AI is not the next tech bubble waiting to burst. Unlike the dot-coms of 2000, artificial intelligence is already generating real, immediate, and measurable value. And the opportunities for those who know how to move are still enormous.

August 1896: gold is discovered in the Klondike. In just a few months, 100,000 people abandon everything for a mad rush to North America.

Sound familiar? Today, we are seeing a similar dynamic with AI:

But there is one crucial difference: the Klondike gold deposits were limited and quickly depleted (1899-1900). The opportunities offered by AI are potentially endless and globally scalable.

Late 1990s: Nasdaq soars to $2.95 trillion, then crashes 78% in two and a half years.

Then: Loss-making companies with non-existent business models Now: Tech giants with solid balance sheets and real cash flow

Then: Vague promises about the “digital future” Now: Concrete applications that already work (healthcare, finance, automation)

Then: Non-existent digital infrastructure Now: Mature ecosystem ready for AI integration

Furthermore: Current valuations remain well below the dot-com peak, and flows into equity funds have been negative in recent years, indicating a more cautious approach by investors than in 2000.

AI is the result of decades of research, not a passing fad.

As an analysis by Quartz puts it: “AI generates substantially more revenue today than the internet did in the 1990s.” Applications are already improving operational efficiency, reducing costs, and creating new opportunities through automation and predictive analytics.

Companies use AI to improve existing processes, not to reinvent everything from scratch.

An interesting paradox: as Patrick Hall, professor at George Washington University, observes, generative AI has “the lowest barrier to entry for consumers of technology.” But according to Reuters, “the end of the arms race for computing power could mean lower barriers to entry” for advanced development as well. The example of DeepSeek has also shown that cheaper systems can compete with expensive ones.

In 2000, we had too much infrastructure (fiber optic cables) and too little demand. Today, it's the opposite: everyone wants AI, but few can deliver it. This creates bottlenecks in data centers and available computing capacity.

As highlighted in the article “The Great AI Rebalancing”, AI is transforming the way we make decisions, creating “augmented decision-making frameworks” where AI handles data processing while humans retain authority over strategic and creative decisions.

Governments around the world are investing billions. This is not just private hype.

Short answer: Yes, but not necessarily in the way you think.

As in the Klondike, the richest people were often not the gold miners, but those who sold shovels and picks. In the Klondike, few miners actually found gold, while the biggest beneficiaries were the equipment sellers. In the AI era, value is more distributed across industries and applications. Today:

Both can win, but remember: success is never guaranteed.

No. The AI revolution is reminiscent of the advent of electricity: not everyone had to be Edison to benefit from it.

The AI ecosystem has several entry points, with a key lesson from tech history: it is substantive knowledge, not intermediate technical skills, that retains value in the long term.

The 5 winning roles in the AI era:

🎯 Strategic users: Professionals who understand AI well enough to reinvent processes in their industry. As with the web, imagining applications is more important than knowing the technical mechanisms.

🏆 Domain experts: The real lasting resource. Just as Google made search syntax experts obsolete, AI will make its capabilities accessible without technical skills. Those with deep disciplinary knowledge (medicine, law, engineering) will maintain an unassailable advantage.

🧠 Critical thinkers: AI will amplify those who know what to ask, not how to ask it. “Prompt engineering” is destined to become irrelevant (like SEO optimization). The ability to ask the right questions and critically evaluate results will remain essential.

🔗 Technology integrators: Developers who connect AI systems to real-world infrastructure. Here too, interfaces will become more accessible, increasing the value of understanding business processes.

🚀 Algorithm pioneers: Researchers at the frontier of innovation. A small but critical group.

The lesson: Mid-level technical skills are short-lived, while domain knowledge and critical thinking increase in value. As in the Klondike, the luckiest prospectors were not the most technical, but those who could best read the terrain.

Just as gold miners faced extreme conditions in the Klondike, “AI miners” also face significant challenges:

⚡ Rapid obsolescence of skills: Technology evolves at a dizzying pace, requiring constant updating

🌍 Global competition: Unlike the Klondike (which was geographically limited), the AI race is global

🔥 Burnout: Long hours in a highly competitive and rapidly evolving field

📜 Regulatory uncertainty: AI regulations are constantly changing, creating risks for projects and investments

⚖️ Ethical risks: Navigating the complex ethical issues surrounding AI requires constant attention

The “miner's life” is not for everyone, but for those who make it, the rewards can be enormous.

Both strategies have merit. Investing in training allows you to participate directly in value creation. Investing in companies can offer significant returns without developing specialized skills.

The best strategy depends on your circumstances, skills, and risk appetite. As in the Klondike, not all startups become unicorns, but some become exceptionally profitable.

Absolutely not. We are still in the early stages. Comparing with the internet, we are perhaps at the equivalent of 1995-1998: the fundamental technologies exist, but most of the applications that will transform the economy have yet to be developed.

With the evolution of “transformers” and generative models, new opportunities are constantly emerging. As in the Klondike, the early arrivals have advantages, but there are still many ‘deposits’ unexplored.

🏆 The hottest in 2025:

Not everything is rosy. The main dangers for those investing in AI:

💸 Valuation bubble - Some companies are overvalued compared to their fundamentals

📜 Regulatory constraints - New regulations could limit certain applications of AI

🔧 Technical barriers - Some promises may prove more difficult to deliver

🏢 Market consolidation - A few dominant companies could capture most of the value

⚖️ Ethical and reputational risks - Autonomous agents that make bad economic decisions, generate fake or deepfake content, manipulate markets, or cause real harm without human supervision. Mistakes that can be costly

📚 Training: Start with online courses on machine learning, prompt engineering, or AI applications in your industry

🧪 Experimentation: Use publicly available AI tools to understand their potential

🤝 Networking: Connect with AI professionals through conferences, online forums, and communities

💰 Investment: Consider AI-focused ETFs or investments in leading companies in the industry

⚡ Application: Identify opportunities to apply AI in your current job or to develop new solutions

Success will require vision, perseverance, adaptability, and a little luck. But unlike the physically limited gold deposits of the Yukon, the potential of AI continues to expand with every technological advancement, continually creating new opportunities for those who know how to seize them.

The AI gold rush is not the dot-com bubble 2.0. It's more like the arrival of electricity or the internet: a fundamental transformation of the economy.

Will there be corrections? Definitely. Will some companies fail? Of course. But the underlying trend is rock solid.

The question is not “if” AI will change everything, but ‘when’ and “how can I be on the right side of history.”

What do you think? Are you already in the AI gold rush or still evaluating? Reply to this email and tell us your strategy!

📚 COMPLETE SOURCES

Historical Sources:

AI vs Dot-Com Analysis:

Trends and Opportunities:

Experts Cited:

If you liked this newsletter, share it with a colleague who needs to understand AI (obviously, I wrote it all myself). If you didn't like it, blame the intern, ChatGPT, or Russian hackers—I had nothing to do with it. In any case, we'll do better next time! 😉

🌅 See you on September 5 with new certainties to demolish and trends to anticipate. A question for the summer: among everything I've told you about AI, what has really changed the way you work? Honest answers welcome—even the uncomfortable ones.

Welcome to Electe’s Newsletter - English

This newsletter explores the fascinating world of how companies are using AI to change the way they work. It shares interesting stories and discoveries about artificial intelligence in business - like how companies are using AI to make smarter decisions, what new AI tools are emerging, and how these changes affect our everyday lives.

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