Dot-Com to Dot-AI: Avoiding the Past’s Pitfalls, Building the Future

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 Hi there, Innovators!

Let’s take a walk down memory lane with our AI shoes on. Today’s edition explores why the AI boom feels eerily like the dot-com bubble, and what enterprises should do now to avoid bursting. We’ll also unpack a landmark study on the true impact of AI assistants on income and productivity (hint: it’s not what you think), plus why NVIDIA is quietly shifting its sights away from hyperscalers and toward enterprise dominance. Oh, and yes—students are still cheating with ChatGPT, but the way they’re doing it says more about your future workforce than it does about academia.

Let’s get into it.

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The Dot-Com Lessons AI Must Learn (Before It’s Too Late)

If the current AI boom is giving you flashbacks to the dot-com era, you're not wrong. The parallels are uncanny: speculative funding, buzzword inflation, a flood of tools with no clear use case, and companies scrambling to “do something with AI” just to stay relevant.

But here’s the real risk: history might not just rhyme, it might fully repeat this time.

In the late ’90s, tech adoption was driven more by FOMO than by strategy. Countless companies poured money into websites and online tools without a clue how they fit into their operations or customer journeys. The result was a lot of vaporware, some spectacular flameouts, and a few quiet giants that quietly laid the groundwork for the next decade.

Sound familiar?

Today’s AI landscape is showing similar patterns:

• Many organizations are deploying GenAI pilots without clear business outcomes or ownership.

• Tools are launched without integration into core systems or KPIs.

• Most teams aren’t trained on how to use AI tools responsibly or effectively.

The winners in this next phase will be the ones who:

• Identify high-impact problems that AI is uniquely suited to solve.

• Build internal infrastructure (data pipelines, governance, training) that sets them up to scale.

• Focus on alignment, not experimentation.

Enterprises don’t need more AI tools. They need better AI strategy.

Bottom line: Treat this moment like an inflection point, not a sprint. Lay the rails now for AI to run on—before your competitors do.

What to Watch: Chatbots Actually Do Boost Income—But There’s a Catch

Fortune just reported on one of the most comprehensive studies yet on AI in the workplace, analyzing how chatbots like GPT-4 impact actual earnings and hours worked across occupations. The results? Both promising and sobering.

Key takeaways:

• AI can raise earnings by 10-20% for workers already in high-productivity environments.

• The benefits disappear for lower-income or less digitized workers, exacerbating inequality.

• It’s not reducing hours overall—it’s just redistributing time from “rote” to “relational” tasks.

Translation for enterprises:

• The productivity boost is real—but only if your teams are equipped, trained, and supported.

• Simply “rolling out” an AI tool isn’t enough. Without enablement, most employees won't use it—or worse, will misuse it.

The Takeaway: If AI isn't lifting your bottom quartile, you’re not deploying it strategically.

In the News

1. AI Cheating in Schools = Your Next Talent Risk
The New York Times explores how students are increasingly using ChatGPT and other AI tools to complete assignments undetected. But this isn’t just a story about academic integrity—it’s a preview of how future employees will (mis)use generative AI tools in corporate settings without proper policies and training.
→ Read more

2. NVIDIA Wants Off the Hyperscaler Hamster Wheel
PYMNTS reports that NVIDIA is pushing beyond its reliance on hyperscalers like AWS and Azure to target a new customer: you. Enterprises are next on the chip giant’s conquest map as it seeks to embed GPUs deeper into vertical-specific stacks and mid-size infrastructure.
→ Full scoop

3. All Eyes on Taiwan: Jensen Huang’s Next Reveal
Reuters confirms that NVIDIA CEO Jensen Huang will headline Taiwan’s Computex event this week. Expect next-gen GPU updates, AI workstation previews, and (rumor has it) a push into more energy-efficient compute for on-prem enterprise stacks.
→ Get the report

TL;DR:

• Main: Don’t let AI become the next dot-com bust—invest in strategy, not just tools.

• What to Watch: AI chatbots can increase income and productivity—but only in the right environments with the right support.

• News:

  • Students are cheating with ChatGPT—but it’s your hiring pipeline that should worry you.

  • NVIDIA is shifting focus from hyperscalers to enterprise infrastructure.

  • Jensen Huang is expected to announce new AI hardware at Computex this week.

AI may be moving fast, but wisdom is still underpriced. Companies that learn from the past (dot-com crash), understand the present (earnings inequality), and anticipate the future (AI-native workplaces) will come out ahead.

Stay sharp,

Cat Valverde
Founder, Enterprise AI Solutions
Navigating Tomorrow's Tech Landscape Together