Everywhere you look, the narrative is the same: innovation begins and ends with AI/ML. Companies are desperate. They are pouring millions of dollars into integrations—often just to plug in a basic AI chatbot—simply to stamp an "AI-Powered" badge on their landing pages.
But if we strip away the marketing hype and look at the actual reality, a troubling question emerges: Where is the world-changing technology built by AI?
Outside of tech demos, the everyday consumer experience hasn't fundamentally shifted. Instead, the AI landscape currently looks like a modern gold rush, but with a twist:
The Only People Making Money Are Selling Shovels: Except for a select few selling hardware, infrastructure, or generative AI tokens, most companies are bleeding cash on AI.
The "Badge" Economy: Massive capital is being spent on optics and FOMO (Fear Of Missing Out) rather than tangible, revolutionary utility.
Missing Breakthroughs: We see incremental software updates, but we haven't seen a completely new, world-changing technology emerge that solves fundamental human problems better than traditional tech.
Are we investing in the next internet, or are we just funding the most expensive marketing campaign in tech history?
It's time to shift the conversation from how much we are spending on AI to what value it is actually delivering to the end-user.
🗣️ To my network of founders, developers, and tech leaders:
Are you seeing genuine, foundational innovation from AI in your sectors, or is the pressure to get the "AI badge" overshadowing real product value? Let's discuss in the comments.
Top comments (3)
I appreciate how you point out the tendency for companies to treat any AI/ML effort as automatic innovation, turning it into more of a badge than a strategic advantage. Have you encountered any concrete frameworks that help differentiate superficial AI hype from truly value‑adding implementations?
Hey Samod,
A lot of companies just throw an "AI-powered" tag on basic features to look cool, rather than actually offering something innovative.
That said, using AI for boring, everyday chores—like summarizing long meetings, taking notes, or pulling out action items—is actually where it shines best. It might not sound super exciting, but saving people from tedious admin work gives entire teams back hours of their day.
If you're looking for a good, widely used framework to separate real value from pure hype, check out the Gartner Hype Cycle:
Peak of Inflated Expectations: Where everyone gets super excited about flashy, hyped-up tech that might not actually solve a real problem.
Slope of Enlightenment: Where companies stop chasing shiny tools and focus on practical, everyday use cases that deliver actual ROI (like automating notes and summaries).
Another super practical approach is the Jobs to Be Done (JTBD) framework. Instead of asking "How can we add AI to this?", it forces you to ask "What specific headache are we trying to fix for the user?" If AI fixes a real pain point, it's worth building; if not, it's just a badge.
Thank you Gaurav, btw, I'm Samod from ZyVOP (zyvop.com), seems interesting platform