Not because of tools, but because firms haven’t reorganized around them.
Some companies even try with Data & AI Literacy programs, but, again, nothing changes because literacy isn’t about knowing what a large language model is.
It’s about changing how people make decisions, use AI to become more efficient, how data is leveraged to make decisions.
That’s the hard part most organizations skip.
My colleagues Nina Stefels and Rozaliya Khafizova shared how to craft programs that work.
Cory Doctorow gives a beautiful explanation, backed by research, of how organizations come to be completely overrun with bullshit because love of corporate bullshit is correlated with bad judgment.
The antidote? Cut to the chase. Skip the hype. Tell it like it is. Keep it simple.
Input: Makes me happy that I support Kagi everytime I see something like this
Output: Moments like this remind me exactly why I’m a proud supporter of Kagi. It’s incredibly rewarding to see this kind of impact and innovation. Grateful to be part of the journey! 🚀 #Kagi #Innovation #CustomerSuccess #Privacy
“When schools began treating Office proficiency as a prerequisite for adult life, instead of focusing on writing and thinking, we reached peak absurdity.”
This week, The Economist published an article on why AI is NOT increasing productivity
The killer quote is
All this signals a deeper flaw in the argument that ai is powering a productivity boom. Such improvements are usually made not just when workers use a new tool more often, but when firms reorganise production around it
My colleague Fanny Kassapian wrote about this challenge: reorganize your operating model or fail to gain any value from your data and AI initiatives.
