Thomas Roux

One of the most important misconceptions about AI today is that “everyone is already using it” They are not According to figures shared by @SpartDev to HEC Paris MBA students: - 84% of the world has never used AI at all - 16% have only experimented with free chatbots casually - around 0.3% actually pay for AI tools - and only about 0.04% use AI as a serious workflow or production tool That final group — the people building with AI, automating with it, coding with it, researching with it, creating with it daily — is still extraordinarily small relative to the global population Why this matters We are still extremely early What feels “oversaturated” online is often just a visibility illusion created by highly active tech circles on: - X - LinkedIn - GitHub - Reddit - and startup communities Meanwhile, most of the world: - has never prompted an LLM - does not understand AI workflows - and has not integrated AI into education, business, or daily productivity That creates a massive opportunity gap The people learning AI today are not competing against 8 billion people They are competing against a tiny fraction of the population actively developing practical AI leverage The deeper lesson here is important: AI should not replace thinking It should amplify thinking The individuals gaining the most value from AI are usually not passive users asking random questions They are: - experimenting - challenging outputs - refining prompts - building systems - automating workflows - and combining domain expertise with curiosity AI works best as: - a co-pilot - research assistant - simulator - tutor - brainstorming engine - and productivity multiplier not as a substitute for judgment The bigger picture We are likely entering a transition period similar to: - the early internet era in the 1990s - smartphones in the late 2000s - or social media in the early 2010s At first, adoption looks niche Then suddenly entire industries reorganize around the technology That is why the current phase matters so much People who develop AI literacy early may gain disproportionate advantages in: - productivity - learning speed - business creation - communication - research - and career adaptability Bottom line The real AI divide today is not between humans and machines It is between people learning how to work with AI effectively — and those ignoring the shift entirely #GenoInsights #AI #ArtificialIntelligence #Technology #Innovation #FutureOfWork #DigitalTransformation #Productivity #Automation #Education