Surviving AI – Career, Income, and Life Strategy in the Age of Artificial Intelligence

Surviving AI with Carlo Thompson
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Join Carlo Thompson on Surviving AI, the definitive resource for navigating AI job displacement and building a complete career, income, and life strategy for the age of artificial intelligence. This podcast breaks down the AI trends actually affecting jobs and the economy, and delivers practical guidance on skill development, career pivots, geographic positioning, and navigating automation before it navigates you. With expert insights and structured content, listeners are equipped to protect their income and capitalize on the opportunities emerging in the changing economy. Surviving AI delivers: ✓ Early warning signs your job — or industry — is vulnerable ✓ Skills that AI can't replicate (yet) ✓ Career pivots that protect your income ✓ Geographic arbitrage strategies for the AI economy ✓ Real case studies from the automation frontlines ✓ The truth about "AI will create more jobs than it destroys" This is a structured, season-by-season curriculum, not a news recap. Seasons 1–2 cover the foundations: automation risk, protected careers, skilled trades, corporate survival, and business ownership. Season 3 goes deeper into strategic positioning: where to live, how to build a career-proof network, how to read the AI market's financial signals, and how the map of opportunity is being redrawn. For professionals who'd rather adapt than be replaced, regardless of industry. This isn't fear-mongering. It's a wake-up call. Because hope isn't a strategy, but preparation is. New episodes weekly.

  1. 1d ago

    Amazon Cut AI Jobs and Funded 340,000 New Ones. Most People Don't Know They Exist.

    Send us Fan Mail Monday, we asked where the AI infrastructure money went. Today we name the seats it created: 340,000 data center positions sitting open in the US right now, against a total build-out need of roughly 650,000 across construction and operations not a 2030 forecast; open jobs the industry can't fill today. Carlo and Ainsley trace the real career ladder within that number, from entry-level data center technician roles through engineer, MEP, and AI infrastructure specialist roles, and show why Microsoft, Google, AWS, and Meta have all dropped the four-year degree requirement for entry-level technician hiring. Stargate, the Oracle/OpenAI buildout that just added 4.5 gigawatts of capacity and an estimated 100,000+ jobs, becomes the single clearest proof point: a named project, a named partner, workers already on site. The back half goes wider and harder: a "silver tsunami" retirement wave that's pulling out roughly a third of the current technical workforce at the same moment the industry needs them most, a workforce where half of all data centers report women make up less than five percent of staff, and a global build-out where high-income countries hold the overwhelming majority of capacity while the regions with the fastest-growing populations are still years behind and why the physics of latency means that has to change. The through-line from this season: the capital moved, the jobs moved with it, and almost nobody got the memo. Chapters: 00:00 Intro: Picking Up From the $700 Billion Question 00:38 The Real Number: 340,000 Open Seats Right Now 01:51 Does Your Career Port Over? Trades, PMs, and the "Wrong Room" Problem 04:49 Stargate: One Named Project, National Footprint 09:01 Who Actually Gets Hired: The Real Build-Out Labor Force and Salary Ladder 11:38 The Global Picture: Who Gets Left Out 14:24 Physics, Latency, and Why Local Data Centers Have to Exist 16:09 The Silver Tsunami: A Retirement Crisis Hiding Inside the Shortage 18:10 Less Than 5%: Where Are the Women? 20:56 The On-Ramps Nobody Tells You About 23:33 It's Not Just America: The Global Jobs Case 27:02 Structural Exclusion, Not a Pipeline Problem 29:28 Call to Action: Do This Before the Week Is Out 32:09 What's Next: Inside the Machine Subscribe: Apple Podcasts, YouTube, and Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    Amazon Cut AI Jobs and Funded 340,000 New Ones. Most People Don't Know They Exist.

  2. 6d ago

    Amazon's Layoffs Aren't Cost-Cutting. They're a $200 Billion Financing Move.

