Latest / The DEX Show: A Show for IT Change Makers / Meet the Poet of Disruption: AI, Risk, Respair 🔥 (w/ Terence Mauri)

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Meet the Poet of Disruption: AI, Risk, Respair 🔥 (w/ Terence Mauri) · 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 McGraw. Let's get into it.
• 0:08
  Speaker 2: If manners make a man, as someone said, then he's
• 0:11
  Speaker 2: the hero of the day. We can hear it in
• 0:15
  Speaker 2: his accent when he talks. He's an Englishman in New York,
• 0:18
  Speaker 2: which is my way, Ladies and gentlemen of welcoming our
• 0:21
  Speaker 2: special guest today, an english Man in New York. Terrence Maori, Heydan.
• 0:25
  Speaker 3: Terrence, Hey, Tom, Great to be on the show. Did
• 0:29
  Speaker 3: you like that?
• 0:29
  Speaker 2: It's not my rendition of it, which may have been
• 0:31
  Speaker 2: just off, But did you ever like that song? I
• 0:33
  Speaker 2: always quite like that song, you know, I always thought
• 0:35
  Speaker 2: it was very evocative.
• 0:36
  Speaker 3: Sting's song is great. It's one of my favorites.
• 0:38
  Speaker 4: And I grew up in Strap up and Aven, the
• 0:40
  Speaker 4: birthplace of Shakespeare. So I think you have an inner
• 0:43
  Speaker 4: poet in you.
• 0:45
  Speaker 2: Thank you think I was going to say, it's about
• 0:47
  Speaker 2: time someone put Stratford upon Avan on the map right exactly,
• 0:51
  Speaker 2: And I have to say it's great to have him
• 0:53
  Speaker 2: because I feel like I feel Tim.
• 0:56
  Speaker 5: Can maybe voucher this right.
• 0:57
  Speaker 6: But if I was to think of a theme, a
• 1:01
  Speaker 6: meta theme for the first quarter of Deck shows of
• 1:04
  Speaker 6: twenty twenty five, I'm going to say disruption. You know,
• 1:08
  Speaker 6: we did a lot of We've done a lot of
• 1:09
  Speaker 6: stuff around around Assist two point zero.
• 1:12
  Speaker 2: As listeners will know, we we launched the Transformation Report
• 1:18
  Speaker 2: about AI transformation, and speaking of PUTT, it is something
• 1:22
  Speaker 2: of the poet of disruption. We might say terrence right
• 1:25
  Speaker 2: when you tell people a little bit, a little bit
• 1:27
  Speaker 2: about your work.
• 1:30
  Speaker 3: I love the framing, and it's true.
• 1:32
  Speaker 4: I think disruption is one of these words that's misunderstood.
• 1:35
  Speaker 4: It's overused, often becomes a buzzword and loses its specificity.
• 1:41
  Speaker 4: But I'm interested in the upside of disruption because I
• 1:44
  Speaker 4: think on the other side of disruption, whether that's technology
• 1:47
  Speaker 4: change or talent scarcity or industry convergence, is the upside.
• 1:52
  Speaker 4: And the upside the opportunity for reinvention could be a
• 1:55
  Speaker 4: new service, a new product, a new platform. And I
• 1:58
  Speaker 4: think one of the big takeaways today that I want
• 2:00
  Speaker 4: to explore with you guys, with your listeners and viewers,
• 2:03
  Speaker 4: is this idea that we always overestimate the risk of
• 2:06
  Speaker 4: doing something new and always underestimate the risk of standing still.
• 2:11
  Speaker 4: That's really at the sort of central call to action
• 2:14
  Speaker 4: around disruption. Even job titles are being disrupted by the way.
• 2:18
  Speaker 4: I was at the had a meeting at the Department
• 2:20
  Speaker 4: of State, the State Department recently, and we exchange business cards,
• 2:24
  Speaker 4: and on the business card it said head of Uncertainty.
• 2:34
  Speaker 2: Okay, maybe be the king of the King of uncertainty.
• 2:40
  Speaker 7: But I do think, you know, particularly with AI arrians
• 2:43
  Speaker 7: right like I you know, I'm sure what you say
• 2:45
  Speaker 7: is right in general, but tell me if you disagree that.
• 2:50
  Speaker 7: With AI, there is a consensus that people need to
• 2:54
  Speaker 7: move and as much as there's that urgency about it,
• 2:58
  Speaker 7: there's also a sense of like an awareness. But yes
• 3:01
  Speaker 7: you can you can jump too late, but you can
• 3:04
  Speaker 7: also jump too early, right like, It's it's a push
• 3:06
  Speaker 7: and pull.
