This thought-provoking blog explores how AI has transitioned from being a groundbreaking innovation to a commoditized product in an oversaturated market. It questions whether current AI advancements are truly impactful or simply iterative releases aimed at profit. From brand battles between OpenAI, Anthropic, and Google to the lack of real-world utility like handling physical labor, the blog challenges readers to reflect: Is AI still special, or are we just stuck in a cycle of digital convenience? With compelling examples and references, the piece encourages a necessary pause to reassess AI’s purpose in everyday life.
Asma Syeda
Imagine a future where we don’t just use AI — we shop for it like any other product. Just like we have brand loyalties for phones, watches, and cars, soon we’ll have AI brand preferences.
Some of us swear by Apple, others by Samsung. Some people won’t drive anything but a BMW, while others are die-hard Tesla fans. Now, imagine walking into a store and choosing an AI assistant the same way:
“Which AI gives me the best deal — Claude 5, ChatGPT 6, or DeepSeek?”
“Which AI understands me better — Anthropic’s model or OpenAI’s?”
“Which AI aligns with my values — Google’s Gemini or an open-source alternative?”
Welcome to the AI commoditization era — where AI is no longer an optional strategic tool for businesses but an everyday necessity. What was once an exciting innovation is now a market flooded with similar-sounding products competing for dominance.
The real question is: Are we advancing AI, or just iterating for the sake of profit?
The Generative AI Arms Race: Too Many Models, Not Enough Impact
Every month — sometimes every week — a new AI model is released, claiming to be:
More intelligent
More powerful,
More context-aware
More human-like
But how different are they?
Take OpenAI’s ChatGPT, which is marketed as the leader in generative AI, yet often frustratingly cautious, prone to hallucinations, and evasive in responses.
Then there’s Claude from Anthropic, an AI built on “ethical alignment.” But sometimes, that translates into avoiding tough questions altogether, making it feel more like an AI nanny than an assistant.
DeepSeek AI — a Chinese competitor that claims to be faster and more capable, but at its core, is yet another LLM competing in an oversaturated space.
And Google’s Gemini (formerly Bard) — which, despite Google’s vast AI resources, continues to underdeliver compared to OpenAI and Anthropic, playing catch-up instead of leading.
Even Meta’s Llama and other open-source LLMs enter the fray, but most of them offer marginal improvements, not game-changing breakthroughs.
At this point, the AI market isn’t about intelligence anymore — it’s about who can market their model better.
But AI Still Can’t Do What We Actually Need
For all the hype around AI revolutionizing work, it still can’t do the real tasks humans hate doing.
While AI excels at automating cognitive work — generating reports, summarizing texts, and predicting trends — it still falls short when it comes to tangible, hands-on tasks that consume much of our daily lives. Laundry, dishwashing, folding clothes, and cooking — all tasks that people would love to offload — remain outside AI’s reach.
Rather than another chatbot that refines search queries or summarizes emails, the real breakthrough would be an AI-powered home assistant that physically alleviates human labour — a system that doesn’t just process information but actively interacts with and changes the world around it.
For all of AI’s advancements, we are still firmly rooted in digital automation, where AI augments knowledge work but leaves the physical burden entirely on humans.
AI Isn’t Special Anymore — And That’s a Problem
AI used to be a strategic asset — a technology that provided businesses with a competitive advantage. Today, it’s a baseline expectation.
If a company doesn’t use AI, it’s outdated.If a professional doesn’t leverage AI tools, they’re seen as inefficient.If an AI model isn’t released every few months, it’s considered obsolete.
We’ve entered an era where AI is no longer a luxury — it’s just another product on the shelf.
The real problem? AI is no longer about innovation. It’s about mass production.
Just as electricity became a commodity, AI is following the same path. But there’s a crucial difference:
- Electricity enables everything — from industries to homes, making life easier.
- AI, as it stands today, mostly enables PowerPoint presentations, chatbots, and automated emails.
The question we should be asking isn’t, “Which AI model is best?”
It’s “Is AI actually making life easier in ways that matter?”
Where Are We Headed? The Future of AI
At the rate we’re going, AI models will be releasing every hour.
But is this progress — or just noise?
What happens when: Every AI claims to be “state-of-the-art,” but they all feel the same?We have too many AI models, but none that truly revolutionize human life?
Companies start treating AI assistants like streaming subscriptions — constantly switching for the best price and features?
The AI race has shifted from intelligence to branding. Instead of focusing on truly transformative AI applications, we’re locked in a corporate battle of who owns the most market share.
What we should be focusing on:
AI that can actually handle physical labor, not just digital work
AI that improves human well-being, not just corporate efficiency
AI that doesn’t just get smarter, but gets more useful
If we continue on this path, AI will stop being a breakthrough and start being just another thing we consume. And that would be the biggest failure of all.
Final Thought: Are We Moving Too Fast?
The AI hype cycle is spinning faster than ever. New models, bigger models, better models — but are they truly better, or just more of the same?
Are we moving toward true innovation, or just fueling a marketing war between AI giants?
If we don’t pause and rethink AI’s role in our lives, we risk creating a world where AI is everywhere, but impact is nowhere.
Because in the end, if AI can’t even fold our laundry, what have we really achieved?
What do you think? Are we moving too fast in the AI race? Or is this the natural evolution of technology? Let’s discuss.
Additional Reference and Resources
- AI Transofrmation Playbook by Andrew Ng https://assets.landing.ai/content/uploads/2018/12/AI-Transformation-Playbook-v8.pdf
- https://medium.com/mev-shoaib/ai-product-management-19e344f79d4e
- https://ai.gopubby.com/why-ai-cant-do-your-laundry-90d1011ebbe1
- Why Robotics Startups Don’t Use Deep Learning (Think Autonomous, 2022)
- https://medium.com/data-science-in-your-pocket/deepseek-is-highly-biased-dont-use-it-2cb0358647f9
- https://every.to/chain-of-thought/we-tried-openai-s-new-deep-research-here-s-what-we-found?utm_source=tldrnewsletter
- https://arstechnica.com/ai/2025/02/are-ais-getting-dangerously-good-at-persuasion-openai-says-not-yet/?utm_source=tldrnewsletter
- https://medium.com/towards-data-science/7-types-of-ai-risk-and-how-to-mitigate-their-impact-36c086bfd732
#Machine learning #Automation #Artifical Intelligence #humanify AI