Latest / The DEX Show: A Show for IT Change Makers / 🐙 What the Octopus Can Teach Us About AI (w/ Steve Wunker)

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🐙 What the Octopus Can Teach Us About AI (w/ Steve Wunker) · The DEX Show: A Show for IT Change Makers

• 0:01
  Speaker 1: Welcome it, change makers to the deck show with Tim
• 0:05
  Speaker 1: Flower and Tom McGrath. Let's get into it.
• 0:09
  Speaker 2: Hallo, change makers.
• 0:11
  Speaker 3: It's Tom McGrath back for another sort of year's end
• 0:14
  Speaker 3: deck show. We're winding down. We've got an eye on
• 0:17
  Speaker 3: the holidays everybody, but no change to the schedule programming.
• 0:21
  Speaker 3: We've got another fantastic guest and I'm joined as ever,
• 0:23
  Speaker 3: bites Tim Flower. How are you doing to me? You
• 0:25
  Speaker 3: feel you feeling festive?
• 0:26
  Speaker 4: Staid.
• 0:26
  Speaker 3: There's a bit of snowfall out there at the moment.
• 0:29
  Speaker 2: Yeah, first measurable snow of the year. Be a nice
• 0:32
  Speaker 2: little view out the window. And fortunately, like we were
• 0:35
  Speaker 2: talking to Tom, I got a guy to come take
• 0:36
  Speaker 2: care of it. So it's it's nice when you're on
• 0:38
  Speaker 2: the inside.
• 0:40
  Speaker 3: He's a staring out of his window as this poor
• 0:43
  Speaker 3: gentleman is blowing around with his shovel. Picture of a
• 0:46
  Speaker 3: picture of decadence, Tim, And we've got we've got a wonderful,
• 0:49
  Speaker 3: wonderful guest today. He's a Steve Wonker. He's a managing
• 0:53
  Speaker 3: director of New Markets Advisors. That's a consulting firm that
• 0:57
  Speaker 3: works with twenty nine of a fortune five one hundred
• 1:01
  Speaker 3: and among his many distinctions in his career. Steve has
• 1:05
  Speaker 3: developed one of the world's first smartphones, which I'm going
• 1:07
  Speaker 3: to be asking him about momentarily, and worked across a
• 1:10
  Speaker 3: lot of different AI initiatives across the last twelve years.
• 1:14
  Speaker 3: He's an author. He's written hundreds of articles for places
• 1:17
  Speaker 3: like Forbes and Harvard Business Review, as well as for
• 1:21
  Speaker 3: best selling books. So we're very fortunate to have him.
• 1:23
  Speaker 3: They were excited to talk to him. How are you doing, Steve,
• 1:26
  Speaker 3: I'm doing great. Thanks for having me our pleasure. So
• 1:29
  Speaker 3: going out of interest, we're going to get into your
• 1:31
  Speaker 3: new book momentarily or your recent book, I should say,
• 1:34
  Speaker 3: which is AI and the Octopus Organization building the super
• 1:39
  Speaker 3: Intelligent Firm splendid title. But before we do, I have
• 1:42
  Speaker 3: to pick up on this development of an early smartphone.
• 1:46
  Speaker 3: Tell us about the role you played in and tell
• 1:48
  Speaker 3: us tell us about that that fascinating sounding chapter in
• 1:52
  Speaker 3: and You Buy Over.
• 1:54
  Speaker 4: Oh You Bet tom So.
• 1:55
  Speaker 5: Back in two thousand, I was recruited by Cion, which
• 1:59
  Speaker 5: is a British consumer electronics company that had invented the
• 2:03
  Speaker 5: personal digital system back in the eighties. They had software
• 2:08
  Speaker 5: that became Symbian, which was the operating system for some
• 2:11
  Speaker 5: of the early smartphones, and their CEO wanted to go
• 2:16
  Speaker 5: from pure play digital systems into what we were calling
• 2:20
  Speaker 5: a smartphone.
• 2:21
  Speaker 4: It was a very novel term back then. We were
• 2:24
  Speaker 4: also going up the connected PDA.
• 2:26
  Speaker 5: That was not a term that's stuck. The smartphone's stuck.