• 3:08
  Speaker 4: I think we have to avoid what I call artificial idiocy.
• 3:11
  Speaker 4: And as I play on the words AI, and what
• 3:16
  Speaker 4: I mean by that is that I agree AIS are
• 3:20
  Speaker 4: here to stay secular and structural trend presenting tremendous risk
• 3:25
  Speaker 4: but also a tremendous opportunity.
• 3:28
  Speaker 3: I think one of the things we're missing.
• 3:30
  Speaker 4: Right now with AI is it's largely an automation story
• 3:33
  Speaker 4: for many organizations and the media as well. And I'm
• 3:36
  Speaker 4: interested in an elevation story and the facts. In my
• 3:40
  Speaker 4: new body, the Upside of Disruption, I talk about really
• 3:42
  Speaker 4: two narratives around AI, warm AI, which is humanity first
• 3:47
  Speaker 4: enabled by AI, and cold AI, which is machine first,
• 3:52
  Speaker 4: often at the expense of at the cost of loneliness
• 3:55
  Speaker 4: or well being. And I feel that a lot of
• 3:57
  Speaker 4: cape capex is going into cold AI at the moment,
• 4:00
  Speaker 4: at the expense of warm AI.
• 4:05
  Speaker 2: And you know it's something we okay, so think about that,
• 4:09
  Speaker 2: what war MAI looks like in real terms? Right we
• 4:12
  Speaker 2: You know, you're seeing a lot of AI naturally launched
• 4:15
  Speaker 2: at the moment for non technical users. And I mentioned
• 4:18
  Speaker 2: ASI two point zh. We did a series of shows
• 4:21
  Speaker 2: about that. But listeners should check out if they mistram
• 4:23
  Speaker 2: which is effectively putting, you know, highly sophisticated dex insights
• 4:27
  Speaker 2: into democratizing those insights effectively, what kind.
• 4:32
  Speaker 8: Of opportunities and risks ternce does that kind of does
• 4:37
  Speaker 8: that kind of power of AI put in democratized offers
• 4:41
  Speaker 8: to organizations in your view?
• 4:43
  Speaker 3: So I think, you know, in terms of the key
• 4:45
  Speaker 3: difference here, it's one between.
• 4:47
  Speaker 4: Value extraction and value creation. It's one between AI that
• 4:53
  Speaker 4: actually creates an ultra process world when we're drowning in
• 4:57
  Speaker 4: information and drowning in data kind of world where actually
• 5:01
  Speaker 4: we achieve what's called ROI, which is not just with
• 5:03
  Speaker 4: ternal investment from our new human metric for a post
• 5:07
  Speaker 4: AI world return on intelligence and the research is unequivocal.
• 5:12
  Speaker 4: Around seventy percent of our time every week is spent
• 5:14
  Speaker 4: on bureaucratic activities and expensive intelligent activities. There's one thing
• 5:19
  Speaker 4: that AI could do to help us be more productive,
• 5:22
  Speaker 4: lead more meaningful lives.
• 5:24
  Speaker 3: Higher value and more intelligent driven lives.
• 5:26
  Speaker 4: It would be to democratize, but also to delete and disrupt, automate, remove,
• 5:34
  Speaker 4: subtract a lot of this bureaucratic, bad bureaucracy that we
• 5:40
  Speaker 4: have to deal with, whether that's too many meetings, too
• 5:43
  Speaker 4: many processes, duplicative structures, or just ways of thinking that
• 5:48
  Speaker 4: have gone off, like yoga in the fridge.
• 5:52
  Speaker 5: And so Tom, I'll agree with you. I think the
• 5:55
  Speaker 5: first part of the year, there's been a lot of
• 5:57
  Speaker 5: talk about disruption. In my travels around the world, I've
• 6:02
  Speaker 5: seen not just excitement about the opportunities of AI, but
• 6:07
  Speaker 5: I would characterize it as nervous excitement, and I think
• 6:10
  Speaker 5: it covers a lot of what terrence you're what you're
• 6:12
  Speaker 5: referencing that you know is the Is the fear of
• 6:16
  Speaker 5: moving forward justified? Or is it the traditional fud right, fear,
• 6:21
  Speaker 5: uncertainty and doubt. It's something new. It could be dangerous,
• 6:24
  Speaker 5: but we're not quite sure. I agree with it too,
• 6:28
  Speaker 5: that a lot of it is. It has almost been
• 6:30
  Speaker 5: fairly simplistic in the way it's talked about, uh leveraging
• 6:36
  Speaker 5: it mostly for automation, But AI, in my view, is
• 6:40
  Speaker 5: really an advanced way to get information or answer a question.
