(highlight:: Organizations Are a Construct and AI Will Atomize Them
Summary:
The future will witness a significant shift where organizations will be viewed as mere constructs, and the marketplace will not be limited by the boundaries of a company.
Tasks will be atomized, focusing more on specific work components or experiences rather than on specific individuals or roles within organizations. AI will play a crucial role in this atomization process by performing tasks more efficiently than humans.
This transformation will lead to the breakdown of human-made boundaries such as job roles and organizational structures, moving away from the current monolithic approach to work and paving the way for a more decentralized and agile work environment.
Transcript:
Speaker 1
I fundamentally think that this shift is going to accelerate the knowledge and idea that organizations as a construct are just constructs But my point is the marketplace will not be Ultimately constrained by the walls of our company. It will be just like it is now when I say to the ready, we need an instructional designer. Anybody know how to do that? And everybody goes no. And then it's like, cool. Should we get a consultant? Should we hire a partner? Should we go on up work? I don't know. Like AI will be able to do that work in just a month. Much better way than we do it now. So like, I think on the one hand, everything will become much more atomized where it's not like I need this person. It will be like, I need this piece of work or this kind of experience or this specific moment and on the other side there will not be containment inside of people roles organizations, Etc. Like just a lot of those human made boundaries will be brought down, which is just sort of an inversion of how things work right now, which is like monolithic jobs in monolithic orgs. It's just like an unbundling and an atomization that we can't do now because of our little human brains.)
- Time 0:30:07
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(highlight:: Impact of AI on Industrial v.s. Evolutionary Organizations and Enabling the Living Wiki
Summary:
AI applied to industrial era organizations may lead to negative outcomes due to a cost-focused perspective and lack of adaptation to complex systems.
In contrast, applying AI to evolutionary organizations, which function as complex adaptive systems, has the potential to enhance transparency, manage information effectively, and enable a more collaborative and intelligent work environment. The current limitations in managing complex systems through traditional documentation are highlighted, illustrating the need for AI to unlock the full potential of organizational evolution and transformation.
Transcript:
Speaker 2
I think a lot of the anxiety around AI and automation and what that could mean is because people are looking at the application of AI into industrial era OS organizations. Because that's what most people know and they can see the writing on the wall. These organizations generally see people as cost and if there's ways to get rid of the people, then they're gonna do it. And I think there's lots of other things going on there where AI being applied to industrial era OS is just going to be bad in lots of different ways, including bad for the organization, I think. I think an industrial era OS applying AI is going to go faster into irrelevance. What I'm excited about is applying AI into evolutionary organizations. Organizations that are already trying to act like a network, like a truly complex adaptive system, and are actually being let down by our lack of tooling. Like we do a lot of talking about how important transparency is, but I don't know that we have a great explanation or solution to how do you manage all of that information that you're making Transparent. How do you make sense of it all? And I think AI in one way could be a huge unlock for that. So I'm very curious about what it looks like for AI to enable this future of work that we actually talk a lot about and have to do some hand-waving around because we don't have that technology To actually bring to life what we have in our brains.
Speaker 1
Yeah. I mean, I don't know if this has been your experience, but we call level five the neural network because the idea is that there are all of these connections that are being made and there's Not a triangle shape where the top is making those connections or holding and doling out the information, but that there is a level of intelligence that is becoming ever better and stronger And more refined and added to. I have been in more than one large-scale transformation project where the visualization of the evolution the OS has been trash. Where the clients were like, how can we know and see what we've tried and then what's happened and what that means and understand both the explicit outcomes of that but also what the inputs Were to that and blah, blah, blah, blah. I'm like, let me make you a pitch deck with some sticky notes on it. Like that's not good. Like we live in complex systems that live, and then the systems that we have to document them and to draw from, and to like have an archive are not living. They are complicated dead systems that are only as good as the living inputs to them. And that will go away and I truly cannot wait.
Speaker 2
Yeah, it's like we have created a more beautiful and lush forest. And instead of me being able to really just take your hand and stand on this hill and we'll look at it together, I have to break off a branch and give it to you and do a 35 minute presentation About where this came from. And it's not really quite the same experience.)
- Time 0:33:10
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(highlight:: Continuous Evolution and Documentation in Complex Systems
Summary:
Level five, or the neural network, in large-scale transformation projects signifies continuous improvement and intelligence growth without a hierarchy; however, visualizing this evolution in operating systems often falls short in depicting the journey comprehensively.
The challenge lies in representing both the explicit outcomes and the inputs of the complex systems effectively, as traditional documentation methods like pitch decks with sticky notes fail to capture the dynamic nature of these systems.
Transcript:
Speaker 1
Yeah. I mean, I don't know if this has been your experience, but we call level five the neural network because the idea is that there are all of these connections that are being made and there's Not a triangle shape where the top is making those connections or holding and doling out the information, but that there is a level of intelligence that is becoming ever better and stronger And more refined and added to. I have been in more than one large-scale transformation project where the visualization of the evolution the OS has been trash. Where the clients were like, how can we know and see what we've tried and then what's happened and what that means and understand both the explicit outcomes of that but also what the inputs Were to that and blah, blah, blah, blah. I'm like, let me make you a pitch deck with some sticky notes on it. Like that's not good. Like we live in complex systems that live, and then the systems that we have to document them and to draw from, and to like have an archive are not living.)
- Time 0:34:44
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