    Send us Fan Mail The same week Amazon cut jobs on its artificial general intelligence team, it committed $200 billion to AI infrastructure. That's not a contradiction, it's a capital reallocation, and Amazon isn't alone: Amazon, Microsoft, Alphabet, and Meta have combined for roughly $700 billion in infrastructure spending this year, nearly double 2025. Carlo and Ainsley unpack what's actually happening when a company cuts the people building the model while pouring money into the buildings that run it, and why one analyst's reading of these cuts (flagged clearly as interpretation, not Amazon's own words) treats layoffs less like cost-cutting and more like a way to help finance the infrastructure bet itself. The number that matters for anyone watching their own job be affected by this: 340,000 U.S. data center positions sit unfilled right now, projected through the end of this year, including electricians, HVAC technicians, low-voltage cabling technicians, project managers, and facility operations roles. Ainsley names the "wrong room problem", why displaced tech and AI workers almost never hear about this shortage, and why the outplacement firms paid to help them rarely point there either, and walks through the dark-fiber parallel from the late-1990s telecom buildout: the builders went bankrupt, the infrastructure survived, and somebody else built the next thing on top of it for cents on the dollar. Three states, Michigan, Minnesota, and Washington, are quietly tying data center tax breaks to prevailing wages and registered apprenticeships, which may be the most structurally interesting attempt to fix this yet. The jobs didn't vanish. They moved. Most people just never get told where. Wednesday, we crack open the 340,000 number: what the roles actually are, what the credential pathways look like, and what it takes to get from where you are today to inside that gap. Resources:  https://drive.google.com/file/d/14bcTnUcD7f1YR09tL-Gc7bPxo9d6VNsV/view?usp=drive_link Please visit our website for more information - Surviving AI: Navigate the Future

    Amazon's Layoffs Aren't Cost-Cutting. They're a $200 Billion Financing Move.

  3. Jul 27

    77% of Employers Will Upskill for AI. 41% Will Cut Headcount Anyway.

    Send us Fan Mail The World Economic Forum's Future of Jobs Report projects AI will create 170 million new jobs by 2030, against 92 million displaced, for a net gain of 78 million [PROJECTION, from a 1,000+ employer survey across 55 economies]. Almost everyone has heard the displacement number. Almost nobody can name one of the 170 million, because the creation half of that story never traveled the way the destruction half did. Two days after Dat Nguyen's story of falling through exactly this kind of gap, this episode names the shape of it: four real tiers of AI-era work hiring right now. Carlo and Ainsley map infrastructure and operations (the data center trades boom and the union pipelines that lead into it), the AI trainer/evaluator/red-teamer tier (domain experts, not coders, catching AI being confidently wrong), the AI-augmented professional (same job title, meaningfully more pay for the version of you that works fluently with the tools  PwC finds these "professionalized" roles growing twice as fast with 42% faster wage growth [OBSERVED]), and AI governance and compliance (driven by regulatory deadlines rather than philosophy). Along the way: why 120 million workers sit inside the WEF's own "good news" number and still won't get reskilled in time, and why the same employers who told the WEF 77% of them plan to upskill their workforce also told them 41% plan to cut headcount anyway [PROJECTION]. The honest complication closing the episode: none of this looks the same depending on where you live. The ILO and World Bank's joint research across 135 countries found that disruption often reaches workers before the dividend does. This week's call to action: run the honest inventory. Which of the four tiers are you actually closest to not with what you're planning to get, but with what you already have? Chapters below. Surviving AI publishes every Monday and Wednesday. Subscribe on Apple Podcasts, YouTube, or Spotify so you don't miss Tier 1's full deep dive in S6E2. Links:  Website: https://survivingai.co Apple Podcasts: https://podcasts.apple.com/us/podcast/surviving-ai-job-automation-workforce-future-insights/id1864360631 YouTube: https://www.youtube.com/@SurvivingAIRisk/videos Spotify: open.spotify.com/show/5rd6gdFu76HPdLBuvV5K0X Facebook: https://www.facebook.com/profile.php?id=61585767510424 TikTok: https://www.tiktok.com/@survivingai Instagram: https://www.instagram.com/surviving2030/ Please visit our website for more information - Surviving AI: Navigate the Future

    77% of Employers Will Upskill for AI. 41% Will Cut Headcount Anyway.

  4. Jul 22

    He Led 90% of His Bank's AI Rollout. They Laid Him Off Anyway.

