One small step in tech, one GIANT leap in marketing
The Illusion of Progress
The AI industry feels like déjà vu. Everyone’s shouting about “revolutionary breakthroughs,” but if you look past the noise, it’s the same old trick: promise the moon, deliver a bornfire. Billions have been poured into startups claiming they’ve built “autonomous intelligence,” yet half of them can barely automate a simple workflow without a human babysitting in the background.
Every funding round, a new buzzword popped up. First year it was “AGI.” Then came “Agentic AI” and "MCP server". Now it’s “Self-Learning Systems.” Each term sounded smarter than the last, but none actually worked as advertised. The tech didn’t evolve as fast as the vocabulary did.
First investors pounded billions into this revolutionary new tech. Then investors, realising their losses and desperate not to lose more or miss the next big thing doubled down, pouring billions of dollars into the AI industry. Credit where it’s due: AI has come a long way. But it’s still in the R&D stage. AI cannot replace humans or think for itself or is suitable for standalone business use. But that doesn’t maximize investor returns or help secure the next round of funding. So what did the AI industry do? They implemented AI into everything just for the sake of it and delivered half-baked products. All AI companies had to do was mention “AI” and sprinkle in a few buzzwords in their pitch deck. It wasn’t innovation, it was FOMO and marketing genius, dressed up as the second coming of the Lord himself.
The echo chamber built itself. Thanks to all the “new technological advancements” now fake hype and false promises spreads faster than wild fire. Founders realised this and hyped progress to raise funds. Investors hyped it further to justify their “gambles”. Media amplified the cycle because “AI is taking over the world” and “AI will take your job, wife and kids” sells more clicks than “AI still kinda struggles with the most simple tasks.” We’ve all been guilty of buying into the illusion thinking each new model release would mark the dawn of true intelligence. But here we are, in 2025, and most systems still hallucinate, still break under pressure, and still need humans to clean up their mess. The so-called AI Gold Rush looks more like a speculative fever dream than a technological revolution.
The Buzzword Economy: Selling Hype as Innovation
Somewhere along the line, the AI world stopped being about breakthroughs and started being about branding. You can almost picture the boardrooms executives nodding at PowerPoint slides full of words like “agentic,” “self-adaptive,” and “intelligent orchestration,” all while the product is a glorified autocomplete. It’s wild how fast marketing teams learned to outshine engineering departments. The story mattered more than the substance. The flashier the claim, the fatter the check.
“Agentic AI” became the new “blockchain.” Everyone wanted to say they had it few could explain what it actually meant. It’s a masterclass in corporate storytelling: take something half-functional, sprinkle buzzwords, and suddenly it’s “the future of cognition.” Behind the scenes, engineers roll their eyes, fully aware the system’s not as autonomous as the press release claims. But PR doesn’t care about technical truth it cares about investor excitement.
Let’s call it what it is: a hype machine. Investors wanted vision, not reality checks. Founders learned that exaggeration sells better than incremental progress. And the result? A trillion-dollar industry powered by beautifully written fiction. When words like “self-improving” or “sentient” become business strategies, truth gets lost in translation. Real innovation takes time but in the AI arms race, no one wants to admit that. So we keep buying into slogans, mistaking motion for progress, and acting surprised when the next big thing turns out to be the same old vaporware in a shinier suit.
Cracks in the System: Even the Giants Are Struggling
Here’s the thing if the biggest names in AI can’t get their own house in order, what chance do the rest of us have? It’s becoming painfully clear that even the so-called “leaders” of artificial intelligence are fumbling basic integration. These companies have billions in funding, armies of engineers, and access to the most advanced models on Earth yet half of them can’t even use their own tech effectively. The irony is almost poetic: the same firms preaching “seamless automation” still rely on manual support, delayed responses, and overworked human staff just to keep things running.
