will handle the AI transition better, as workers can more fluidly move into new occupations as old ones decline.

4. Economic Restructuring and New Metrics: In a world with less formal employment, we may need to rethink economic metrics and structures. For instance, today we focus heavily on the unemployment rate as a gauge of economic health. In a future with widespread automation, a low employment-to-population ratio might not mean poverty if wealth is redistributed – but it does mean we need new measures of well-being (such as median income, inequality indices, or even happiness) to guide policy. Economies might shift towards sectors that are human-centric. Some economists argue that rather than a post-work doom scenario, AI could free humans to do more of the work that machines can’t do well – for example, jobs in creative arts, entrepreneurship, research, or personalized services might flourish. The structure of the economy might thus see a smaller traditional labor force, but perhaps a larger number of people in flexible, creative roles supported by the wealth generated from automation. Additionally, there could be greater emphasis on redistribution – through taxes and public services – to ensure the gains from AI lead to general prosperity rather than concentrating in a few hands.

5. Community and Individual Adaptation: On a community level, areas facing job losses will need to reinvent themselves. This has happened in some places through transitioning to new industries (for example, former manufacturing towns attracting logistics centers or tech startups). Local governments might play a role in economic redevelopment initiatives – attracting new businesses, investing in infrastructure, and providing incentives for industries to set up in areas hit by automation layoffs. Individuals, on the other hand, will adapt by possibly having more non-linear career paths. It may become normal for a person to have to switch fields multiple times or spend periods of time in gig work, retraining, or personal projects. Resilience and flexibility will be crucial personal traits. Society might also need to address mental health and identity issues in a world where one’s job is no longer the sole defining feature – meaning counseling, community groups, and purpose-finding programs could help people adjust to new life patterns.

6. Collaboration between Stakeholders: Governments, businesses, and civil society will need to collaborate closely. Businesses should act responsibly by preparing their workforce for changes – many companies are already investing in employee retraining and “future of work” strategies (4 ways to achieve a smooth transition to the digital economy). Public-private partnerships could fund apprenticeship programs in AI-related fields for displaced workers. Labor unions and worker organizations might expand their focus from just protecting current jobs to also helping workers transition (for example, negotiating for severance, retraining funds, or phased automation plans). Some have called for an “Automation Adjustment Assistance” akin to trade adjustment assistance – policies specifically targeted at communities and workers impacted by AI, including job search assistance, relocation support if new jobs are in different regions, and even psychological support.

Ultimately, societies have a choice in how to handle the AI revolution. In an optimistic scenario, automation could lead to a high-productivity economy where people work less but enjoy a high standard of living, supported by the fruits of AI. We would have more time for family, creativity, and community, with machines doing the drudge work. To get there, proactive adaptation is key: investing in people, updating our social contract, and ensuring that the economic gains from AI benefit everyone. In a pessimistic scenario, if we fail to adapt, we could see deepened inequality, with a small group of tech owners prospering while many others are unemployed or stuck in low-wage gigs, leading to social unrest. Governments and societies are beginning to grapple with this challenge now, through various commissions and think-tanks exploring future-of-work policies.

In conclusion, the next decade will be a pivotal time. Many jobs will likely disappear due to AI by 2035, especially routine jobs in sectors like manufacturing, clerical work, retail, and transportation. The industries and demographics hit first will be those already feeling the wave of automation – typically lower-skill roles and regions tied to those jobs – although AI’s reach will also extend into higher-skill domains and urban areas. Workers who can adapt by gaining new skills will move into the jobs of the future, but a significant number who cannot upskill will need robust support systems. To prevent widespread economic hardship, policy interventions such as UBI (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute), reduced workweeks (We Need Five Days’ Pay for Four Days’ Work), targeted retraining, and stronger safety nets will be necessary. Societies might also embrace new models of living where one’s livelihood isn’t strictly dependent on a traditional job. Change on this scale is daunting, but with foresight and collective effort, we can manage the transition. As we’ve learned from past technological upheavals, human resilience and ingenuity — coupled with wise policy — can turn the challenge of automation into an opportunity, ensuring that AI ultimately elevates society rather than divides it.

Sources:

• World Economic Forum, Future of Jobs Report 2025 – projections of job creation vs displacement and roles in decline (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum) (These jobs will disappear fastest by 2030 as AI rises, according to the World Economic Forum).
• McKinsey Global Institute – analysis of automation potential and workforce transitions by 2030 (Jobs of the future: Jobs lost, jobs gained | McKinsey) (Jobs of the future: Jobs lost, jobs gained | McKinsey).
• Oxford Economics – forecast that up to 20 million manufacturing jobs could be lost to robots by 2030 (Robots will kill 20m manufacturing jobs by 2030).
• International Transport Forum – scenario of 50–70% of trucking jobs displaced by self-driving technology by 2030 (Driverless Trucks: New Report Maps Out Global Action on Driver Jobs and Legal Issues | ITF).
• Hypotenuse AI report – notes that low-skill repetitive jobs (data entry, telemarketing, assembly) are highly vulnerable to near-term AI replacement (What Jobs Will AI Replace by 2030? – Hypotenuse AI).
• Brookings Institution – research on geographic and sectoral exposure to AI (finding that generative AI may impact white-collar metro jobs, whereas past automation hit manufacturing towns) (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty) (‘Not your parents’ automation’: How generative AI will impact jobs in major cities – Route Fifty).
• Wiley/Amer. J. of Economics & Sociology – study on automation risk disparities by race and gender in the U.S. (showing higher risk for Black/Hispanic workers in automatable roles) ( What are the effects of workforce automation across race and gender in the United States? | John Wiley & Sons, Inc. ).
• Seven Pillars Institute – discussion on AI displacement and the case for UBI, including McKinsey data on workforce needing transitions (up to one-third in advanced economies) (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute) (AI Job Displacements: UBI to the Rescue? – Seven Pillars Institute).
• USAII (United States Artificial Intelligence Institute) – insights on funding UBI via an “AI automation tax” and the need for rapid policy action to address AI-driven unemployment (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?) (Can Universal Basic Income (UBI) Be A Sustainable Response to The Rise of AI Agents?).
• Jacobin Magazine – argument for a four-day workweek as a way to share work in the age of automation (We Need Five Days’ Pay for Four Days’ Work).
• World Economic Forum – “Unlocking Opportunity” framework emphasizing reskilling, flexible work models, and safety nets for the digital economy (4 ways to achieve a smooth transition to the digital economy | World Economic Forum) (4 ways to achieve a smooth transition to the digital economy | World Economic Forum).
• Various news sources and analyses compiled through 2023-2025 on AI’s impact on jobs and potential solutions (56% of current jobs in UAE will undergo substantial change in next 5 years: WEF report – Aletihad News Center) (What Jobs Will AI Replace by 2030? – Hypotenuse AI).

The post The Next Decade of AI Automation: Disappearing Jobs and Societal Adaptation appeared first on Thomas Michael - Founder Coach & Strategic Advisor.