    Send us Fan Mail We spent almost a year mapping AI job displacement in data and projections. This episode puts a real person in that picture. Dat Nguyen is an Army National Guard veteran who transitioned into IT, became a bank project manager, and ultimately led one of his bank's major AI implementation projects. He thought that made him safe. In November 2025, the bank laid him off anyway, and in his view, performance wasn't the deciding factor at all. "It's just an excuse to lay off people, and using AI as an excuse," he says. His read: Companies over-hired during the COVID-era tech boom and are now "self-correcting," with AI providing convenient cover. What makes Dat's story the right way to open Season 6 is what happened next. He didn't scramble. Within the hour, he'd redirected fourteen years of part-time stock trading experience into a full-time career, no transition period, no gap. He walks through the financial discipline that made that possible (diversifying beyond a 401(k) most people never touch), the two military-trained instincts that mattered more than his technical resume (resilience and thinking in probability instead of pass/fail), and his real advice for using AI: build a system around it instead of prompting it line by line, so you stay the one in the loop. He's also candid about what the transition cost him: carpal tunnel in both wrists, a shoulder that started hurting, and a hesitation to use veteran support resources he feels he hasn't "earned" because his service was domestic. This is Season 6's premiere: the season maps 170 million jobs AI is creating. This episode is why that map matters. Resources: https://drive.google.com/file/d/1O1VwL-vRUBx8fTAtl0wW0WdWE0hxZFwS/view?usp=sharing Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    He Led 90% of His Bank's AI Rollout. They Laid Him Off Anyway.

  5. Jul 20

    Your Power Bill Just Went Up $340 to Fund an AI Capability Nobody Can Measure

    Send us Fan Mail Three days before this episode, the grid operator serving 67 million people across 13 states cleared its latest power auction at $16.4 billion — $6.3 billion of it data centers. Across the last four auctions, data centers have added $29.4 billion to the electricity bill of those 67 million Americans. That number is filed, audited by an independent market monitor, and hasn't moved. Everything else in the AI conversation has: the forecasters, the CEOs, the EU, and the famous AI 2027 report all moved their timelines this year — some of them twice, in opposite directions. So instead of grading the forecast, we measured the noise. We walk through what AI 2027 actually says (and where its own two lead authors disagree with each other), run four simple filters — publish your update history, tell us if the ruler moved or the world did, know the difference between a mode and a median, and show us the meter — against every major voice in this fight (Kokotajlo, Hassabis, Sutskever, LeCun, Amodei, Huang), and land on the one number in the whole story nobody disputes: what's already on your power bill. Along the way: why a March 2026 Gallup poll found Americans more opposed to a data center moving in next door than a nuclear plant (a 18-point gap), what "Automated Coder" actually means as a definition (it's a layoffs threshold, not a sci-fi milestone), why METR's own randomized controlled trial found AI coding tools slowed experienced developers down while Anthropic's internal survey found the opposite, and the bad-actor scenario the entire report never scores. We also disclose plainly: this show runs on Anthropic's models, so when we're covering Anthropic's regulatory asks, that's held to the same four filters as everyone else's. Resources: https://drive.google.com/file/d/1OMvaT-kVyDfEaE6XzTjS03VtSiTDlWzV/view?usp=drive_link Surviving AI publishes every Monday and Wednesday. Subscribe on YouTube, Apple Podcasts, and Spotify. Please visit our website for more information - Surviving AI: Navigate the Future

  6. Jul 15

    The Most Dangerous AI Misconception, according to a 40-Year IT Veteran, CEO Joe Turso of Hivepoint

