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The buzz around Artificial Intelligence is deafening. The surge in AI hype has led to an explosion of new tools, platforms, and services promising to revolutionize everything from writing emails to diagnosing diseases. This wave of AI-driven innovation evokes a powerful sense of déjà vu for those who witnessed the dot-com boom and bust of the late 90s and early 2000s. Are we witnessing history repeat itself, or is this time truly different?
AI Hype & Déjà Vu: Echoes of the Dot-Com Bubble
The parallels between the two eras are striking. Just as the internet promised to transform business in the late 90s, AI is now touted as the next disruptive force. During the dot-com bubble, investors poured money into anything with a “.com” in its name. Eager to capitalize on the internet’s perceived limitless potential, they funded companies that often lacked viable business models or even a clear understanding of what they were building. The market was full of hype but short on substance, and when the bubble burst, it wiped out billions in market value almost overnight.
Similarly, the current wave of AI hype has created a crowded market full of hastily assembled products and services. But look closely, and many of these offerings are nothing more than thin wrappers around existing models like ChatGPT—marketing themselves as revolutionary without adding real value. It’s not just about investors buying stocks or venture capitalists backing companies; even individual consumers are getting swept up in the frenzy, subscribing to AI tools that might not deliver on their lofty promises.
“…many of these offerings are nothing more than thin wrappers around existing models like ChatGPT—marketing themselves as revolutionary without adding real value.”
The Rise of Empty Promises: Influencers and the Era of Hype
We live in the “era of the influencer,” where self-proclaimed experts tout AI tools on social media, driven more by AI hype than actual expertise, often with little understanding of the technology themselves. Their authority is based on follower counts, not expertise. They promise to transform your business or skyrocket your productivity with “cutting-edge” tools. But the harsh reality is that many of these tools are like empty plastic bags—poke a little, and they tear right through, revealing nothing but air.
Influencers peddle prompt engineering courses or AI-generated content services as quick paths to success. They promise to share the secret sauce but often recycle freely available information or advice easily obtained with a few minutes of research. Their real influence? The ability to sell hype and make a quick buck, not to offer genuinely valuable insights or tools.
“…the harsh reality is that many of these tools are like empty plastic bags—poke a little, and they tear right through, revealing nothing but air.”
Caution: It’s Not Just for Investors Anymore
While it’s crucial for investors to exercise due diligence before backing an AI startup, this caution extends to everyday users as well. Many individuals are now paying for tools and services that are little more than fancy interfaces built on top of free AI models. For instance:
- Paid writing assistants that simply integrate with ChatGPT or Gemini but add little beyond a basic UI layer.
- Overpriced productivity tools that automate mundane tasks you could easily do with free alternatives.
- Subscription-based “AI insights” services offering data analysis that can be performed using basic, no-cost software.
This proliferation of paper-thin products not only wastes people’s money but also distracts them from genuinely valuable tools that could make a meaningful impact on their work or personal life.
AI Hype: Recognizing Fool’s Gold in the AI Landscape
The dot-com era’s downfall was hastened by several warning signs that are re-emerging in today’s AI gold rush:
- Hype Without Substance
During the dot-com boom, buzzwords like “e-commerce” and “click-through rates” dominated pitches, often without any real business plan behind them. Today, “next-gen,” “disruptive,” and “game-changing” are plastered across AI products. If a tool relies solely on flashy marketing and can’t clearly demonstrate its tangible benefits, it’s a red flag. The focus should be on measurable ROI, not vague promises. - Lack of Transparency
Many AI products operate as black boxes, obscuring how they work. This is eerily similar to the opaque metrics of the dot-com era, where page views were touted as success indicators. Today, transparency about data usage, model training, and potential biases is critical. If a company can’t explain what its AI does and how it does it, that’s a signal to steer clear. - Superficial Niche Applications
The market is flooded with “AI-powered” tools for niche tasks, like generating basic social media posts or automating mundane workflows. While AI can undoubtedly add value in these areas, many of these tools simply repackage freely available or low-cost solutions with an “AI” label, providing minimal added benefit. Beware of tools that offer only marginal gains at a premium price; genuine value creation should be the focus, not simply automation for automation’s sake. Ask yourself: does this tool truly leverage AI to provide something novel, or is it simply charging a premium for a readily available capability? - Influencer-Driven Hype
The dot-com era had tech “gurus”; today, we have influencers. But are they genuinely knowledgeable about AI, or are they simply capitalizing on the trend for personal gain? When evaluating their recommendations, ask yourself: what’s their expertise, and why are they promoting this product? The answer often reveals a focus on profit over substance.
