Your legal team says you need local AI servers for compliance. But do you really?

In this 10-minute Q&A, Malcolm explains why 98% of companies don’t need on-premise AI at all—and why your DPA matters more than your server room.

Featuring real insights from Emil Muthu (Neuronic Solutions), who builds AI systems for banks, insurance firms, and government ministries.

You’ll learn:

• Why your Data Processing Agreement protects you more than server location
• The three things regulators actually check
• How OpenAI, Anthropic & Azure stay GDPR-compliant
• Why encryption at rest matters
• The difference between cloud with governance vs. on-premise with chaos
• A real GDPR audit example from a Romanian market leader

SHOW NOTES

Episode Summary

Malcolm destroys the biggest compliance myth: that companies need local AI servers for GDPR. Most don’t. What matters is governance, DPAs, encryption, and legal fine print.

Key Topics Covered

• The 2% Rule
• What DPAs really do
• The real compliance checklist
• Cloud with governance
• GDPR audit realities
• When on-premise actually makes sense
• How to avoid burning millions

Notable Insights“Only 2% of clients need local deployment.” — Emil Muthu“It’s not where your servers sit. It’s your DPA.”“Cloud with governance beats on-premise with chaos.”“Regulators checked the privacy policy—not the servers.”

Who Should Listen

• CEOs
• CTOs
• Compliance & Legal
• Data & AI leaders
• IT decision-makers
• Finance leaders

Key Takeaways

1. Only 2% need local servers
2. DPA > server location
3. Focus on encryption + legal fine print
4. Do POCs before infrastructure spend
5. Governance beats hardware

Where to find Malcolm Werchota:

🔗 LinkedIn:

https://www.linkedin.com/in/malcolmwerchota/

🌐 Website:

https://www.werchota.ai/

▶️ YouTube:

https://www.youtube.com/@werchota

𝕏 X / Twitter:

https://x.com/malcolmwerchota

📘 Facebook:

https://www.facebook.com/people/AI-Cookbook-by-Malcolm-Werchota/61580362300250/?sk=reels_tab

📸 Instagram:

https://www.instagram.com/malcolmwerchotaai/

🎵 TikTok:

https://www.tiktok.com/malcolmwerchota

Get in touch

📧 [email protected]

Email the Show

📧 [email protected]

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Keywords: AI compliance, data privacy, GDPR, cloud vs on-premise, DPA, AI governance, encryption, EU AI Act, business AI, enterprise AI

November 7th, 2025. Brussels.

 9:00 AM. A bureaucrat spills his coffee.

 And by 17:43 the same day, the most ambitious tech regulation in European history effectively collapses into a PDF no one wants to talk about.

In this episode, Malcolm tells the full unfiltered story of the EU AI Act — a four-year political labyrinth filled with 3,000 amendments, endless committees, lobbyists, geopolitics, and a shocking final sequence where the United States forces Europe to hit a “full regulatory pause.”

This isn’t a legal analysis.

 It’s a political thriller.

 A comedy.

 A tragedy.

 And a case study of how Europe went from leading global tech regulation to accidentally kneecapping its own innovation ecosystem.

You’ll learn:

• How Google’s Code Red panic rewired global AI strategy
• Why Europe wrote rules for a technology that didn’t exist yet
• How US pressure under the new administration broke the Act
• Why Mistral, Europe’s great AI hope, packed its bags and moved to Seattle
• Why “Education First” effectively turned the Act into a zombie law

And — most importantly — what your company should actually do next.

 Because while Brussels was dancing the Bureaucrat Tango, the rest of the world kept building.

If you want a brutally honest, geopolitical, slightly comedic breakdown of why the EU just lost its regulatory crown, this is the episode.

Key Topics Covered

🇪🇺 The Original Sin

• The EU wrote rules in 2021 for AI models that were invented in 2023–2025
• Why all classification systems failed instantly
• Overconfidence + under-technology = chaos

🧨 The Lobby Explosion

• 900+ full-time lobbyists
• €150 million spent
• 90% of AI Act meetings with Big Tech
• 3,000+ amendments turning the Act into Frankenstein

🇺🇸 American Pressure

• New U.S. administration: “Regulation freezes innovation”
• US commerce + defense warnings to EU
• NATO implications used as leverage
• EU forced into “regulatory pause”