• 6:46
  Speaker 5: Right we We've used Google forever. You google your question,
• 6:49
  Speaker 5: you get tons of results back, but this gives you
• 6:51
  Speaker 5: very specific, detailed answers to your question. But you talk
• 6:55
  Speaker 5: about it in the context of next level decision making?
• 6:59
  Speaker 5: How to company is prepare for that shift? Right? We've
• 7:03
  Speaker 5: is data driven decisioning already ingreened in US and it's
• 7:06
  Speaker 5: not that big a deal. Are we already prepared or
• 7:09
  Speaker 5: do we need to do something else to get ready
• 7:11
  Speaker 5: for that next level decision making?
• 7:13
  Speaker 3: Yeah? I loved I love the question. It's a catalytic question.
• 7:17
  Speaker 4: It's a question that doesn't just make us feel good,
• 7:19
  Speaker 4: but makes people think hard, and that's important. I think
• 7:22
  Speaker 4: AI has completely misunderstood. The CEO of the IBM today
• 7:27
  Speaker 4: said that ninety nine percent of data has not been
• 7:30
  Speaker 4: touched by AI in enterprises and some of two of
• 7:33
  Speaker 4: the biggest challenges we're facing right now data quality and
• 7:37
  Speaker 4: speed to insight. And so obviously organizations are drowning in
• 7:43
  Speaker 4: multi layers and complexity. For example, the average number of
• 7:47
  Speaker 4: apps for a large enterprise and S and P five
• 7:50
  Speaker 4: hundred is over six hundred.
• 7:52
  Speaker 3: So we've got.
• 7:53
  Speaker 4: Legacy, we've got tech debt, we've got different levels of
• 7:58
  Speaker 4: different levels of hierarchies, and this creates all sorts of complexity,
• 8:02
  Speaker 4: which is a tax on our ability to really harness
• 8:06
  Speaker 4: the full intelligenible insight of our AI platforms. So I
• 8:11
  Speaker 4: think that's the challenge, and that's the opportunity actually, and
• 8:14
  Speaker 4: I agree with you. I think most organizations are trapped
• 8:16
  Speaker 4: between the panic zone and the opportunity zone. So sorry,
• 8:22
  Speaker 4: the panic zone and the complacency zone. And I think
• 8:25
  Speaker 4: we need to sort of look at a third a
• 8:28
  Speaker 4: third space, a third zone, which would be the learning zone,
• 8:31
  Speaker 4: the sandbox zone, the iterative zone, the zone where we're
• 8:35
  Speaker 4: really kind of you know, a simple core to action
• 8:37
  Speaker 4: would be what's a simple experiment we can do with
• 8:41
  Speaker 4: AI over the next thirty days to create our own
• 8:44
  Speaker 4: AI use case and get started on this journey. That
• 8:47
  Speaker 4: would be a great call to action straight away.
• 8:53
  Speaker 5: So some of the things I've been hearing as I
• 8:55
  Speaker 5: travel kind of divergent thoughts. The first is we won't
• 9:00
  Speaker 5: need experts anymore. I'll just ask AI. AI will be
• 9:03
  Speaker 5: my intelligence. I won't need intelligent people, I'll just need
• 9:07
  Speaker 5: the artificial intelligence, and I'll rely on that more and
• 9:10
  Speaker 5: more over time. You see that in even in Microsoft
• 9:13
  Speaker 5: as they move to using AI to do the majority
• 9:16
  Speaker 5: of their coding, this notion that AI is going to
• 9:20
  Speaker 5: be my full time intelligence. But on the other hand,
• 9:24
  Speaker 5: the divergent alarm that some experts are starting to set
• 9:29
  Speaker 5: is this concept of AI eating its own tail and
• 9:33
  Speaker 5: that the model will eventually collapse, that the data it's
• 9:36
  Speaker 5: consuming to make decisions will be the data that was
• 9:40
  Speaker 5: generated by AI, and that data is it always accurate.