Take OpenAI the very company that ignited the AI boom. Their products? Undeniably impressive. ChatGPT changed the game, no question. But the reality behind the curtain tells a different story. When I subscribed to GPT Go, the amount was deducted instantly, but the subscription never activated. No refund. No resolution. So I reached out to their customer support or rather, their AI-powered chatbot and provided every single detail it asked for. I was assured it’d be resolved within 48 hours. Two days later? Nothing. I reached out again, and the response was the same polite copy-paste: “Please wait another 24–48 hours.” It’s been days since, and the issue still hangs in limbo.
Think about that. A company valued in the tens of billions, with the world’s most advanced AI systems, couldn’t automate a simple customer service process something as basic as activating a subscription and issuing a refund. If the pioneers of AI can’t make their own AI work internally, what does that say about the tech’s maturity? It’s like watching a chef burn their own signature dish. The message is clear: this industry is still more about optics than operational reality.
And it’s not just OpenAI. Across the board, we’re seeing companies touting “autonomous customer experiences” while their bots loop users in endless circles of “I’m sorry, I didn’t catch that” and “Please provide your details again.” These aren’t isolated hiccups they’re symptoms of a larger truth. AI, right now, is fun, flashy, and full of potential, but it’s still in the R&D stage. It’s experimental tech being force-fit into business-critical systems that demand reliability, nuance, and empathy three things today’s AI just doesn’t consistently deliver.
What’s happening now is a massive overpromise cycle. Startups build B2B AI tools on top of models not designed for complex real-world scenarios. They pitch them as ready for enterprise deployment, but under the hood, these systems are fragile prototypes prone to confusion, inconsistency, and failure. It’s all smoke and mirrors: fancy dashboards, “productivity charts,” and metrics that look great in investor decks but fall apart in daily use.
AI hasn’t arrived. It’s still finding its footing. What we’re calling automation today is really a collection of stitched-together demos wearing a suit and tie. Until AI can actually handle something as simple as fixing a billing issue without looping endlessly, we need to stop pretending it’s ready to replace human reliability. The hype is miles ahead of the technology and deep down, even the giants know it.
The Cost of the Hype: What AI Broke
Remember when the internet was messy but at least human? Now it’s a landfill of synthetic slop. AI didn’t just sneak in; it bulldozed its way through blogs, news, and search results, leaving a trail of spam so thick you need a machete to find anything real.
Here’s the punchline: over half the internet traffic in 2025 isn’t even human. Yep, more than 50% is bots, according to Imperva’s 2024 Bot Traffic Report. Half. So while you’re scrolling, arguing with strangers, and doom-clicking headlines, odds are you’re just shadowboxing with scripts.
The fallout is everywhere. Misinformation spreads like mold in a damp basement. Deepfakes blur the line between fact and fantasy. Plagiarism isn’t even lazy anymore; it’s automated. And content saturation? It’s like trying to find a needle in a needle factory.
Even creativity feels tired. When every headline, blog, and video looks like it was spat out by the same beige algorithm, it all turns into white noise. The internet didn’t get smarter with AI. It got louder, cheaper, and way more annoying. This isn’t the web we built; it’s a never-ending loop of bot chatter and regurgitated fluff.
What Comes After the Crash?
Eventually, the hype bubble pops. Investors get cold feet. Suddenly, “disruption” isn’t sexy anymore it’s expensive. Money stops chasing every chatbot idea like it’s gold. Instead, people start asking uncomfortable questions like, “Does this even work without humans babysitting it?”
The industry quietly shifts. No more “AI will replace everyone.” Now it’s “AI, but with someone watching so it doesn’t catch fire.” Human oversight sneaks back in like the adult in the room after a wild house party. The gold rush cools off, and what’s left standing are the tools that actually help, not just impress VCs.
This isn’t the death of AI. It’s the death of the AI fairy tale. The curtain’s down, the smoke’s cleared, and surprise surpise - there was no wizard, only a bunch of marketing decks with AI buzzwords. Maybe the real intelligence wasn’t artificial. It was the marketing all along.