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If you had asked me even a year ago whether we would experience the rampant strides in AI that has made humans significantly more productive, more trusting of the technology and more willing to innovate as we march towards a more sophisticated AI, I would have my doubts.
In the last year, we have witnessed LLMs evolve and have seen the rise of Generative AI capabilities. Adoption rates with the improved technology are impressive. Here are some statistics from Hostinger:
- As of 2025, 78% of companies have adopted AI technologies, a significant increase from previous years.
- Out of 359 million companies worldwide, 280 million use AI in at least one business function.
- On average, companies are now using AI in three different functions, reflecting a noticeable increase since early 2024.
It’s safe to say that Global adoption of Generative Artificial Intelligence (GenAI) has exploded into mainstream, transforming how individuals work, create, and interact with technology.
But how useful is this adoption? While the technology is saving people and companies considerable time and money, what are the opportunity costs of this transformation and will it inflict sustainable negative downstream impacts?
For those that have tinkered with Gemini, Claude, ChatGPT, there are numerous signs that technology still needs time to remedy many of its hallucinations in order to be truly trustworthy. But more than this, the impact on human beings is now front and center.
What impact does this have on human cognition if humans were to become truly addicted to these technologies and acquiescence to machine outputs? Will the value of work collaboration disintegrate if what was once “brainstorming” defaults to “ask GenAI to provide me 10 of the best topics.”
The question of trusting the code that powers our applications and our systems also becomes paramount? Will the developers’ job change to ensure better governance? If so, how? And to what extent will we enable our digital infrastructures to be created by AI?
We are excited to welcome Jing Hu to Tech Uncensored. Jing bridges the gap between AI promises and reality. A former biochemist spent years in research, then another decade as a tech product leader before becoming a trusted AI journalist. Her Substack is 2nd order thinkers. What is trustworthy and useful AI? Are we jumping the gun in embracing these technologies? We’ll also discuss the cognitive impact from increased use of Generative AI and now more sophisticated chatbots and that impending cost to human connection.