• 9:44
  Speaker 5: We see it often that the questions that are asked
• 9:46
  Speaker 5: into AI result in bad data, or it leverages the
• 9:49
  Speaker 5: wrong information to give you bad answers, and that eventually
• 9:53
  Speaker 5: AI and the models will collapse because it's just all
• 9:55
  Speaker 5: regurgitated bad data. I'm curious what your thoughts are on
• 10:01
  Speaker 5: that kind of that soft skill of asking the great
• 10:04
  Speaker 5: question I deciphering the data that it returns back to
• 10:09
  Speaker 5: determine if it's good or bad. Where are what do
• 10:11
  Speaker 5: you What do you feel about the skills that it
• 10:14
  Speaker 5: actually are needed to leverage AI to its forest.
• 10:18
  Speaker 4: I think one of the interesting perspectives here, and I
• 10:22
  Speaker 4: sort of think about the research by Ethan Mollock, for example,
• 10:28
  Speaker 4: a great researcher on AI is I think one of
• 10:32
  Speaker 4: the you know this kind of idea that too much
• 10:35
  Speaker 4: information leads to a poverty of attention, And I think,
• 10:38
  Speaker 4: how we harness this intelligently so that you know the careering,
• 10:43
  Speaker 4: for example, the questioning is.
• 10:45
  Speaker 3: A real imperative.
• 10:47
  Speaker 4: I agree, I think in terms of the upside, and
• 10:50
  Speaker 4: I talk about a lot about the upside. Using AI
• 10:52
  Speaker 4: as a consultant as a service, for example, not just
• 10:56
  Speaker 4: as as as a co pilot, as a co thinker,
• 10:59
  Speaker 4: as a co strategist is where the upside is. But
• 11:03
  Speaker 4: I also think there's a risk of the curse of saneness.
• 11:07
  Speaker 4: And what I mean by the curse of sameness is
• 11:09
  Speaker 4: this really interesting paradox when everyone's got access to the
• 11:13
  Speaker 4: same cheap AI, the same data, how do you actually
• 11:16
  Speaker 4: differentiate yourself?
• 11:20
  Speaker 3: That's the real dilemma here.
• 11:21
  Speaker 4: That great, we've all been democratized, we've all got access
• 11:24
  Speaker 4: to AI, But then how do you differentiate yourself? It's
• 11:27
  Speaker 4: a genuine question as an individual, as a business, as
• 11:31
  Speaker 4: an enterprise when you've all got access to.
• 11:34
  Speaker 3: The same zero cost AI.
• 11:36
  Speaker 4: And by the way, we know that the cost of
• 11:38
  Speaker 4: AI models has dropped over two hundred and eighty x
• 11:41
  Speaker 4: in the last two years. So that's the dilemma that
• 11:44
  Speaker 4: I'm interested in exploring as well, which is actually what
• 11:47
  Speaker 4: will become more scarce when everyone's got access to the
• 11:50
  Speaker 4: same data, the same information, the same democratized AI. Well,
• 11:54
  Speaker 4: actually what will become scarce is human intelligence, human imagination,
• 12:00
  Speaker 4: and empathy, deep trust as opposed to shallow trust. The
• 12:05
  Speaker 4: two takeaways here one is be aware of the curse
• 12:07
  Speaker 4: of sameness and to what the world needs right now
• 12:11
  Speaker 4: more than ever, a willful contrarianism.
• 12:17
  Speaker 5: I couldn't agree more that the need for empathy, the
• 12:21
  Speaker 5: need for creativity, both in how we interact initially with
• 12:26
  Speaker 5: it as well as how we analyze the results. What
• 12:28
  Speaker 5: we're going to do with it. I think that's what
• 12:30
  Speaker 5: differentiates us. If we've all got access to the same models,
• 12:34
  Speaker 5: the same data, it's going to be how the human
• 12:36
  Speaker 5: interacts and leverages it and actually uses it to its fullest.
• 12:41
  Speaker 5: You know, these intelligent systems are becoming more conversational, more embedded.
• 12:46
  Speaker 5: I've told this story before a not long ago. Preparing
• 12:50
  Speaker 5: for a roundtable that I was participating in, I asked CHATGBT,
• 12:55
  Speaker 5: what roles will start to leverage AI more and more?
• 12:59
  Speaker 5: What new roles will do develop? And it came back
• 13:02
  Speaker 5: and one of the items it said was dex strategist
• 13:05
  Speaker 5: and in parentheses next to it it said wink wink,
• 13:09
  Speaker 5: because that's my title, and it just it made me
• 13:11
  Speaker 5: sit up and say, now, who coded who programmed GPT
• 13:16
  Speaker 5: to have that level of interaction and almost humor? Right,
• 13:20
  Speaker 5: So that.