• 2:30
  Speaker 5: So we on a white label basis were developing smartphones
• 2:35
  Speaker 5: for Motorola and ericson to bring out to the market.
• 2:40
  Speaker 5: And I led that that program area. So you know,
• 2:44
  Speaker 5: those lessons stick with you. Sometimes you don't know the
• 2:49
  Speaker 5: full potential what you have. We knew this was good.
• 2:51
  Speaker 5: We knew this had a lot of potential. Not that
• 2:54
  Speaker 5: it would addict several billion people, we were not really
• 2:58
  Speaker 5: aware of that. But we did have a view about
• 3:02
  Speaker 5: how it could be used for maps and gaming, not
• 3:05
  Speaker 5: social media, nothing like that. But I learned a few
• 3:09
  Speaker 5: things from that. I learned how big innovations can sometimes
• 3:14
  Speaker 5: come from just amalgamating a lot of small innovations. The
• 3:19
  Speaker 5: smartphone itself, at least to us, was a fairly obvious
• 3:23
  Speaker 5: extension of the different parts that were coming together, and
• 3:26
  Speaker 5: now we could integrate them in a pretty novel way,
• 3:28
  Speaker 5: not trivialized it. It was difficult, but it wasn't an
• 3:33
  Speaker 5: outlandish notion. But then you also need to have sort
• 3:36
  Speaker 5: of the on ramp to new behaviors. My landlady in
• 3:41
  Speaker 5: London had seen me on British TeV talking about smartphones
• 3:47
  Speaker 5: and she was a little baffled by it and she
• 3:50
  Speaker 5: asked what it was good for and I sort of
• 3:52
  Speaker 5: explained really enthusiastically, and she paused and she said, oh, well,
• 3:57
  Speaker 5: does it send a text? And not really, it was
• 4:01
  Speaker 5: very good attending to get text. I mean, you could
• 4:03
  Speaker 5: tap stuff out with a stylist, but if that's what
• 4:07
  Speaker 5: you want to do, you could just use your thumbs
• 4:09
  Speaker 5: and tap something out much more quickly. So you know,
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  Speaker 5: it showed me that, yes, you need to add that
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  Speaker 5: future in mind, but we also need to give people
• 4:18
  Speaker 5: a smooth adoption curve.
• 4:20
  Speaker 4: They're not going to just leap the future overnight.
• 4:24
  Speaker 3: Going yes, so we're going to get into this momentary.
• 4:27
  Speaker 3: But I was just saying it, and it arguably right.
• 4:30
  Speaker 3: I mean, let's start with this, do we We're obviously
• 4:32
  Speaker 3: living through the most significant period of technical, technological innovation
• 4:37
  Speaker 3: and consumer innovation since the launch of a smartphone. I
• 4:41
  Speaker 3: think that's a fair comment, right, gentlemen, although do we
• 4:44
  Speaker 3: neglect social media? Oh my goodness, I don't know.
• 4:47
  Speaker 4: Where are we? Where does it rape? But yes, Tom,
• 4:51
  Speaker 4: certainly hand the last twenty five years.
• 4:53
  Speaker 3: In the last twenty five years, this is this is
• 4:55
  Speaker 3: the key moment, and it does it? Does it outweigh?
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  Speaker 3: And what where could can you give concrete examples of
• 5:02
  Speaker 3: those lessons you took from that last period of a
• 5:06
  Speaker 3: popularization and growth that you just described.
• 5:09
  Speaker 5: So look, if we look at AI, a lot of
• 5:13
  Speaker 5: people are talking about this destination of artificial general intelligence
• 5:18
  Speaker 5: or artificial superintelligence, and that is really the wrong thing
• 5:23
  Speaker 5: to be looking for. We're not looking for Skynet, this
• 5:26
  Speaker 5: sort of all knowing machine that might destroy the human race.
• 5:31
  Speaker 5: All we need is AI to be good enough to
• 5:35
  Speaker 5: be better than what humans are doing now in certain areas,
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  Speaker 5: or able to do things that we either can't do
• 5:43
  Speaker 5: or won't do because they're just so time consuming, like
• 5:46
  Speaker 5: taking careful notes of every meeting and creating a summary
• 5:49
  Speaker 5: for all participants, just not something that would usually happen
• 5:53
  Speaker 5: because we couldn't be bothered. So by those metrics, AI
• 5:57
  Speaker 5: is actually plenty good enough today to have a transformative effect.