🤖 The Rise of Frontier AI

• Google’s Code Red
• Microsoft–OpenAI supercycle
• Anthropic, xAI, Mistral, Cohere
• EU suddenly two years behind

🧟 The EU AI Act Becomes a Zombie

• No enforcement
• No fines
• No clear authority
• “Education First” replaces compliance
• Rollout pushed to 2027–2028

🇫🇷 The Final Blow: Mistral Relocates

• Europe’s most promising AI lab moves operations to Seattle
• “We need talent density & compute”
• Symbolic end of EU AI sovereignty

🧭 What Companies Should Do Now

• Stop waiting for Brussels
• Build internal AI safety & governance
• Adopt frontier models
• Document everything
• Focus on capability uplift, not compliance paperwork

💬 NOTABLE QUOTES

“We used to talk about the Brussels Effect. Now we talk about the Brussels Bluff.” “The EU tried to regulate a future they didn’t understand — and the future arrived faster than the law.” “Geopolitically, the US didn’t just kill the Act. They used a feather.” “By the time the Act was ready, the world had already moved on.” “Mistral moving to Seattle is Europe’s AI moment of truth.”

🔗 LINKSMalcolm Werchota

• LinkedIn → https://www.linkedin.com/in/malcolmwerchota
• Website → https://www.werchota.ai
• YouTube → https://www.youtube.com/@werchota
• X → https://x.com/malcolmwerchota
• Instagram → https://www.instagram.com/malcolmwerchotaai
• TikTok → https://www.tiktok.com/@malcolmwerchota

🧠 AI FIT ACADEMY

Ship First. Study Later.

 Working AI workflows by Week 2 — or 100% refund.

 Start your transformation → https://www.werchota.ai/ai-fit-academy

The consulting industry’s 70-year-old pyramid model is cracking in real time.

Four days ago, the Financial Times dropped a quiet bomb:

“Top consultancies freeze starting salaries as AI threatens the pyramid model.”

For the third year in a row, McKinsey, BCG, Bain and the Big Four have frozen graduate salaries.

Graduate hiring in the UK is down 50%.

Accenture just laid off 11,000 people and announced a massive partnership with OpenAI.

Microsoft paused all U.S. consulting hiring for an entire fiscal year.

In this episode, Malcolm breaks down why the pyramid is collapsing, what shapes will replace it, and why clients today show up better prepared with Gemini, Claude and ChatGPT than many consultants.

You’ll learn:

• Why junior consultant tasks (research, analysis, slide-making) have been automated
• Why partners are protecting profits at the expense of the base
• How Accenture admitted it can’t retrain its consultants fast enough
• Why clients now challenge Big Four experts using AI before meetings
• Why entry consulting roles may vanish before new ones are created
• What the “hourglass” and “obelisk” consulting models look like
• What this means for MBA graduates, senior partners, and boutique firms
• Why the real winners are small, AI-native consulting teams

If you're in consulting, planning to join, or hiring consultants for AI transformation — this episode is your wake-up call.

The pyramid is crumbling. Something new is rising.

KEY TOPICS COVERED

🔹 The Classic Pyramid Model (and why it worked for 70 years)

• Tens of thousands of junior analysts → few partners
• Juniors billed at 400–600 EUR/hour
• Model based on leverage + generalists + manual labor

🔹 Why the Pyramid Is Cracking Now

• AI replaces research, synthesis, due diligence, basic analysis
• Claude/Sonnet/Gemini produce P&Ls, analysis, dashboards instantly
• Slide-making still manual, but everything else is automated
• Clients know this — and refuse to pay old prices

🔹 Industry Signals & Data Points

• McKinsey, BCG, Bain freeze salaries for 3rd consecutive year
• PwC cuts graduate hiring by 50%
• Accenture cuts 11,000 consultants, signs OpenAI mega-partnership
• Microsoft freezes all consulting hiring through FY2025
• Consulting revenue stagnant, but cloud/AI revenue booming

🔹 The Accenture Case

• CEO Julie Sweet: “We are exiting on a compressed timeline… reskilling is not viable.”
• 40,000 ChatGPT Enterprise licenses
• Investors reward layoffs + AI investment (stock jumps 4%)

🔹 Client Behavior Has Changed

• Clients run their own AI analysis before consultants arrive
• “We yanked the dataset into Gemini — here are the 4 scenarios; validate them.”
• Projects shrink from €500k strategy engagements to €50k validations
• Consulting value shifts from “We think…” to “Show us you actually use AI.”