    Send us Fan Mail "AI doesn't replace the human; it enhances the human." That's the flat answer Joe Turso — Co-Founder/CEO of HivePoint Group, a managed service provider that has spent the last several years building an AI-native operating system for small and mid-sized businesses gives when asked whether AI is costing his clients jobs. In this Season 5 closing guest conversation, Joe walks Carlo and Ainsley through what actually happens when small businesses adopt AI without a plan: shadow AI instances popping up department by department, data silos that never talk to each other, and — the episode's real turning point — the most dangerous misconception he sees in the field: that AI can fix a broken process. It can't. It just makes a bad process fail faster. Joe also lays out the framework behind his own product: governance before adoption, "Experience Level Agreements" instead of just SLAs, and a concept he calls the "living persona" — an AI trained closely enough on how you work that it can answer for you when you're out. And in a genuinely candid turn for someone who's built his business on AI, he says plainly: he doesn't trust AI himself — which is exactly why his product keeps every client's data centralized rather than sending it to a model. This episode closes Season 5's human-skills arc from the employer's side: what businesses actually hand to AI, and what they keep human on purpose. Chapters: 00:00 Intro Meet Joe Turso, HivePoint Group 01:54 The philosophy: AI enhances, doesn't replace 04:53 Real-world enhancement the email-triage example 05:46 AI hype vs. reality: shadow AI and data silos in small business 09:15 Is AI different from the cloud, mobile, and cybersecurity waves? 10:15 Why governance has to come before adoption 12:30 What AI adoption failure actually looks like 14:03 Experience Level Agreements vs. SLAs 16:02 Early warning signs your AI is going off the rails 18:06 Trust, feedback, and the "one-person corporation" myth 20:10 Where to start: AI Readiness and the Four Ps 25:33 Hiring in the AI era: culture first, human first 28:41 The "Living Persona" and building HivePoint from scratch 34:24 The most dangerous misconception — and what to tell scared owners 38:22 Where to find Joe, and closing Find Joe and HivePoint Group at hivepointgroup.ai. Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    The Most Dangerous AI Misconception, according to a 40-Year IT Veteran, CEO Joe Turso of Hivepoint

  7. Jul 13

    1.8 million Americans Are Stuck in a Job Search Loop an AI Built — Here's the Way Out

    Send us Fan Mail "The silence is the tell." That's how this episode opens because if you've sent out dozens of applications and heard almost nothing back, the instinct is to assume something's wrong with you. It isn't. Roughly a quarter of everyone currently unemployed has been searching for 27 weeks or longer, and the average search now runs about six and a half months. Carlo and Ainsley dig into why: most applications today are screened by automated systems before a human ever sees them, and those systems were trained on years of historical hiring data which means they can quietly reproduce old bias at a scale no individual recruiter ever could. Amazon found this out the hard way with its own internal recruiting tool, which it scrapped in 2018 after discovering it was penalizing resumes that simply contained the word "women's." And the pattern goes further: one landmark independent study found that a meaningful share of Black applicants' submissions was consistently filtered out by the same systems across completely different companies — what researchers came to call "algorithmic blackball." So, what do you actually do with that? This episode is built around two practical moves. First, a reality checks most job seekers skip: a real chunk of live job postings may not be genuinely open at all — "ghost jobs" posted for pipeline-building or already spoken for internally — and there's a three-check test (posting age, division layoffs, visible new hires) that takes about ten minutes. Second, the human bypass: weak-tie networking, the kind of loosely connected relationships that get you in front of a person before a system decides you don't belong in the room. Carlo shares his own early-career habit of showing up at conferences outside his industry — and Ainsley connects it directly to decades of research on why acquaintances, not close contacts, are how most people actually find their next role. The episode closes with the Next-Door Challenge: a four-step, ten-minute-a-day plan for anyone in a long search, checking whether your target roles are real, running your resume through a free ATS scanner, reaching out to three people at target companies, and confirming whether your target category is actually growing. Because getting through the door is only half the job; showing up ready when it opens is the other half. Episode Resource: https://drive.google.com/file/d/1gyvmm3mgZvIyJL3B4B9aVvRxWOB7M3nn/view?usp=sharing Chapters: 00:00 Intro — "The silence is the tell" 03:15 Welcome, and the friends who've been searching for a year 04:16 Amazon's discarded recruiting tool 07:57 Proxy variables — how bias hides in plain sight 11:01 The algorithmic blackball stat, and the case for pivoting industries 16:25 Weak ties, Granovetter, and the blind-audition study 19:02 A conference habit that built a cross-industry network 22:17 Naming who this episode is actually for 23:33 The undercounted — who the unemployment number misses 25:57 Setting up the ghost job problem 27:07 Ghost jobs — the three-check reality test 30:41 Where the pivot starts, and the gig-economy question 32:46 Referrals, runway, and the EU vs. US legal gap 35:55 Reactivating a cold network 37:40 The loop AI hiring creates, and the Next Door Challenge 41:38 Carlo's closing story 44:56 Wrap-up, and next Monday 45:31 Bonus: mirror the new industry's language Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    1.8 million Americans Are Stuck in a Job Search Loop an AI Built — Here's the Way Out

  8. Jul 8

    77% of Companies Say They'll Help You When AI Cuts Your Job. Only 19% of Workers Ever Find Out.