• 6:01
  Speaker 5: So we need that sort of on ramp of behavior,
• 6:04
  Speaker 5: which we're already looking at. But let me let me
• 6:06
  Speaker 5: use another example. It goes a little bit further back.
• 6:09
  Speaker 5: So back in the eighteen eighties, electrification started really penetrating
• 6:14
  Speaker 5: into factories, and the first thing that factories did was
• 6:18
  Speaker 5: swap out their steam powered machines for electric machines, which
• 6:21
  Speaker 5: were better on many accounts, they were more reliable, you
• 6:25
  Speaker 5: could put more of them on a factory floor, et cetera.
• 6:28
  Speaker 5: But it wasn't really the big unlock of productivity. That
• 6:33
  Speaker 5: didn't happen for another thirty five years until the assembly
• 6:37
  Speaker 5: line was created. Now, you couldn't have the assembly line
• 6:40
  Speaker 5: without electricity, but it was only once you had that
• 6:44
  Speaker 5: that you had these massive increases, in many fold increases
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  Speaker 5: in individual productivity. So you can't just think about this
• 6:54
  Speaker 5: one for one swapping out of what we used to
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  Speaker 5: do for an AI and line. You need to rethink
• 7:00
  Speaker 5: the whole system, as people did with the assembly line
• 7:03
  Speaker 5: to really create the massive games.
• 7:08
  Speaker 3: Let's delve steve a bit into your your your key,
• 7:11
  Speaker 3: the key metaphor at the center of your of your
• 7:13
  Speaker 3: new book, if your octopus organization and you.
• 7:17
  Speaker 5: Mentioned on the cover to usual atibate books have an
• 7:21
  Speaker 5: octopus on the cover.
• 7:22
  Speaker 4: I asked you.
• 7:24
  Speaker 3: Were quite all right, quite right, and but we do
• 7:28
  Speaker 3: know that the octopus is octopi.
• 7:30
  Speaker 5: It's all right, it's a Greek term, not a Latin.
• 7:33
  Speaker 3: Term, an octopus. Let's go the name of the James.
• 7:37
  Speaker 3: But one side. And we do know very extra extraordinarily
• 7:43
  Speaker 3: intelligent creatures. Maybe maybe that's part of the picture. But
• 7:47
  Speaker 3: one thing you discussed in the book, I believe is
• 7:49
  Speaker 3: the extinction of the ammonite versus the survival of the octopus.
• 7:55
  Speaker 3: Unpack this whole metaphorical conception for us.
• 7:58
  Speaker 5: Sure thing, So let's go back sixty six million years.
• 8:02
  Speaker 5: These creatures called ammonites were everywhere in the ocean. There
• 8:08
  Speaker 5: were over ten thousand species of ammonites.
• 8:10
  Speaker 4: These were these.
• 8:13
  Speaker 5: Thickly armored, tightly coiled shellfish basically that were where everywhere.
• 8:20
  Speaker 5: They could range from a few inches in diameter to
• 8:23
  Speaker 5: ten feet. It could be enormous. And the octopuses were
• 8:27
  Speaker 5: the sort of marginal creature in the seas. And the
• 8:31
  Speaker 5: ammonites had developed this thick armor over eons to defend
• 8:35
  Speaker 5: themselves against well known threats like the gigantic dinosaur fish.
• 8:40
  Speaker 5: For instance, and then a meteor struck the earth and
• 8:45
  Speaker 5: it killed all the dinosaurs. It wiped out seventy five
• 8:49
  Speaker 5: percent of species on Earth. One thing it did was
• 8:52
  Speaker 5: create acid rain, and the acid rain changed the chemistry
• 8:58
  Speaker 5: of the seas, and the seas dissolved the shells of
• 9:03
  Speaker 5: the young ammonites, so what used to be their fortress
• 9:06
  Speaker 5: became a prison and they were trapped there, and almost
• 9:11
  Speaker 5: immediately the ammonites went extinct. The octopus is actually three
• 9:16
  Speaker 5: hundred million years old. That's seventy million years older than
• 9:20
  Speaker 5: the dinosaurs. It's been around a really long time, and
• 9:25
  Speaker 5: it has almost no natural defenses. What it can do
• 9:30
  Speaker 5: is adapt itself super rapidly because it can actually recode
• 9:34
  Speaker 5: its RNA within hours. So you can take an octopus
• 9:37
  Speaker 5: from the Antarctic and PLoP it into the Caribbean and
• 9:40
  Speaker 5: within hours it will be just fun. So the octopus
• 9:44
  Speaker 5: could very rapidly adapt to the justessification of the seas.