🔹 New Consulting Shapes Emerging

• Obelisk Model – fewer layers, senior-heavy
• Hourglass Model – AI automates the middle, small base + small middle + large top
• Box Model – stable senior cohort with small technical pods

🔹 Why AI Breaks the Leverage Model

• 1 senior consultant + AI = output of 5 analysts
• Less coaching, less overhead, no long training pipeline
• Shrinking base = collapsing partner economics

🔹 “The Gap in the Middle”

• Roles disappear before new ones arrive
• Young graduates can’t “learn the craft” without entry roles
• Partners may have no successors in 10 years

🔹 What Malcolm Sees in Real Projects

• Big consultancies unable to demonstrate hands-on AI usage
• Boutique AI-native teams outperforming traditional players
• CTOs saying: “Your consultants know nothing more than college students using AI.”

NOTABLE QUOTES

“With good prompting, clients can get 80% of the value directly from AI tools.”“Accenture’s stock went up the moment they cut 11,000 people. The market spoke.”“Clients arrive armed with Gemini deep research — and they’re not paying for interns to learn on the job.”“If you’re planning to become a partner in 15 years… I’m not sure the pyramid will still exist.”“No one at a big firm uses AI 10% as intensively as small boutiques do.”📣 WHERE TO FIND MALCOLM

• LinkedIn: https://www.linkedin.com/in/malcolmwerchota/
• Website: https://www.werchota.ai
• YouTube: https://www.youtube.com/@werchota
• X/Twitter: https://x.com/malcolmwerchota
• Instagram: https://www.instagram.com/malcolmwerchotaai/
• TikTok: https://www.tiktok.com/@malcolmwerchota

🧠 AI FIT ACADEMY

Ship First. Study Later.

Working AI workflows by Week 2, or 100% refund.

→ https://www.werchota.ai/ai-fit-academy

We talk a lot about new AI models, benchmarks, context windows, agents and multimodality.

 But while everyone is staring at technical progress, something far bigger is unfolding:

Courts all over the world are beginning to define the legal boundaries of AI.

 And they are doing it fast.

 Faster than any regulator, faster than any company, and definitely faster than the EU AI Act.

In this episode, Malcolm breaks down three explosive legal cases that mark the beginning of the global AI jurisprudence era:

• Anthropic pays $1.5 billion to settle a copyright lawsuit in the U.S.
• OpenAI loses a landmark ruling in Munich against GEMA
• Hollywood giants unite against Midjourney, signaling a massive wave of lawsuits for image models

These aren’t “AI ethics” discussions.

 This is real money, real precedent, real danger — and real opportunity.

If your company builds AI models, fine-tunes them, trains them on internal data, advises clients, or simply stores mountains of PDFs on SharePoint…

 this episode is mission-critical.

 Because these cases are defining the rules of the next decade — right now, in real time.

Action. Let’s go.

🔥 Key Topics Covered

🔹 1. The $1.5 Billion Anthropic Settlement (U.S.)

• Largest copyright settlement in U.S. history
• Authors accuse Anthropic of training Claude on pirated books
• Court rejects “fair use” defense:
•  “This is not transformation. This is piracy.”
• Datasets included BookTree, Library Genesis, Pirate Library Mirror
• Effective price per illegally trained book: $3,000
• Sets a global precedent: The source matters.

🔹 2. GEMA vs. OpenAI (Germany) — A Landmark Ruling

• Munich District Court: OpenAI reproduces copyrighted song lyrics
• OpenAI defense: “Users are responsible, not us.”
• Court: “Bullshit. The developer is responsible.”
• Key takeaway:
  • LLMs memorize and reproduce copyright-protected text
  • Companies must stop ingesting unlicensed material
  • No model can “unlearn” — deletion is impossible

🔹 3. Hollywood vs. Midjourney — The Visual Copyright War

• Disney, Warner Bros., Universal join forces
• Accusation: training on Superman, Batman, Wonder Woman, Bugs Bunny, Mickey Mouse
• Potential damages: $150,000 per work
• Midjourney claims “fair use,” courts likely disagree
• This could become the Napster moment of image models

💬 Notable Quotes“This is not fair use. This is piracy.” “LLMs can’t unlearn — once it’s in, it’s in forever.” “You don’t even know what’s sitting on your company’s SharePoint.” “The EU AI Act is sleeping. Courts are not.” “Lawyers move slow. AI law is moving at rocket speed.”