• 13:23
  Speaker 3: Is it I did.
• 13:26
  Speaker 4: What's exciting about that, tim is this idea that AI
• 13:30
  Speaker 4: is the worst it will ever be today. AI is
• 13:32
  Speaker 4: the slowest it will ever be today. So imagine after
• 13:35
  Speaker 4: all another three years, five years, we don't even have
• 13:37
  Speaker 4: to speak about ten years.
• 13:38
  Speaker 3: I'm talking about the next thirty six months.
• 13:41
  Speaker 4: So I think that's really interesting and I think alongside that,
• 13:44
  Speaker 4: what we're not talking about enough is the psychological revolution.
• 13:48
  Speaker 4: We're so focused on the technology revolution and the AI
• 13:51
  Speaker 4: revolution and this exciting it sucks up all the oxygen
• 13:54
  Speaker 4: in the room, but we can't actually harness the full
• 13:57
  Speaker 4: potential of that without a psychological revolution. What I mean
• 14:01
  Speaker 4: by that is if I go into most organizations today,
• 14:05
  Speaker 4: they're still using the same organizational playbooks that they used
• 14:08
  Speaker 4: one hundred years ago, quite literally in the way that
• 14:11
  Speaker 4: they approach the working day, meetings, committees and breaking down
• 14:17
  Speaker 4: a bundling and unbundling of jobs. So that's what's interesting
• 14:20
  Speaker 4: to me, and that's that's the risk and opportunity again,
• 14:23
  Speaker 4: which is we've got this incredible access to superpower now
• 14:28
  Speaker 4: only limited by our own imaginations, but without that psychological
• 14:31
  Speaker 4: and organizational revolutions to supports it, we risk artificial idiocy.
• 14:36
  Speaker 4: It's a bit like getting a Ferrari or a Porsche
• 14:39
  Speaker 4: and actually still you know, only going five miles per
• 14:42
  Speaker 4: hour in it because we don't know how to use it.
• 14:46
  Speaker 5: And I think that idiocy is is learned over many
• 14:51
  Speaker 5: decades of ingreined process ingreined hierarchy in our organizations. You know,
• 14:57
  Speaker 5: we're stuck in status quo. So we look at things
• 15:00
  Speaker 5: in the context of what we've done versus the possible
• 15:03
  Speaker 5: and what exactly right And to get back to this
• 15:07
  Speaker 5: this concept of taking those old ideas, those old methodologies
• 15:13
  Speaker 5: and disrupting them. Right, there's some very visible tech leaders
• 15:17
  Speaker 5: right now who have a strong disruption mindset, but that
• 15:21
  Speaker 5: when it's done incorrectly, we can see that disruption can
• 15:25
  Speaker 5: really cause severe havoc. Right, So you've said that this
• 15:29
  Speaker 5: mindset is a strategy and mindset can really change how
• 15:33
  Speaker 5: technology is viewed, how it's designed, how it's implemented. Talk
• 15:37
  Speaker 5: about mindset. What mindset do these leaders of digital column
• 15:42
  Speaker 5: digital leaders? How do they lead effectively through this disruption
• 15:47
  Speaker 5: and not avoid the chaos?
• 15:50
  Speaker 4: Interesting questions A pivotal question right now, a question of
• 15:53
  Speaker 4: our times. And you know, i'd spent some time working
• 15:57
  Speaker 4: with Revolute recently, and we know Revolute for you know,
• 16:01
  Speaker 4: being really a sort of future ready frontier company in
• 16:07
  Speaker 4: banking and sort of neo banking, but actually they're going
• 16:12
  Speaker 4: to start disrupting the telecoms market next you know, they've
• 16:15
  Speaker 4: they've decided that and this is this is the interesting
• 16:18
  Speaker 4: thing about these pioneer disruptors, which they're not just focusing
• 16:22
  Speaker 4: on one vertical on an industry. They can actually disrupt
• 16:26
  Speaker 4: multiple verticals. And that's the scary truth for anyone listening
• 16:30
  Speaker 4: today that your next biggest competitor could be a Revolute,
• 16:33
  Speaker 4: could be a or a company you've never actually heard
• 16:35
  Speaker 4: of VC backed. So I think in terms of those
• 16:38
  Speaker 4: minds to collective mindset shifts that we're talking about economies
• 16:41
  Speaker 4: of scale to economies of sustainability and economies of light speed.