• 9:48
  Speaker 5: And with all these competitors wiped out, it thried it
• 9:50
  Speaker 5: was having a breaton. So we need to be like octopuses,
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  Speaker 5: super adaptable. But most corporations are like ammonites. They've got
• 10:01
  Speaker 5: these very the coats some armor against the very well
• 10:06
  Speaker 5: known threats that are out there, and yet those defenses
• 10:10
  Speaker 5: can actually become a prison. They can impede change, whereas
• 10:15
  Speaker 5: the octopuses of the world thrive on it.
• 10:20
  Speaker 2: And that's fascinating. And Steve, you talk about the fact
• 10:26
  Speaker 2: that AI isn't just a tool, that it's a force
• 10:30
  Speaker 2: that reshapes how organizations think. Is it helping us figure
• 10:33
  Speaker 2: out how to think or is it actually thinking for us?
• 10:36
  Speaker 2: Expand a bit on that, if you could.
• 10:39
  Speaker 4: That's a great question.
• 10:40
  Speaker 5: I think it does a bit of both. In very
• 10:44
  Speaker 5: rudimentary functions like say, I know call center, it can
• 10:49
  Speaker 5: do the thinking for you. It can lift up relatively
• 10:54
  Speaker 5: mediocre call center people to be decent, and its limited
• 11:00
  Speaker 5: effects on people who are really good. Back in high school,
• 11:04
  Speaker 5: I had one of the worst jobs in my life.
• 11:06
  Speaker 5: I was a telemarketer selling meat over the phone. Nobody
• 11:10
  Speaker 5: wanted to buy from me, and I sucked. But you know,
• 11:14
  Speaker 5: if I had had an AI script sort of indicating
• 11:16
  Speaker 5: what to say in response to what people might be raising,
• 11:19
  Speaker 5: I probably would have done better. My colleague was also
• 11:23
  Speaker 5: in high school. He was really naturally charming. I don't
• 11:26
  Speaker 5: think it was going to help him very much. So
• 11:28
  Speaker 5: in this case, AI can do the thinking for us.
• 11:31
  Speaker 5: But if you're at a higher level of capability, then
• 11:36
  Speaker 5: AI is really a thought partner. So look in my
• 11:40
  Speaker 5: firm here, a consulting firm. I don't want the AI
• 11:42
  Speaker 5: thinking for us.
• 11:43
  Speaker 4: I want it as a thought partner.
• 11:46
  Speaker 5: Poke holes in what I've done. Find me an example,
• 11:51
  Speaker 5: by the way, how I found the ammonite as an example,
• 11:53
  Speaker 5: we asked AI for a particular example. So you sort
• 11:56
  Speaker 5: of engage in a dance with it. It's not like
• 11:58
  Speaker 5: you're doing your dance and the AI is doing it. Stance,
• 12:01
  Speaker 5: get together, and jointly you create something that is much
• 12:06
  Speaker 5: better than what either of you could have created on
• 12:08
  Speaker 5: your own.
• 12:09
  Speaker 2: And Gardner makes that point a lot as well, that
• 12:12
  Speaker 2: AI has different value to different levels of thinking humans
• 12:17
  Speaker 2: and different places in their career. Right, a seasoned, experienced
• 12:21
  Speaker 2: lawyer is going to use AI as that thought partner
• 12:24
  Speaker 2: and is going to understand the responses that they get
• 12:27
  Speaker 2: back and validate. Is this legit?
• 12:29
  Speaker 5: Is this real?
• 12:30
  Speaker 2: Did it just make something up?
• 12:31
  Speaker 4: Right?
• 12:32
  Speaker 2: We've seen cases of AI just making up cases out
• 12:35
  Speaker 2: of thin air, so it definitely can, and I use
• 12:39
  Speaker 2: it as that thought partner and creative partner all the time.