🔗 LINKSMalcolm Werchota

• Website → https://www.werchota.ai
• LinkedIn → https://www.linkedin.com/in/malcolmwerchota/
• YouTube → https://www.youtube.com/@werchota
• X → https://x.com/malcolmwerchota
• Instagram → https://www.instagram.com/malcolmwerchotaai
• TikTok → https://www.tiktok.com/@malcolmwerchota

🧠 AI FIT ACADEMY

Ship First. Study Later.

 Your team builds real AI workflows by Week 2 — or you get 100% of your money back.

 Start here → https://www.werchota.ai/ai-fit-academy

The future of work is not science fiction. It’s happening right now — quietly, rapidly, beneath the surface of corporate boardrooms. And the job at the center of this revolution is one most executives have never even heard of:

Forward Deployed Engineers (FDEs).

While some companies are still debating AI governance frameworks and writing 40-page PowerPoints, the real action — the real transformation — is happening on the ground. FDEs at Palantir, Cohere, Anthropic, OpenAI and dozens of hyper-growth startups are embedding with customers, building prototypes in days instead of quarters, and translating impossible workflows into scalable AI solutions.

And here’s the shockwave:

📈 170 million NEW jobs by 2030.

 📉 92 million jobs disappearing.

 = +78 million net new roles, many of them hybrid, human-centered, and deeply underestimated.

In this episode, Malcolm breaks down why FDEs have become the fastest-growing role in AI (800% YoY), how companies like John Deere, Tesla, Amazon and global banks are using them to unlock billions in operational value, and why this role fundamentally proves one thing:

Humans are not being replaced. Humans are being upgraded.

This episode goes beyond hype. It’s a grounded, data-driven look at AI adoption, the real tasks disappearing, the new skills emerging, and why the companies that refuse to invest in FDE-style talent will lose entire markets to competitors who move faster, learn faster, and deploy faster.

If you want to understand the real future of AI work — not the headlines, but the mechanics — this is the episode.

Key Topics Covered🔹 The Rise of the Forward Deployed Engineer

• 800% growth in 12 months
• Why OpenAI, Anthropic and Palantir hire FDEs instead of “prompt engineers”
• Human-in-the-loop value creation

🔹 170 Million New Jobs

• World Economic Forum data
• Why net job creation is positive, not negative
• The illusion of “AI job loss panic”

🔹 John Deere’s Precision AI Example

• 60–70% reduction in chemicals
• Agriculture becomes a high-tech industry
• Machines + humans → exponential gains

🔹 The Skills That Actually Matter

• Judgment
• Communication
• Domain expertise
• Curiosity, courage, humility

🔹 Why Traditional Roles Are Evolving, Not Disappearing

• CFOs become “AI-augmented risk allocators”
• Engineers become workflow architects
• HR turns into an AI-powered talent engine

🔹 The Corporate Gap

• Executives planning AI strategy vs.
• 7-year-olds already deploying AI apps (true story)
• Why the adoption gap is a leadership problem, not a tech problem

💬 NOTABLE QUOTES“AI isn’t replacing humans — it’s replacing humans who refuse to use AI.” “FDEs don’t wait for permission. They deploy, iterate, and learn in real time.” “170 million new jobs is not a warning. It’s a renaissance.” “If your 7-year-old can build a dashboard in five minutes, what’s your executive team’s excuse?” “The companies winning today aren’t the ones with the most strategy — they’re the ones with the most action.”

🔗 LINKS & REFERENCESMalcolm Werchota

• LinkedIn → https://www.linkedin.com/in/malcolmwerchota/
• Website → https://www.werchota.ai/
• YouTube → https://www.youtube.com/@werchota
• X → https://x.com/malcolmwerchota
• Instagram → https://www.instagram.com/malcolmwerchotaai/
• TikTok → https://www.tiktok.com/@malcolmwerchota

🧠 AI FIT ACADEMY

Ship First. Study Later.

 Get your team to working AI workflows by Week 2, or 100% refund — no questions asked.

 Start here → https://www.werchota.ai/ai-fit-academy

Google just did something nobody expected. After two years of awkward missteps (remember Bard?), they launched Gemini 3.0 — and instantly flipped the entire AI industry on its head.

This episode is not a product review.

 It’s a story about comebacks, market power, geopolitics, and how quickly the ground can shift beneath you.

