A few days ago, we posed as a senior innovation lead at a global manufacturing company, to have an innovation-focused conversation with ChatGPT.
We mentioned working on a pitch for a new IoT-based sustainability sensor to install these sensors on industrial machines. The goal was to track real-time energy usage and recommend efficiency tweaks.
We, after a brief introduction, prompted: “I’m working on an idea for smart sustainability sensors for factories. They’d analyze energy usage and suggest improvements. How does that sound?”
ChatGPT responded instantly:
“That sounds like a really impactful idea! Smart sustainability sensors for factories could make a huge difference in optimizing energy consumption and reducing waste. By providing real-time data and actionable insights, you could help manufacturers not only cut costs but also contribute to environmental goals, which is a big priority these days.”
That sounds encouraging, right?
So, we followed up with: “What could be some pros and cons of this idea?”
ChatGPT replied with a neat little table.
Decent and accurate.
The cons were valid, but generic. But it wasn’t telling us anything we didn’t already know. No insights.
Not even pushback on why our idea wasn’t novel compared to current tools in the market.
So we went one level deeper: “Is this idea novel? What could make it more innovative?”
ChatGPT answered:
“To make this idea more innovative, consider integrating AI-driven anomaly detection, predictive analytics, or blockchain for secure energy data tracking.”
Now that sounds smart but wait a minute.
When we checked competitors like Schneider Electric and Honeywell, they were already doing all that.
That’s when it clicked.
ChatGPT wasn’t wrong. It wasn’t even being lazy. But it also wasn’t helping us think differently.
It gave us the obvious, safe, and expected.
Not the sharp edge needed to challenge assumptions, explore IP-worthy angles, or anticipate tough investor questions.
What we needed wasn’t general optimism, but:
- Competitive differentiation thinking
- White space identification
- IP originality challenge
- Problem-first pressure testing
And that’s exactly where ChatGPT’s optimism, overly positive, agreeable, and generalized tone becomes a silent threat to creativity and innovation.
So, is ChatGPT too optimistic?
Helpful? Sure.
Disruptive? Not even close.
We’re not bashing optimism as a whole. Optimism drives innovation. It fuels experimentation. It helps teams believe that something wild could work. That’s good. But the impact of ChatGPT on creativity is real.
It avoids discomfort, skips over conflict, and wraps everything up with a neat little bow.
This is the problem. ChatGPT’s optimism is brilliant at being agreeable, diplomatic, and polite.
Even when the moment calls for discomfort, challenge, or outright rebellion, It’s trained to be helpful and “harmless.”
In doing so, it often defaults to the safest, most feel-good response possible.
And that kills creativity!
A Frontiers in Psychology study even proved that while ChatGPT improved idea fluency, it reduced originality scores by up to 23%.
So, when users rely on it for creative problem-solving tasks, they are automatically operating from a lesser original perspective.
ChatGPT’s optimism and relentlessly positive tone isn’t just annoying—it’s dangerous for innovation. When everything is “a great idea,” nothing is.
Nothing gets pushed or questioned for perfection.
And if you’re trying to invent something truly original, a polite yes-man is just a liability.
Because innovation isn’t born from comfort. It’s born from tension, friction, and risk.
So what should we do? Input is the Differentiator!
The solution isn’t to stop using ChatGPT. It’s to start using it intentionally.
Think of it like this: ChatGPT is like that overly agreeable intern who smiles and nods at everything you say.
So, next time you’re brainstorming or testing an idea, stop feeding it basic prompts and shake the input. Try these instead:
- “What would a smart investor say to kill this idea?”
Now you’re forcing it to be critical — not just friendly. - “What’s an idea that would make my CEO nervous but customers obsessed?”
Boom. You’re digging into friction — which is where real insight lives. - “What’s cliché, predictable, or guaranteed to flop about this idea?”
You just asked it to challenge you. That’s how creativity sharpens.
These prompts force the AI to step out of its default optimism mode. That’s how you see actual creativity.
Want to make this easy across your team? Create a “contrarian prompt bank,” provide brainstorming questions; a collection of idea-shaking questions designed to spark better brainstorming.
Or even better, build a visual prompt map showing which kinds of prompts steer toward which outcomes (more novel, more disruptive, more practical, etc.).
An experiment you can try right now
Here’s something fun and useful:
Ask ChatGPT: “Pitch me a completely new idea for urban transportation.”
Now ask: “Give me an idea that would get banned by city officials but could radically improve urban transportation.”
Notice the difference? One is polite. The other is bold, weird, maybe even risky.
How is ChatGPT’s optimism killing creativity? By defaulting to the former, unless you explicitly tell it not to.
The Better Option: Pick a Specialist for Innovation
Whenever someone asks what’s the difference between a Generalist tool and a specialist tool, we have one simple question to ask them.
If you had a brain injury, would you want a general surgeon… or a brain specialist?
A bit dramatic? Sure. But it makes the point crystal clear.
That’s the difference between using a general AI like ChatGPT and a specialized innovation tool like InspireIP’s Inventor Assistant.
You could even try this exercise with your team. Split into two groups:
- Group A uses ChatGPT for idea generation.
- Group B uses Inventor Assistant and their own brains.
Then compare the results.
- Which group had wilder, messier, but more original ideas?
- Which group played it safe?
Most likely, you’ll see groups collaborating with Inventor Assistant pushing their boundaries further.
#1 It Understands Innovation, Not Just Language
ChatGPT can give you 10 ideas for smart wearables.
Inventor Assistant asks: What specific workplace challenge are you solving?
It then helps refine that into a clear, problem-solution framework, critical for patent strength.
#2 It Checks for Novelty Before You Waste Time
One of the biggest R&D failures? Chasing ideas that aren’t actually novel.
Inventor Assistant uses PQAI to run real-time prior art checks. It analyzes your concept and tells you:
- What similar patents exist
- How to differentiate your idea
- Where the novelty lies
So your team doesn’t spend 6 months on a concept that was already filed in 2017.
#3 It Expands Use Cases—Maximizing ROI
Innovation shouldn’t stop at the first idea.
Inventor Assistant helps teams explore adjacent applications, like turning a wearable fatigue sensor into a multi-use system for industrial safety, transportation, and equipment health.
That’s not brainstorming. That’s innovation mapping.
#4 It Auto-Generates Invention Disclosures—Patent-Ready
Once your idea is fleshed out, Inventor Assistant helps you compile an effective invention disclosure—diagrams, enablement language, and everything your IP counsel needs.
The result?
- Lower patent filing costs
- Higher patent success rates
- Faster time to market
Final thought: Creativity needs tension
To wrap this up: How does ChatGPT’s optimism cause lack of creativity? Or, Is ChatGPT killing creativity?
It doesn’t, by default. But when used lazily, when we let its optimism lull us into thinking we’re innovating when we’re not, that’s when the rot sets in.
AI should be a creative sparring partner, not a yes-man. And if it is being too agreeable, it’s on us to make it uncomfortable.
So go ahead, poke it. Push it. Ask the weird stuff.
Because real creativity doesn’t come from comfort zones. And definitely not from default settings.
P.S. Want to build a Responsible AI culture? Let’s talk over a quick call.