    Send us Fan Mail As of July 2, 2026, AI has been the number-one stated reason for U.S. layoffs for four consecutive months  101,743 jobs cut so far this year with AI explicitly named as the cause (Challenger, Gray and Christmas). That's not a projection. It's a count of what already happened. Meanwhile, a survey of 11,000 HR leaders and employees across seven countries found something almost as alarming: 77 percent of HR leaders say their organizations already have redeployment programs to move at-risk workers into new roles. Only 19 percent of employees have ever experienced or even recognized one. Fifty-eight percentage points. That's not a communication problem; that's a safety net that's functionally invisible to the people it's supposed to catch. (LHH is a talent-solutions and outplacement business worth knowing whose research this is, even though the finding itself is well-sampled and directionally credible.) This episode closes the Responsibility Trilogy — Corporate (S5E6), Government (S5E8), and now Individual with an honest ledger of what each actor actually owns. Corporate had the resources and mostly chose efficiency over people. Government had the mandate and the scale, and where the right programs exist, uptake still lags badly. Neither of those failures disappears just because this episode is about individual action. But waiting for either institution to show up is not a strategy; it's a bet, and four straight months of AI-cited layoffs says it's a losing one. The framework: Invisibility (you're more likely to be cut for being unreadable than for being bad at your job), Inventory (three separate audits AI exposure by task, human skills, relationship inventory — that most people collapse into one), and Leverage (domain depth plus AI fluency, not a pivot to prompt engineering). This isn't just a white-collar problem — the episode makes the case that the same mechanism applies whether you're a software engineer or a shift supervisor at a distribution center. And individual responsibility doesn't mean going it alone: from a nearly-900-member worker association in Africa to a regional training community in Latin America to a program reaching a million small business owners in Nigeria, people are already building this leverage collectively. Season 5 closes here. Season 6 is coming. 📌 Listener Resource: The Invisibility, Inventory, Leverage Workbook — the full framework, three audits, and the Human Edge Challenge. Link in show notes. 🎙️ Subscribe: Apple Podcasts | Spotify | YouTube 🎧 Apple Podcasts: https://podcasts.apple.com/us/podcast/surviving-ai-navigating-ai-job-displacement-and/id1864360631 ▶️ YouTube: https://www.youtube.com/@SurvivingAIRisk 🎙️ Spotify: https://open.spotify.com/show/5rd6gdFu76HPdLBuvV5K0X 🌐 survivingai.co Please visit our website for more information - Surviving AI: Navigate the Future

    77% of Companies Say They'll Help You When AI Cuts Your Job. Only 19% of Workers Ever Find Out.
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About

Join Carlo Thompson on Surviving AI, the definitive resource for navigating AI job displacement and building a complete career, income, and life strategy for the age of artificial intelligence. This podcast breaks down the AI trends actually affecting jobs and the economy, and delivers practical guidance on skill development, career pivots, geographic positioning, and navigating automation before it navigates you. With expert insights and structured content, listeners are equipped to protect their income and capitalize on the opportunities emerging in the changing economy. Surviving AI delivers: ✓ Early warning signs your job — or industry — is vulnerable ✓ Skills that AI can't replicate (yet) ✓ Career pivots that protect your income ✓ Geographic arbitrage strategies for the AI economy ✓ Real case studies from the automation frontlines ✓ The truth about "AI will create more jobs than it destroys" This is a structured, season-by-season curriculum, not a news recap. Seasons 1–2 cover the foundations: automation risk, protected careers, skilled trades, corporate survival, and business ownership. Season 3 goes deeper into strategic positioning: where to live, how to build a career-proof network, how to read the AI market's financial signals, and how the map of opportunity is being redrawn. For professionals who'd rather adapt than be replaced, regardless of industry. This isn't fear-mongering. It's a wake-up call. Because hope isn't a strategy, but preparation is. New episodes weekly.

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