Salesforce CEO Marc Benioff tested Gemini for two hours and publicly wrote:

 “Holy shit. I’m not going back.”

 Sam Altman himself had to respond.

Malcolm breaks down what changed technically, strategically, and emotionally — including how he built a production-ready invoice processor and a full 5S hazard-detection app in 188 seconds. This is Google at its most dangerous: fast, focused, and building all the missing pieces at once.

We explore why Nano Banana Pro is rewriting the rules of image generation, why SynthID might become the global watermarking standard, why Alphabet stock is exploding, and how Google is attacking Nvidia’s hardware monopoly through TPUs.

And Malcolm goes deeper — sharing a personal story about losing his mother just days before recording, and why the overwhelming support from listeners gave him the strength to come back.

If you want one episode that captures the drama, the breakthroughs, and the raw “holy shit” moments of late 2025 AI — this is it.

Key Topics Covered

🔹 Google’s Comeback

• Gemini 3.0 as a true “ChatGPT moment”
• Benioff’s viral post and Sam Altman’s rare acknowledgment
• How Gemini fixed image, video, and reasoning weaknesses overnight

🔹 Hands-On Builds

• Expense processor app using 200+ invoices
• The 188-second hazard-detection camera app
• Why Gemini finally beats Claude & ChatGPT on workflow speed

🔹 Nano Banana Pro

• “Thinking before generating” — a new paradigm
• Website annotation, UX feedback, photography restoration
• Visual summaries of papers, comics, manga explanations
• SynthID watermarking for image verification

🔹 Market Impact

• Alphabet at $3.82 trillion, heading toward $4T
• Buffett entering Alphabet for the first time
• Google beating earnings by 26%
• Why cloud and AI revenue are accelerating

🔹 TPUs vs Nvidia

• Meta planning billions in Google TPU spending
• Anthropic diversifying training compute
• Nvidia stock wobbling after the news
• Why we’re entering a hardware multipolar world

🔹 The 3 Takeaways

1. The AI race is unpredictable
2. Multimodal is the future
3. Diversify your AI stack — no more single-vendor thinking

Notable Quotes“This is a real earthquake in AI. A terremoto.” “You know the model is broken when you ask for a Nazi in SS uniform and a Black guy comes out.” “188 seconds. That’s how long it took to build something developers need two weeks for.” “Warren Buffett does not invest in hype. Him buying Alphabet means something fundamental changed.” “Don’t put all your eggs in one basket. We’re done with that era.” “Google is back. And Malcolm is too.”LINKSMalcolm Werchota

• LinkedIn → https://www.linkedin.com/in/malcolmwerchota/
• Website → https://www.werchota.ai/
• YouTube → https://www.youtube.com/@werchota
• X → https://x.com/malcolmwerchota
• Instagram → https://www.instagram.com/malcolmwerchotaai/
• TikTok → https://www.tiktok.com/@malcolmwerchota
• Facebook → https://www.facebook.com/people/AI-Cookbook-by-Malcolm-Werchota/61580362300250

🧠 AI FIT ACADEMY

Ship First. Study Later.

 Your team will build working AI workflows by Week 2 — or 100% refund.

 Start now → https://www.werchota.ai/ai-fit-academy

NVIDIA just became the first company in history to hit a $5 trillion valuation — and most analysts think it’s overpriced.

But what if they’re completely wrong?

In this episode, Malcolm Werchota breaks down why NVIDIA’s $5 trillion market cap might be the biggest misjudgment in tech investing. With $500 billion in signed chip orders, 90% market share in AI chips, and an unbreakable software moat called CUDA, NVIDIA isn’t just riding the AI wave — they’re building the infrastructure that makes everything else possible.

🧠 You’ll discover:

• Why NVIDIA has $500B in VISIBLE revenue already locked in (no speculation needed)
• The “railroad analogy” that explains why this isn’t another dot-com bubble
• How CUDA software creates 6–18 months of switching costs for any competitor
• Why China’s reopening could add $50B in annual revenue (pure upside not priced in)
• The power-grid crisis that proves AI infrastructure demand is already locked in
• What it means when companies become GPU-rich vs GPU-poor

Malcolm explains why NVIDIA isn’t a speculative bet on AI — they’re the picks-and-shovels manufacturer in the largest infrastructure transformation since electricity.

Whether AI apps succeed or fail, the hardware stays.

📍 Recorded in London — real analysis, zero BS.