• 12:42
  Speaker 2: You've argued that in doing so, that companies shouldn't just
• 12:47
  Speaker 2: simply and we're going to coin a term here, a
• 12:50
  Speaker 2: coin a word. Maybe we'll get this in Webster's dictionary.
• 12:52
  Speaker 2: A shout out to Tom. Companies shouldn't simply AI afi
• 12:57
  Speaker 2: existing processes, right. You see that a lot in this industry,
• 13:01
  Speaker 2: traditional tech companies playing catch up, They bolt on an
• 13:03
  Speaker 2: AI capability and they call it AI and move forward.
• 13:07
  Speaker 2: What's the risk of retrofitting AI onto old ways of
• 13:12
  Speaker 2: not only old ways of working, but old ways of thinking.
• 13:16
  Speaker 5: Look, it's like swapping in an electric machine for a
• 13:19
  Speaker 5: steam machine. That's nice, but it's not going to revolutionize
• 13:26
  Speaker 5: how you do things, and it may actually ossify the
• 13:30
  Speaker 5: way you've done stuff. Right, if you just brought in
• 13:34
  Speaker 5: all this I infrastructure to automate each step of your
• 13:39
  Speaker 5: seventeen step process, you're probably not going to rethink and say, well,
• 13:42
  Speaker 5: maybe it should be four steps, and it should be
• 13:44
  Speaker 5: four very different steps. So, as we work with enterprises
• 13:50
  Speaker 5: on how they really scale up AI adoption, what we're
• 13:55
  Speaker 5: finding is that you're not just fixing the technolgical ways
• 14:00
  Speaker 5: of doing stuff you're thinking about who has authority to
• 14:04
  Speaker 5: do different things, how do different functions interact, how quickly
• 14:09
  Speaker 5: can decisions get made? Where are the decision rights? Those
• 14:12
  Speaker 5: are all the sorts of questions that should get answered
• 14:15
  Speaker 5: as you're thinking about a workflow, and as you do that,
• 14:18
  Speaker 5: you might fundamentally rethink how stuff is being done.
• 14:24
  Speaker 2: So let's go back to the book. Love the image
• 14:27
  Speaker 2: on the cover, but help us more clearly define what
• 14:32
  Speaker 2: that means to build an octopus organization and maybe share
• 14:35
  Speaker 2: a few real world examples of one that's actually in practice.
• 14:39
  Speaker 5: Sure thing, So look, an octopus is a lesson for us,
• 14:43
  Speaker 5: not only in its hyperadaptability, but in its biology. An
• 14:48
  Speaker 5: octopus actually has nine brains. It has one central brain
• 14:53
  Speaker 5: that its head, and then a brain in each of
• 14:56
  Speaker 5: its arms, and these arms brains can coordinate amongst themselves
• 15:01
  Speaker 5: without even involving the central head. So it is a
• 15:04
  Speaker 5: model of distributed intelligence and action. Two thirds of its
• 15:08
  Speaker 5: neural tissue is actually not in its head, it's throughout
• 15:12
  Speaker 5: the body. So we need to change from our conception
• 15:16
  Speaker 5: of organizations, which is like how us humans are, with
• 15:19
  Speaker 5: the central head commanding the arms and of whatnot, to
• 15:22
  Speaker 5: something that's quite alien, and that's more octopus like, and
• 15:27
  Speaker 5: that enables rapid action. If you look at a high
• 15:31
  Speaker 5: frequency trading firm, for instance, that's how they are organized.
• 15:35
  Speaker 5: They have these different pods, and the pods of traders
• 15:39
  Speaker 5: can act fairly autonomously. They work very tightly with AI algorithms.
• 15:46
  Speaker 5: They're almost never placing the trades themselves. They're governing the
• 15:50
  Speaker 5: algorithms that do, and then they can coordinate amongst themselves
• 15:54
  Speaker 5: as necessary. The central brain can look at what it
• 15:57
  Speaker 5: really needs to like collectively as an enterprise, are we
• 15:59
  Speaker 5: taking these sorts of appropriate risks? Are we complying with regulations?
• 16:06
  Speaker 5: Hello Fresh is another example in a totally different industry.