• 16:47
  Speaker 4: Ecosystem to ecosystem preservers of the status quo to challengers
• 16:52
  Speaker 4: of the status quo, Homo sapient to techno sapient data
• 16:58
  Speaker 4: silo to collective intel eligence and wait and see, to
• 17:03
  Speaker 4: learn and explore, do faster than doubt would be a
• 17:07
  Speaker 4: key call to action right now. I spent some time
• 17:09
  Speaker 4: met Jesse Armstrong, the chief writer behind Succession. One of
• 17:14
  Speaker 4: my favorite sayings from that brilliant show, by the way,
• 17:17
  Speaker 4: is you can't make a can't make a Tomlet without
• 17:21
  Speaker 4: breaking some gregs. And Jesse Armstrong, yeah, he used to.
• 17:26
  Speaker 4: He iterated the script over a one hundred times with
• 17:28
  Speaker 4: his team, and one of their mottos is start before
• 17:31
  Speaker 4: you're ready or don't start at all. And I think
• 17:34
  Speaker 4: in this moment of extreme liminality, in this moment of
• 17:38
  Speaker 4: high speed on reality, for many, actually not taking a
• 17:41
  Speaker 4: risk as a risk when it comes to AI.
• 17:46
  Speaker 2: Interesting and extreme liminality is super cool. Terrence. I know
• 17:53
  Speaker 2: you've also written about trust as a kind of currency
• 17:56
  Speaker 2: in this emergent world thinking, maybe describe your ideas and
• 18:02
  Speaker 2: about trust and why it's so significant and significant, and
• 18:05
  Speaker 2: then relate that if you can to how technology teams
• 18:09
  Speaker 2: and organizations can can build trust as they start to
• 18:12
  Speaker 2: roll out these very disruptive new tools.
• 18:15
  Speaker 4: If trust was on the dashboard right now, be flashing red.
• 18:19
  Speaker 4: The writer George Orwell would love these times, but not
• 18:22
  Speaker 4: in the right way.
• 18:23
  Speaker 3: We have mean warfare. Deep fake.
• 18:26
  Speaker 4: We heard recently that one of the finance team er
• 18:30
  Speaker 4: up the engineering company based well, this was the Hong
• 18:33
  Speaker 4: Kong Offers. He saw a deep fake of his CFO
• 18:36
  Speaker 4: and it was so believable that he transferred twenty five
• 18:39
  Speaker 4: million dollars. But he did it in twenty five transactions.
• 18:43
  Speaker 4: And here's an interesting question for you. If you saw
• 18:46
  Speaker 4: a if you saw your CEO on the screen, how
• 18:50
  Speaker 4: confident would you be to know that it was him
• 18:52
  Speaker 4: or her or a deep fake. Last year it was
• 18:55
  Speaker 4: about sixty six percent confidence. This year's thirty three percent
• 18:58
  Speaker 4: confidence with the actually is irrelevant.
• 19:01
  Speaker 3: At some point, very soon, you won't know the difference.
• 19:05
  Speaker 4: And if cybercrime and truth decay and trust and ethical
• 19:09
  Speaker 4: breaches were a country, there'd be the third fastest growing
• 19:13
  Speaker 4: country on the planet. Right now, global GDP over eleven
• 19:17
  Speaker 4: trillion dollars growing at a compound on your growth rate hooever,
• 19:20
  Speaker 4: twenty eight percent. We see some big examples in the
• 19:23
  Speaker 4: last eighteen months, snowflake healthcare companies. The average data breach
• 19:29
  Speaker 4: will cost you between six and ten million dollars. It
• 19:33
  Speaker 4: will affect your stock price by seven to nine percent.
• 19:37
  Speaker 4: And trust is the number one driver of enterprise value,
• 19:41
  Speaker 4: but it's never been more tested and more under attack.
• 19:45
  Speaker 4: And trust is the ultimate human currency in this age
• 19:49
  Speaker 4: of AI acceleration and automation. And so for me, if
• 19:53
  Speaker 4: I break down trust, you know, we're going through different
• 19:56
  Speaker 4: evolutions of trust. Institutional trust, local trust, this distributed trust
• 20:03
  Speaker 4: which is enabled by technology, and then auto sapient trust,
• 20:07
  Speaker 4: which will be you know, you'll have the equivalent of
• 20:10
  Speaker 4: a chat GBT that will be your your ure, your
• 20:13
  Speaker 4: user interface, and you will decide what to do through
• 20:17
  Speaker 4: that particular chatbot auto sapient trust and the organizations own
• 20:22
  Speaker 4: that own the trust on the ecosystem and own the
• 20:25
  Speaker 4: value chain. So trust is a big deal. It's time
• 20:29
  Speaker 4: to rethink trust, physical, digital, ethical, and I think it's
• 20:33
  Speaker 4: never been under more under under pressure.