🔥 Notable Quotes

“NVIDIA is probably the first technology company in history with visibility of half a trillion dollars of revenue.” — Jensen Huang“Every single European company I meet is GPU-poor — they simply can’t get enough NVIDIA chips.”“Top AI talent goes where the best hardware is. Access to GPUs has become a recruiting advantage.”“NVIDIA isn’t the speculative railroad company. They’re the track manufacturer, the locomotive builder, and the OS provider.”“It doesn’t matter which AI app wins — they’ll all run on NVIDIA hardware.”“It’s a $5 trillion misjudgment. We’re laying the tracks of the next industrial age.”

📈 Key Stats to Remember

• $5 T – NVIDIA’s market valuation (first ever)
• $500 B – Signed chip orders (visible revenue)
• 90%+ – Market share in AI data-center GPUs
• 3.5 M – CUDA developers
• $50 B – China upside
• 1 GW – Power per AI data center
• 6–18 months – Switching cost from CUDA
• 95% – Former China share

📡 Connect with Malcolm Werchota

🌐 Website: www.werchota.ai

💼 LinkedIn: Malcolm Werchota

🎥 YouTube: @werchota

🐦 X / Twitter: @malcolmwerchota

📸 Instagram: malcolmwerchotaai

🎧 TikTok: @malcolmwerchota

📬 Email: [email protected]

🎓 AI Fit Academy

Ready to level up your AI skills?

Join Malcolm’s AI Fit Academy — where professionals and teams learn to apply AI tools effectively in real workflows.

Ship First. Study Later.

Working AI workflows by Week 2 or 100% refund.

👉 Learn more here.

Amazon’s announcement of 30,000 corporate layoffs marks the largest job cut in company history—and it’s just the first wave. In this eye-opening episode recorded from Zurich Airport, Malcolm Werchota exposes the brutal economics behind Amazon’s AI-driven workforce reduction and what it means for white-collar workers everywhere. With leaked documents revealing plans to eliminate 600,000 positions by 2033, this isn’t just Amazon’s story—it’s a preview of what’s coming to every industry.

Key Topics Covered

• Amazon’s 30,000 corporate layoffs: Who’s getting cut and why
• The brutal math: How AI automation drives $13B in savings
• HR departments slashed by 15%—recruiting, performance reviews, and support automated
• AWS optimization: Cutting humans even in profitable divisions
• Internal “prompt mining” systems tracking employee AI usage
• Collapse of middle management: Ages 45–60 most vulnerable
• Leaked docs: 150,000 additional job cuts planned in 2 years
• Why Amazon’s stock rose 1.5% after announcing layoffs
• The CapEx/OpEx loop: Reinvesting salary savings into more AI
• Career survival strategies for the AI era

Notable Quotes“Amazon is removing 30,000 problems. And who are they replacing it with? Well, probably AI agents, robots.”“If you can do the same job that you had 100 people for, now with 30, this is where you can go and create efficiency gain.”“It’s easier for experienced workers to learn how to use AI very well, versus an AI system learning your skills.”“Be AI hungry. Because that’s the only thing that will save you from being part of these 30,000 people at Amazon.”Who Should Listen

• Middle managers, project managers, and operations professionals
• HR professionals concerned about automation
• White-collar workers ages 45–60
• Anyone in customer support, documentation, or administrative roles
• Business leaders planning workforce strategy
• Professionals who want to upskill with AI before it’s too late

Key Takeaways

• ✓ Amazon’s layoffs target white-collar corporate roles, not warehouse workers
• ✓ AI creates a vicious circle: more AI → fewer people → more money for AI
• ✓ Companies are tracking employee AI usage via prompt mining and internal dashboards
• ✓ Middle management is collapsing—the “middle” of the fork is disappearing
• ✓ Your business experience + AI skills = irreplaceable value
• ✓ Start asking your company about AI strategy, training, and co-pilot licenses now
• ✓ Being “AI-hungry” is no longer optional—it’s a survival skill

Resources Mentioned

• AI Fit Academy — Malcolm’s program for professionals and teams applying AI tools effectively:
• 🔗 https://www.werchota.ai/ai-fit-academy
• “Ship First, Study Later” philosophy — Working workflows by Week 2 or 100% refund

Call to Action

Don’t wait until the layoffs hit your company. Start your AI upskilling journey today with AI Fit Academy, where Malcolm helps professionals transform their careers with practical AI implementation. Get working workflows by Week 2 or receive a 100% refund.

