Such an incredibly important post, thank you for laying this out so clearly.
I have been talking about this for the past 18 months on my podcast (and almost everywhere else).
Individual productivity became a new vanity metric, and told us nothing about how teams, departments, or organizations were doing. One (human) cog going 10x while others go 1-2x means something is going to break.
You have to be measuring AI readiness and maturity with different attributes as you go from individual to institution.
Only two things I would add are 1) we need responsibility and human-centricity by design to mitigate risk and build things properly the first time, and 2) this also points to the importance of capitalizing on the institutional collective intelligence for making better decisions and architecting strategic work.
:) I’m solo nowadays but over 25 years of witnessing enterprise transformation challenges. AI is the disruptive wake-up call as well as the catalyst to reimagine work itself.
Thank you for this article. What stood out most for me and how I interpret this is that even more important than an AI strategy, companies need an infrastructure that drives, sustains and ensures consistent adoption of AI. I view this as part of what normally would be a change management strategy. Also, thank you for including the critical component of bias! I feel like the topic used to be a central part of most conversations around AI but it has slowly disappeared as the race to proliferate has taken center stage.
To add to that, in the software value chain, AI is squeezing the layers between talent, skills, capabilities and end business outcome.
Since we can now deliver software at a software speed, re-wiring the organization is the key institutional change required, and this is primarily required for non-software businesses.
Huge difference: electricity could not change the production process' organisation but AI can do that. AI brings not only new technology as electricity did but also new organisation of production process. The challenge: would it be adopted by the human-led production system or must it be changed to AI-lead system?
Good article and spot on about institutional redesign. The irony for me and one thing missing here, is the obvious - that institutions rarely lead these shifts. Individuals usually adopt the tools first and therefore yes, create chaos and the drag the Institutions kicking and screaming into adoption. I went from Private sector to public sector recently where it’s all too apparent that individuals discover the capability, then force institutions industrialize it by causing this chaos of jevons paradox…
Such an incredibly important post, thank you for laying this out so clearly.
I have been talking about this for the past 18 months on my podcast (and almost everywhere else).
Individual productivity became a new vanity metric, and told us nothing about how teams, departments, or organizations were doing. One (human) cog going 10x while others go 1-2x means something is going to break.
You have to be measuring AI readiness and maturity with different attributes as you go from individual to institution.
Only two things I would add are 1) we need responsibility and human-centricity by design to mitigate risk and build things properly the first time, and 2) this also points to the importance of capitalizing on the institutional collective intelligence for making better decisions and architecting strategic work.
Thanks Rob…agree. Most of the alternate arguments for AI in knowledge work today are made by solo practitioners…
:) I’m solo nowadays but over 25 years of witnessing enterprise transformation challenges. AI is the disruptive wake-up call as well as the catalyst to reimagine work itself.
Thank you for this article. What stood out most for me and how I interpret this is that even more important than an AI strategy, companies need an infrastructure that drives, sustains and ensures consistent adoption of AI. I view this as part of what normally would be a change management strategy. Also, thank you for including the critical component of bias! I feel like the topic used to be a central part of most conversations around AI but it has slowly disappeared as the race to proliferate has taken center stage.
Very good insights.
To add to that, in the software value chain, AI is squeezing the layers between talent, skills, capabilities and end business outcome.
Since we can now deliver software at a software speed, re-wiring the organization is the key institutional change required, and this is primarily required for non-software businesses.
Huge difference: electricity could not change the production process' organisation but AI can do that. AI brings not only new technology as electricity did but also new organisation of production process. The challenge: would it be adopted by the human-led production system or must it be changed to AI-lead system?
Good article and spot on about institutional redesign. The irony for me and one thing missing here, is the obvious - that institutions rarely lead these shifts. Individuals usually adopt the tools first and therefore yes, create chaos and the drag the Institutions kicking and screaming into adoption. I went from Private sector to public sector recently where it’s all too apparent that individuals discover the capability, then force institutions industrialize it by causing this chaos of jevons paradox…