• 20:37
  Speaker 2: I already fell for just about every phishing scam going terns.
• 20:41
  Speaker 2: So you know, they don't they don't need to, they
• 20:43
  Speaker 2: don't need to invest so heavily to pull me in.
• 20:46
  Speaker 2: Who think you send twenty five million dollars zero to some.
• 20:51
  Speaker 3: Company?
• 20:52
  Speaker 4: And you know, basically I was on Microsoft recently. They're
• 20:56
  Speaker 4: just Microsoft, just one company. They're dealing with seven thousand
• 21:00
  Speaker 4: password attacks a second, and that translates into six hundred
• 21:05
  Speaker 4: million a day, two trillion a year. Now compound that
• 21:09
  Speaker 4: by different companies, and you know, we go beyond the
• 21:12
  Speaker 4: cognitive limits of these numbers. But this is the interesting
• 21:17
  Speaker 4: paradox again. As AI gets more and more advanced exponential
• 21:21
  Speaker 4: speed and scale, so does deep fake.
• 21:24
  Speaker 3: So do cyber crime, so does data breach. That they're
• 21:27
  Speaker 3: in parallel together.
• 21:30
  Speaker 2: That's that's wild. I have to say, I've kind of
• 21:35
  Speaker 2: touched upon it already. But what's going to separate, what's
• 21:38
  Speaker 2: going to distinguish first technology leaders or organizations who can
• 21:42
  Speaker 2: drive genuine, enduring change as against those who just who
• 21:47
  Speaker 2: just react to it and dole it out.
• 21:50
  Speaker 5: You know, take it under Chin.
• 21:52
  Speaker 3: I think what you said there was exactly the right word.
• 21:55
  Speaker 3: Don't react, but respond.
• 21:57
  Speaker 4: And it's about I called it the be proactive, prosilient, pro.
• 22:02
  Speaker 3: Experimentation, pro growth.
• 22:05
  Speaker 4: So it's really the pros and I spoke about this
• 22:09
  Speaker 4: dilemma that most companies are trapped between the panic zone
• 22:12
  Speaker 4: and the complacency zone. Recognize where you are and get
• 22:16
  Speaker 4: into the learning and growth zone. That's the first the
• 22:19
  Speaker 4: first quarter action. The second quarter action would be be
• 22:22
  Speaker 4: aware of the rubber band effect. Right now, we're all growing,
• 22:26
  Speaker 4: we're stretched, we've got aspirations, but our rubber band snap
• 22:31
  Speaker 4: back into place very easily.
• 22:33
  Speaker 3: As Tim said right at the beginning, you.
• 22:35
  Speaker 4: Know, we're kind of prisoners of orthodoxy.
• 22:39
  Speaker 3: We're prisoners of a ton of years of doing things.
• 22:43
  Speaker 4: They always done ways, and you can't achieve the full
• 22:46
  Speaker 4: potential of the technology revolution without a leadership revolution. In fact,
• 22:50
  Speaker 4: AI is not just a technology challenge. That's one of
• 22:53
  Speaker 4: the biggest mistakes we can make. It's a leadership challenge.
• 22:58
  Speaker 2: What about beneath the leader, below the leadership level of terrence.
• 23:02
  Speaker 2: What about all of us taken together? What's the most
• 23:04
  Speaker 2: important mindset shift that you think is most urgently required
• 23:11
  Speaker 2: on a mass scale as we all seek to sort
• 23:13
  Speaker 2: of successfully navigate this fast changing world.
• 23:17
  Speaker 4: There's a lot of fear out there. We've got fear
• 23:20
  Speaker 4: of missing out fomo. We've got fear of becoming obsolete phobo.
• 23:24
  Speaker 4: We've got fear of messing up bomo. Apart from that,
• 23:29
  Speaker 4: we've got burnout, record levels of burnout costing trillion dollars
• 23:32
  Speaker 4: a year.
• 23:33
  Speaker 3: We've also got bor out.
• 23:35
  Speaker 4: I was at an organization in Paris recently and employees
• 23:38
  Speaker 4: successfully sued their company for borout cognitive underload.