👉 https://www.werchota.ai/ai-fit-academy

Where to Find Malcolm Werchota

• LinkedIn: https://www.linkedin.com/in/malcolmwerchota/
• Website: https://www.werchota.ai/
• YouTube: https://www.youtube.com/@werchota
• X (Twitter): https://x.com/malcolmwerchota
• Facebook: https://www.facebook.com/people/AI-Cookbook-by-Malcolm-Werchota/61580362300250/?sk=reels_tab
• Instagram: https://www.instagram.com/malcolmwerchotaai/
• TikTok: https://www.tiktok.com/malcolmwerchota

Get in Touch

• Questions or transformation stories? Email Malcolm:
• [email protected]

Email the Show

• Requests, feedback, or ideas: [email protected]

Ready to Level Up Your AI Skills?

Explore AI Fit Academy — Malcolm’s program helping professionals and teams apply AI tools effectively in work and business. Ship First, Study Later — working workflows by Week 2 or 100% refund.

🔗 https://www.werchota.ai/ai-fit-academy

OpenAI launched a new awards program in October 2025: “Tokens of Appreciation” — physical trophies for companies based on their ChatGPT usage.

The numbers are insane: only 141 companies worldwide received these awards.

McKinsey leads with 100 billion processed tokens — equivalent to 75 billion words, or roughly 7 million consulting reports.

PwC follows as the largest ChatGPT Enterprise customer with over 100,000 licenses, and is now the first official OpenAI reseller.

This episode reveals: when the Pentagon, Morgan Stanley, and the Big Four are all using ChatGPT — what’s your company’s excuse?

Key Topics

OpenAI “Tokens of Appreciation” Awards

• Launched in October 2025
• Only 141 companies worldwide received awards
• Three tiers: Silver (10B tokens), Black (100B tokens), and Blue (top level)
• Physical trophies as new status symbols in the AI community

The Winners – The 1-Billion-Token Club

• Duolingo: Uses ChatGPT for personalized language learning content
• Shopify: Embeds AI into e-commerce management
• Salesforce: CRM giant leverages ChatGPT for customer intelligence
• HubSpot: AI-powered marketing automation
• Stripe: Uses ChatGPT for fraud detection and customer support
• Notion: Productivity platform with advanced AI features

The Champions – The 100-Billion-Token Club

• McKinsey: 100B tokens = 75B words = 500,000 novels = 7M consulting reports
• PwC: Largest ChatGPT Enterprise customer with 100,000+ licenses
• PwC: First official OpenAI reseller with 950+ clients
• BCG: Deep AI integration in client consulting projects
• Bain & Company: Strategic AI implementation across operations
• Deloitte: Completing the Big Four circle

How the Big Four Use ChatGPT

• Direct use in client projects (not just internally)
• Clients ask: “Why pay €500/hour when AI does the work?”
• PwC’s reseller model: selling ChatGPT Enterprise to their clients
• Internal productivity boost: higher output with the same headcount

The Pentagon & Morgan Stanley Connection

• U.S. Department of Defense uses ChatGPT for sensitive operations
• Morgan Stanley: Adopts ChatGPT under strictest compliance rules
• Both operate under extreme security standards — and still use AI
• Proof: Compliance is no longer a valid excuse

Reality Check for European Companies

• Typical excuses: Compliance, Security, Data Privacy, “We’re still evaluating”
• Fact: The Pentagon and the Big Four have far stricter requirements
• Competitors are building massive knowledge and efficiency advantages
• The window of opportunity is closing fast

What These Numbers Really Mean

• 100 billion tokens = an unfathomable amount of processed information
• McKinsey alone = 7 million traditional consulting reports
• These firms aren’t experimenting — AI is business-critical
• The productivity gap is already huge

Malcolm’s Core Message

• “Ship First, Study Later” has never been more important
• The age of excuses is over — the evidence is undeniable
• The question is no longer if but when you start
• Every day of delay = a bigger competitive gap

Notable Quotes

“Holy shit, bro — McKinsey processed 100 BILLION tokens. That’s 7 MILLION consulting reports.”“If the Pentagon uses ChatGPT — what’s your compliance excuse?”“PwC isn’t just the largest ChatGPT customer with 100,000 licenses — they’re the first reseller. They’re selling it to their clients.”“Clients ask: ‘Why pay €500 an hour if AI does the work?’ Good question. But the better one is: What are you doing in your company?”“While you’re still evaluating, your competitors are processing billions of tokens. That lead is not coming back.”Where to Find Malcolm Werchota

• LinkedIn: linkedin.com/in/malcolmwerchota
• Website: werchota.ai
• YouTube: @werchota
• X: @malcolmwerchota
• Facebook: AI Cookbook by Malcolm Werchota
• Instagram: @malcolmwerchotaai
• TikTok: @malcolmwerchota

Get in Touch

Questions about AI implementation or want to share your transformation story?