• 16:09
  Speaker 5: They're the world's largest meal kit delivery company. They have
• 16:14
  Speaker 5: used AI to create radical customization in the menu that.
• 16:19
  Speaker 4: It offers to people.
• 16:20
  Speaker 5: So rather than giving people a handful a dozen or
• 16:24
  Speaker 5: so choices, now there might be two thousand different things
• 16:29
  Speaker 5: that people might have, and they're going to know based
• 16:31
  Speaker 5: upon your history. Tom prefers chicken to pork, and I
• 16:35
  Speaker 5: like things a little bit spicy.
• 16:37
  Speaker 4: Now.
• 16:37
  Speaker 5: What that's meant, though, is that in the operations of
• 16:40
  Speaker 5: the company, you can no longer have this central menu construction.
• 16:45
  Speaker 5: It's radically decentralized, and then the kitchens also can have
• 16:49
  Speaker 5: some master plan on how they're going to be producing
• 16:53
  Speaker 5: meals for the week. That would be impossible to create
• 16:56
  Speaker 5: a master plan for two thousand meals. AI has to
• 16:59
  Speaker 5: do that, and that means the production managers critically are
• 17:04
  Speaker 5: not telling people do this, do that, and they're not
• 17:06
  Speaker 5: creating the plan. They are stewards of the model. They're
• 17:10
  Speaker 5: seeing what might the model not be seeing that they're
• 17:14
  Speaker 5: seeing because perhaps they have fuller context, and they're engaging
• 17:17
  Speaker 5: in the sort of dialogue with the models to make
• 17:19
  Speaker 5: sure that the production plans are appropriate and then explaining
• 17:23
  Speaker 5: this change to the production workers that they have. So
• 17:27
  Speaker 5: the job of middle managers and an octopus organization fundamentally transforms, and.
• 17:34
  Speaker 2: It that's fascinating because it people really get enamored and
• 17:39
  Speaker 2: connected with the technology and the tooling and the new
• 17:43
  Speaker 2: shiny tool that they can bring into their environment. What
• 17:47
  Speaker 2: guidance would you give for folks that are reading the
• 17:51
  Speaker 2: book or really getting their head around this really distributed
• 17:55
  Speaker 2: computing on steroids? What's your guidance for it teams that
• 18:00
  Speaker 2: really want to lead and enable true AI transformation and
• 18:06
  Speaker 2: not just bringing in and bolting on that AI tool.
• 18:10
  Speaker 5: So we shouldn't be thinking about this as an IT implementation.
• 18:16
  Speaker 5: You should be thinking about it as a transformation of
• 18:19
  Speaker 5: how an organization operates. So the IT team really should
• 18:23
  Speaker 5: be a transformation team. Now, sure they have to have
• 18:26
  Speaker 5: tentical strength, and these systems have to work, they have
• 18:30
  Speaker 5: to have certain guardrails, they have to by certain cybersecurity protocols, etc.
• 18:36
  Speaker 5: Of course, but we need to be thinking about that
• 18:40
  Speaker 5: whole system of use, and importantly, not just how do
• 18:44
  Speaker 5: you aiifi the current system of use, but how do
• 18:48
  Speaker 5: to change the system of use to one that is
• 18:51
  Speaker 5: much more appropriate to where the organization is going. That's
• 18:55
  Speaker 5: why Hello Fresh is a great example. Rethought what its
• 18:59
  Speaker 5: customer value opposition should be, and then it worked backwards
• 19:02
  Speaker 5: to what does that mean in terms of the kitchens,
• 19:04
  Speaker 5: What does that mean in terms of ingredients sourcing.
• 19:07
  Speaker 4: It had to think about.
• 19:08
  Speaker 5: The whole knock on effects that were created, and the
• 19:12
  Speaker 5: IT systems then had to accommodate it.
• 19:14
  Speaker 4: This is what IT system IT people need to do.
• 19:17
  Speaker 5: They need to think much more broadly and look, I
• 19:21
  Speaker 5: used an example the organization the insurance company Travelers I
• 19:28
  Speaker 5: interviewed their head of it. But critically, I think her
• 19:32
  Speaker 5: title is very telling. She is the chief Technology and
• 19:36
  Speaker 5: Operations officer, So it's both and whether or not that's
• 19:41
  Speaker 5: your title, you need to think that way.
