How AI Reasoning Models Could Revolutionize Market Research
admin2025-02-03T15:31:15+00:00It feels like the last few months have pushed AI companies into an all-out “lunar race” for AI dominance, each trying to out-announce the other. The biggest names in the field have been racing to keep up with each other’s new features, from faster models to visual inputs and video generation, until Deepseek disrupted everything in an entirely new way.
Over the past year, I’ve been exploring the best ways to integrate AI into my work and help others in my organization make the most of these new tools. More often than not, AI-generated content, whether text or images, wasn’t polished enough to replace human effort. However, I found that when treated as an apprentice handling the drudgery, AI could be an invaluable asset. For those who embrace this concept, it can serve as a diligent editor and researcher that complements and enhances human processes, as long as you don’t rely on it for actual inspiration.
OpenAI recently announced its fast new reasoning model, O3-Mini, optimized for high-level scientific and coding applications. This is undoubtedly a monumental achievement, but what practical impact does it have on our everyday work? I admire scientific research, but I’d much rather have AI help me gain meaningful insights for making better day-to-day decisions, like choosing the best password manager for my organization.
So, I gave this new reasoning model a challenge:
Research competitors that offer enterprise-level password management and protection tools, comparing features, price, security, and other relevant factors. Then, provide a summary of the research and a final recommendation.
Here’s the full interaction with ChatGPT if you want to dive into it. The analysis was surprisingly insightful, far better than what previous models would have produced, and it strongly favored 1Password. That was a bit frustrating personally, as I had previously reviewed it and chosen a different solution ;-).
I tested a few more market research queries (here’s another example comparing cloud edge solutions), and with this new model, the results were significantly better than before, possibly making AI a real threat to human analysis. Could AI disrupt this field? In my limited world, it already is. And while smart developers continue to find incredibly useful applications, for me AI is finally becoming more than just a diligent assistant. It is transforming into an indispensable tool for everyday decision-making. Could this raise ethical concerns for the future? Possibly, but for now, it’s just inspiration for a future LinkedIn article.
This post was originally posted on Linkedin, here.