📩 [email protected]

Have ideas or episode suggestions?

💬 [email protected]

Ready to Level Up Your AI Skills?

Discover the AI Fit Academy — Malcolm’s hands-on program for professionals and teams who want to integrate AI tools effectively in their daily work.

Ship First, Study Later – working workflows from Week 2 or your money back.

👉 https://www.werchota.ai/ai-fit-academy

Tags: #ChatGPT #OpenAI #McKinsey #PwC #BigFour #AIAdoption #EnterpriseAI #AITransformation #ChatGPTEnterprise #AIImplementation #ConsultingIndustry #MalcolmWerchota #AICookbook

Did you know...

that the same AI infrastructure your company relies on is also being used to identify military targets in Gaza and Ukraine?

This episode exposes the shocking reality behind systems like Lavender and Palantir — and what that means for your company’s AI strategy.

In January 2024, a drone strike killed three U.S. soldiers — even though a state-of-the-art AI defense system had detected the incoming drone.

The algorithm simply froze. Why?

Because it couldn’t tell friend from foe when an enemy drone flew beside a U.S. drone.

In this investigative episode, Malcolm Werchota reveals:

The Reality of Military AI Systems

• Lavender: Israel’s AI system that marked 37,000 people in Gaza as targets — with a 10% error rate
• Where’s Daddy: An algorithm that waits until targets return home to strike
• Palantir in Ukraine: Target acquisition time reduced from 6–8 hours to 2–3 minutes
• Eagle Eye by Anduril: Augmented-reality helmets turning soldiers into “technomancers”

The 20-Second Decision

Israeli soldiers have, on average, 20 seconds to review AI-generated target lists.

One soldier admitted:

“I had zero added value as a human being — other than to rubber-stamp the algorithm’s output.”The Business Connection

Microsoft Azure, Google Cloud, and AWS — the same platforms hosting your business data — also process 11,000 terabytes of surveillance footage.

The infrastructure is identical.

Only the application differs.

Critical Questions for Leaders

How much time do you give your employees to verify AI-driven decisions?

20 seconds? 30 seconds?

Do you create a “moral crumple zone” where lower-level employees take the blame when algorithms fail?

The technology you deploy in your company is the same technology that kills people in war.

This episode isn’t science fiction.

It’s October 2025.

This is happening now.

🎧 Listen to the full investigation into the dark side of AI — and what you must change inside your organization.

📊 Systems & Technologies

Military

• Lavender (Israel)
• Where’s Daddy (Israel)
• Eagle Eye (Anduril)
• Meta Constellation (Palantir)
• X-62 Vista (U.S. Air Force)
• FPV Drones (Ukraine)

Commercial

• Microsoft Azure
• Google Cloud (Project Nimbus)
• Amazon AWS
• Anthropic Claude Government
• OpenAI / Pentagon

🔗 Resources & References

• Lavender AI System (IDF)
• Where’s Daddy (IDF)
• Anduril Eagle Eye
• Palantir Meta Constellation
• Project Nimbus
• Claude Government

📬 Contact

Malcolm Werchota

🔗 LinkedIn

🌐 Website

📺 YouTube

𝕏 Twitter / X

📘 Facebook

📸 Instagram

🎵 TikTok

📧 Email: [email protected]

💬 Show Feedback: [email protected]

🚀 AI Fit Academy

Discover the AI Fit Academy — the program that helps professionals apply AI tools practically in daily work.

Ship First, Study Later – real workflows by week 2 or your money back.

🎧 About The AI Cookbook

The AI Cookbook is an investigative podcast about real AI disasters and their human consequences.

Host Malcolm Werchota uncovers how artificial intelligence is already reshaping our world — often in ways we don’t see.

This is Episode 86: AI in War — an investigation into how the same technology powering your company also drives modern warfare.