• 23:42
  Speaker 3: Watch out for.
• 23:43
  Speaker 4: The rise of boor out as more and more of
• 23:46
  Speaker 4: parts of our role, I'm kind of automated borout cognitive underload.
• 23:52
  Speaker 4: Being bored at work is going to become a real thing.
• 23:55
  Speaker 4: And let'sure we are rebundling roles in a way that
• 23:59
  Speaker 4: creates new challenges, new meaning.
• 24:02
  Speaker 3: New purpose.
• 24:03
  Speaker 4: So I think you know, we saw rese a couple
• 24:05
  Speaker 4: of days ago Gallup released its latest annual engagement survey
• 24:10
  Speaker 4: and the scores going down again. I think it's like
• 24:13
  Speaker 4: record levels now in the wrong direction. And my point
• 24:16
  Speaker 4: is we can't achieve these incredible upsides of disruption without
• 24:22
  Speaker 4: motivated workforces, resilient workforces, workforces that have hope. And look
• 24:28
  Speaker 4: as somebody it comes from from Scratford up and abon.
• 24:30
  Speaker 4: It's important to date to introduce a new word into
• 24:33
  Speaker 4: the conversation, an ancient English word that hasn't been used
• 24:36
  Speaker 4: for a long time, but I'm going to share it
• 24:38
  Speaker 4: with you for the first time today.
• 24:39
  Speaker 3: It's the opposite of despair.
• 24:41
  Speaker 4: It means it's called respare and Restpare is hope in
• 24:44
  Speaker 4: the future, fresh optimism, optimism, fresh hope, respare and we
• 24:49
  Speaker 4: need an agenda of respare now in the twenty in this,
• 24:53
  Speaker 4: in this, in this twenty twenty five, because despite all
• 24:58
  Speaker 4: this disruption around us, there an upside.
• 25:01
  Speaker 2: You may have a remarkable repertoire of neologisms and brand
• 25:06
  Speaker 2: new acronyms, but you speak in a lot of sense,
• 25:08
  Speaker 2: my friend, and it's been a great pleasure to have
• 25:11
  Speaker 2: you on very stimulating Where can people find.
• 25:15
  Speaker 3: Any any upcoming or very recent books you want to plug?
• 25:18
  Speaker 2: Where can people find you in contact you?
• 25:20
  Speaker 4: Well, first of all, thanks for the opportunity to have
• 25:22
  Speaker 4: a great double espresso conversation. And it's refreshing to not
• 25:28
  Speaker 4: just talk about AI but also some of the risks
• 25:32
  Speaker 4: around that that I think it's those with the vision
• 25:35
  Speaker 4: and responsibility and those that have ethical leadership as well
• 25:39
  Speaker 4: that will really harness the upside. I think, first of all,
• 25:42
  Speaker 4: my new book, The Upside of Disruption is worth checking out.
• 25:46
  Speaker 4: And number two my website Terrencemoori dot com.
• 25:49
  Speaker 3: I use it.
• 25:50
  Speaker 4: I'm on LinkedIn all the time, so join my community,
• 25:53
  Speaker 4: and I'm often speaking around the world.
• 25:56
  Speaker 3: Tomorrow I fly to Stockholm.
• 25:58
  Speaker 4: So you speak to two thousand business leaders were around
• 26:00
  Speaker 4: the world all about future readiness, Muscle following week, Baralow
• 26:05
  Speaker 4: World and Johanna's burgs On City, So I'm always traveling
• 26:09
  Speaker 4: every week to different parts of the world. I'll be
• 26:11
  Speaker 4: in Boston soon as well at MIT, so catch me
• 26:14
  Speaker 4: at a conference as well.
• 26:16
  Speaker 2: Beautiful and I know correct myself. I think I said neologism.
• 26:20
  Speaker 2: Neologisms is what I'm I'm sorry. I'm sorry, apologize to
• 26:23
  Speaker 2: believe it. I was got to clear your earlier time.
• 26:25
  Speaker 2: But he thought I'd let it slide with that maw
• 26:28
  Speaker 2: of prop ism it why not?
• 26:30
  Speaker 5: Why not?
• 26:30
  Speaker 2: The last note to Shakespeare Terret's great pleasure maybe see
• 26:35
  Speaker 2: you and bossed on them see your past soon.
• 26:38
  Speaker 1: Likes to make sure that you never miss an episode,
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• 26:44
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• 26:55
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• 27:01
  Speaker 1: Until next time,