• 19:46
  Speaker 3: I had a question about a phrase using your work
• 19:48
  Speaker 3: around organizational plasticity. I think because I like p phrase
• 19:52
  Speaker 3: so much, Steve but stood out to me. But I
• 19:55
  Speaker 3: feel like we've you know, but it's it's it's quite
• 19:59
  Speaker 3: kind of in parent and a lot of what you've
• 20:01
  Speaker 3: been talking about. Is there any nuance to it we
• 20:03
  Speaker 3: haven't covered already, or any any way of unpacking that
• 20:06
  Speaker 3: concept further and more concretely when we've already done.
• 20:12
  Speaker 5: Yeah, organizations tend to be very fossilized. They tend to
• 20:18
  Speaker 5: stick in a shape, even when that shape doesn't make
• 20:22
  Speaker 5: a whole lot of sense anymore. I have never been
• 20:25
  Speaker 5: a big fan of reorganizations. I think they can create
• 20:29
  Speaker 5: a tremendous amount of dislocation and confusion. And so I'm
• 20:34
  Speaker 5: not necessarily saying redraw your org chart. Maybe, but what
• 20:39
  Speaker 5: I'm really saying is redraw how you behave as an organization.
• 20:44
  Speaker 5: Where do the decision rights lie? Do we really devolve authority?
• 20:49
  Speaker 5: How do we communicate cross functionally and octopus has devolved
• 20:54
  Speaker 5: authority to its arms. It has the cross silo coordination.
• 20:58
  Speaker 5: One arm knows one another one is doing. And look,
• 21:01
  Speaker 5: this is not a new thought. We have been talking
• 21:04
  Speaker 5: about devolution and desiloing since the nineteen eighties, and yet
• 21:09
  Speaker 5: it hasn't really happened because the information did not flow
• 21:15
  Speaker 5: as it could. Now with AI, AI creates transparency and
• 21:20
  Speaker 5: flow of information, so the right data gets to the
• 21:23
  Speaker 5: right people at the right time. And then it also
• 21:26
  Speaker 5: creates transparency into what's going on in the organization. People
• 21:29
  Speaker 5: have been afraid to devolve authority because they don't know
• 21:31
  Speaker 5: what kind of shenanigans people are going to do in
• 21:34
  Speaker 5: the arms of the organization. Now with AI, there's a
• 21:39
  Speaker 5: lot more visibility into that. Critically, you can't use that
• 21:44
  Speaker 5: as an excuse for centralization. Now that I can see
• 21:47
  Speaker 5: everything that all my people are doing, I can dictate
• 21:50
  Speaker 5: even more and more what's going on.
• 21:53
  Speaker 4: People are going to be tempted to do that.
• 21:54
  Speaker 5: That is a human tendency, But instead we need to
• 21:58
  Speaker 5: use that visibility to let things sort of play out.
• 22:02
  Speaker 5: Intervene were necessary, but by and large, intervening on an
• 22:06
  Speaker 5: exception basis not as a rule.
• 22:11
  Speaker 3: It's been so interesting to have you on. So first,
• 22:14
  Speaker 3: you've I think you've really complemented a series of really
• 22:17
  Speaker 3: exceptional conversations we've had over the last month or two.
• 22:21
  Speaker 3: Would point people to the episode agentic AI and the
• 22:25
  Speaker 3: end of Traditional It with Rob Wilson. We were kind
• 22:29
  Speaker 3: of considering with him a little bit more about what
• 22:32
  Speaker 3: it meant for employees, for individuals in this very new
• 22:35
  Speaker 3: world and the way we approach our lives and quote
• 22:38
  Speaker 3: unquote careers in twenty twenty five and beyond. You've kind
• 22:43
  Speaker 3: of focused a bit more on organizational structure, of course,
• 22:47
  Speaker 3: but with a very similar kind of ethos and message.
• 22:50
  Speaker 3: But I wonder how you would translate that into let's say,
• 22:54
  Speaker 3: advice to organizational leaders may be feeling overwhelmed by the
• 22:59
  Speaker 3: pace and ambiguity of AI change. What would you tell them?
• 23:03
  Speaker 3: What would be your orientation advice as it were, for
• 23:08
  Speaker 3: approaching the future in the strongest spirit.