Beware of Buzzwords: The “Digitalization” Trap in AI Hype
“If someone can’t explain it simply and clearly, it’s a good indication that you’re dealing with fluff rather than true innovation.”
Alongside the avalanche of AI hype-related jargon, one term that keeps cropping up is “digitalization.” It sounds sophisticated, as if it embodies the very essence of technological advancement. But dig a little deeper, and you might find it to be little more than smoke and mirrors. In theory, digitalization refers to transforming analog processes into digital ones—a concept we’ve been familiar with for decades. The shift from paper records to electronic files, or manual data entry to automated systems, is nothing new. So why is it being thrown around now as if it’s some revolutionary concept?
Pairing digitalization with AI has become a common tactic to make products sound cutting-edge. But ask someone pitching a “digitalization strategy” to explain what they mean in plain language, and you might find their answer convoluted or filled with buzzwords. It’s not your inability to grasp the concept; rather, it’s a sign that the term might be being used as a smokescreen. If the explanation leaves you more confused than informed, it’s likely because the term is being used to inflate the perceived value of a product without offering any real, substantive detail.
In a landscape flooded with jargon, keep your radar up for terms like digitalization. If someone can’t explain it simply and clearly, it’s a good indication that you’re dealing with fluff rather than true innovation.
It reminds me of a quote from one of my favorite parody videos:
“We’re using the latest technology to develop tools to allow businesses to connect to global solutions.”
Focus on Real-World Value Amidst AI Hype: From Grand Visions to Everyday Use
Amidst the overwhelming AI hype, it’s crucial to separate the buzz from genuine value. While many products merely capitalize on the excitement surrounding AI, its true potential lies in practical, down-to-earth applications that enhance daily life. Beyond groundbreaking advancements like drug discovery, AI is already making a significant impact in everyday tasks. For instance:
- Enhanced Personal Productivity: Tools like Notion AI and Grammarly’s writing assistant integrate seamlessly into everyday tasks, offering valuable assistance in drafting emails, summarizing notes, or proofreading documents.
- Smart Home Devices: AI-driven voice assistants like Google Assistant or Amazon Alexa make life easier by automating routine tasks, from setting reminders to controlling smart home devices.
- Budgeting and Financial Planning: Personal finance apps use AI to analyze spending patterns, suggest budgeting strategies, and alert users to potential issues, helping people manage their money more effectively.
These practical applications show that while there is plenty of noise, AI also offers real solutions that enhance productivity and simplify tasks.
Betting on AI’s Future—Wisely
Despite my frustration with the fluff surrounding the AI industry, I’m betting my entire career on its potential. But I’m also cautious. I see too many products that are little more than a polished UI over an existing model, ready to collapse under the slightest scrutiny. Just like the dot-com crash cleared the way for genuinely valuable companies to thrive, I believe the same will happen with AI. The hype will fade, the bubble will burst, and what remains will be tools and solutions with real, lasting value.
Let me be clear: I don’t think the AI boom is identical to the dot-com bubble. The technology is far more mature, and the major players—tech giants like Google, Microsoft, and OpenAI—have a much deeper understanding of the underlying science. The investing landscape has also evolved significantly since the 90s. Institutional investors are more cautious, and established companies approach R&D with a sharper focus on strategic, long-term gains rather than speculative, short-term bets.
The biggest risk, in my view, lies with startups (which, let’s be honest, is always the case) and the individual consumer. Many of these small ventures are trying to carve out a niche without a sustainable business model, and everyday users are often swayed by polished marketing into paying for tools that may not deliver real value.
Let’s Discuss:
What red flags do you see in the current AI boom? How do you determine if a tool is worth your time and money? Share your thoughts below. Let’s have an honest discussion about navigating this AI gold rush and finding the true nuggets of value amidst the noise.
Note: AI tools supported the brainstorming, drafting, and refinement of this article.
A seasoned IT professional with 20+ years of experience, including 15 years in financial services at Credit Suisse and Wells Fargo, and 5 years in startups. He specializes in Business Analysis, Solution Architecture, and ITSM, with 9+ years of ServiceNow expertise and strong UX/UI design skills. Passionate about AI, he is also a certified Azure AI Engineer Associate.