• 23:13
  Speaker 5: So a couple people pieces of advice. First of all,
• 23:17
  Speaker 5: we have a chapter in the book called three Hearts,
• 23:20
  Speaker 5: and this derives from the octopus actually having three different
• 23:24
  Speaker 5: hearts that it uses for different purposes. Another weird aspect
• 23:28
  Speaker 5: of octopus biology. We translate that through into different leadership styles.
• 23:35
  Speaker 5: There is an analytics style that you need and typically
• 23:38
  Speaker 5: organizations already have. You certainly need to retain that where
• 23:41
  Speaker 5: we're not saying analysis goes way by any means. AI
• 23:45
  Speaker 5: may help with that analysis, but doesn't replace it. Second, though,
• 23:48
  Speaker 5: you need the agile part. You need to be able
• 23:52
  Speaker 5: to deal on a very flexible basis where flexibility is required,
• 24:00
  Speaker 5: and that is going to happen increasingly with the pace
• 24:02
  Speaker 5: of change. AI is just one element in accelerating that
• 24:05
  Speaker 5: pace of change. So companies need to be able to
• 24:08
  Speaker 5: get more agile where appropriate and to shift between analytic
• 24:12
  Speaker 5: and angel modes. And then finally you need that aligned part.
• 24:16
  Speaker 5: You need to think about the emotional toll that this
• 24:20
  Speaker 5: is going to take on a whole lot of people
• 24:23
  Speaker 5: and really talk to the change in culture, the change
• 24:29
  Speaker 5: and maybe safety that people feel, and be sensitive to
• 24:34
  Speaker 5: all of that. So I think that is the number
• 24:37
  Speaker 5: one thing that people need to do is their leadership styles.
• 24:40
  Speaker 5: The second thing is a little bit more cerebral. They
• 24:43
  Speaker 5: need to think about what does the organization really need
• 24:46
  Speaker 5: to be good at strategically, So for Hello, Fresh They
• 24:51
  Speaker 5: determined that what IT really needed to be good at
• 24:54
  Speaker 5: was understanding user preferences and delivering on those. All this
• 25:00
  Speaker 5: data from fourteen years of history about what you substituted
• 25:04
  Speaker 5: your meals for, what you rated your your meals, and
• 25:07
  Speaker 5: yet it wasn't really using that. It decided to change
• 25:10
  Speaker 5: that into its competitive mode. So AI can fundamentally change
• 25:16
  Speaker 5: who you are as an organization, what your competitive strategy
• 25:19
  Speaker 5: and differentiation is. What should that mean for your enterprise?
• 25:22
  Speaker 5: They have to do that too.
• 25:27
  Speaker 3: That's it's all absolutely amazing. And I think if if
• 25:31
  Speaker 3: if anyone's listening to this at at the very least,
• 25:34
  Speaker 3: they're going to be less likely to enjoy Octopus when
• 25:36
  Speaker 3: they're next on on a Spanish holiday. All this people
• 25:41
  Speaker 3: who get into into octopuses, as I now know it is,
• 25:44
  Speaker 3: they can't they can't bear the fact that we even
• 25:46
  Speaker 3: when it's the nice culumary, all these multiple all these
• 25:50
  Speaker 3: multiple hearts and brains, they have magnificent complexity, and we
• 25:56
  Speaker 3: just we just munch them when we're in Barcelona like
• 25:59
  Speaker 3: at eight, No thing but absolute pleasure. Steve to have
• 26:03
  Speaker 3: you on. I think your your your your thoughts on
• 26:06
  Speaker 3: organizational change in this era are genuinely unique and valuable,
• 26:11
  Speaker 3: and thanks so much for coming on and sharing with
• 26:14
  Speaker 3: any anyway you want to point the listeners to to
• 26:17
  Speaker 3: find out more about yourself or your work.
• 26:19
  Speaker 5: Sure so. The website for the book is AI Mdoctopus
• 26:23
  Speaker 5: dot com. You can look me up on LinkedIn. Stephen
• 26:27
  Speaker 5: Luonker and our company is New Markets Advisors. We engage
• 26:32
  Speaker 5: with organizations that are trying to undertake these sorts of transformations.
• 26:37
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  Speaker 1: Until next time,