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Death in Meta: The Colleague Experience Gone Wrong w/ Kelly Monahan · The DEX Show: A Show for IT Change Makers

• 0:02
  Speaker 1: Hey, IT Changemakers, and welcome to The Deck Show with
• 0:06
  Speaker 1: Tom McGraw. Let's get into it.
• 0:10
  Speaker 2: There's nothing we love more on The Deck Show than
• 0:13
  Speaker 2: welcoming a third-time returning guest to the show. And that's
• 0:16
  Speaker 2: because nobody gets a third invite to The Deck Show
• 0:19
  Speaker 2: unless we absolutely love talking to them. And that is
• 0:23
  Speaker 2: 100% true of today's very special guest. We are absolutely
• 0:28
  Speaker 2: hyped to welcome back. future of work and AI advisor,
• 0:32
  Speaker 2: keynote speaker, co-founder of Beyond the Desk, best-selling author, Kelly Monaghan.
• 0:38
  Speaker 2: Welcome back to the show, Kelly. What a delight to
• 0:40
  Speaker 2: see you again. How are you?
• 0:42
  Speaker 1: You too, Tom. I wish I could just bring you
• 0:43
  Speaker 1: everywhere with me and be like my hype man every
• 0:45
  Speaker 1: time I have to go on stage or speak somewhere.
• 0:47
  Speaker 1: That was great.
• 0:48
  Speaker 2: I'm available, actually. That sounds like a good gig. Kelly,
• 0:55
  Speaker 2: it was a funny thing. I have an email from
• 0:58
  Speaker 2: you in my inbox this morning.
• 1:00
  Speaker 1: Yes.
• 1:00
  Speaker 2: Look, nobody's ever accused the show of being overly organized.
• 1:05
  Speaker 2: And yet it seems I'm talking to you here today
• 1:08
  Speaker 2: on launch day of your new book.
• 1:10
  Speaker 1: Is that correct? That is correct. Like I am in
• 1:13
  Speaker 1: launch day mode. We have been going nonstop since five
• 1:16
  Speaker 1: this morning. And I'm so glad that you're fitting me in.
• 1:20
  Speaker 1: And I also know it's super late your time. So
• 1:21
  Speaker 1: thank you for doing this today.
• 1:23
  Speaker 2: No, it's wonderful. Tell us. Give us the book slur.
• 1:26
  Speaker 2: What better time to do it? 100%.
• 1:29
  Speaker 1: So Reclaim the Plot is written out of the idea
• 1:33
  Speaker 1: that we've lost the plot in business of what AI
• 1:36
  Speaker 1: is all about. And so it's really written as a
• 1:38
  Speaker 1: cautionary tale of what could go wrong in leadership decision-making
• 1:44
  Speaker 1: if we move so fast and so fiercely towards AI
• 1:47
  Speaker 1: without taking a big step back and figuring out What's
• 1:49
  Speaker 1: the right leadership behaviors? What's the right culture change? What's
• 1:52
  Speaker 1: the right change management? How do we rethink our business model?
• 1:55
  Speaker 1: And I don't know about you, but I've never seen
• 1:57
  Speaker 1: a technology where every leader wants it and no one,
• 2:00
  Speaker 1: but they don't know for what, like outside of moving faster, better, cheaper.
• 2:03
  Speaker 1: And so that's what the story is about is how
• 2:05
  Speaker 1: can we rethink AI and actually do something different today?
• 2:09
  Speaker 2: Is that not true just to be a devil's advocate?
• 2:11
  Speaker 2: Of course. Is there some truth to the essence of it? Like,
• 2:17
  Speaker 2: The nature of the technological revolutions we've all lived through
• 2:21
  Speaker 2: in our respective lifetimes, they've always kind of, it's been
• 2:27
  Speaker 2: a bit of a build it and they'll come kind
• 2:28
  Speaker 2: of thing, right down to the individual companies themselves, right?
• 2:32
  Speaker 2: Whether that's Google or Facebook or now OpenAI or whomever,
• 2:37
  Speaker 2: before you know how to monetize it too concretely, you
• 2:40
  Speaker 2: do it. And as part of that same instinctive process
• 2:45
  Speaker 2: towards the future, as we all follow suit, you know,
• 2:49
  Speaker 2: companies invest without necessarily knowing what they're going to do
• 2:52
  Speaker 2: with these innovations. And what would be your counterpoint to that?
• 2:56
  Speaker 2: What could be done better, do you think?
• 2:59
  Speaker 1: Yeah, I think it's a very fair point as you
• 3:02
  Speaker 1: think about other technology revolutions. I think the difference with
• 3:05
  Speaker 1: this one, though, is I'm not sure we've seen the
• 3:07
  Speaker 1: same level of spending. You know, as you think about
• 3:11
  Speaker 1: the dot-com that eventually burst for a while until businesses
• 3:15
  Speaker 1: figured it out. And so I think obviously you've seen
• 3:18
  Speaker 1: the headlines. We're starting to figure out, I still think
• 3:21
  Speaker 1: it's going to boom. I actually don't think we're going
• 3:22
  Speaker 1: to have a bust here. I think too much of
• 3:23
  Speaker 1: the at least Western economy is depending on this and
• 3:27
  Speaker 1: certainly the U.S. GDP. But the reality is I think
• 3:31
  Speaker 1: we need to slow down in order to speed up.
• 3:33
  Speaker 1: I'm not sure I've seen a technology where everyone has
• 3:35
  Speaker 1: been given access to a super intelligence at their fingertips.
• 3:40
  Speaker 1: without any governance, without any training, without actually work redesign.
• 3:44
  Speaker 1: McKinsey recently published a research paper that showed the one
• 3:48
  Speaker 1: thing that if you want to get ROI today, you
• 3:50
  Speaker 1: have to redesign the work first. It was the number
• 3:52
  Speaker 1: one thing correlated. So that to me is, it's a
• 3:55
  Speaker 1: cautionary tale because you know what? There has been the
• 3:57
  Speaker 1: internet and there was that huge thing, but then a
• 3:59
  Speaker 1: lot of companies went under and it busted. And so
• 4:01
  Speaker 1: that's my thing is don't be on the wrong side
• 4:03
  Speaker 1: of history with this particular technology revolution.
• 4:06
  Speaker 2: And do you think it's fair to say that AI is,
• 4:09
  Speaker 2: you mentioned governance, like in some way, and I don't
• 4:11
  Speaker 2: want to overstate it, like a particularly dangerous or like
• 4:16
  Speaker 2: technology potentially, particularly inside the work, inside a workplace.
• 4:20
  Speaker 1: I do think it's probably the most, I'm going to
• 4:24
  Speaker 1: put the quotation, dangerous technology that we've given if we
• 4:28
  Speaker 1: do not reclaim the plot. And here's what I mean
• 4:30
  Speaker 1: by that. Right. What I get worried about is agentic
• 4:33
  Speaker 1: AI that we're super, listen, I'm super excited about agentic
• 4:36
  Speaker 1: AI that agent's running. But what is the span of
• 4:38
  Speaker 1: control before I actually don't even know what one of
• 4:42
  Speaker 1: my agents is doing? And so that's what I get
• 4:45
  Speaker 1: concerned about is we haven't designed accountability and ownership of
• 4:49
  Speaker 1: how this is going to work. And so I can
• 4:51
  Speaker 1: see the scale and yes, we can do amazing things
• 4:54
  Speaker 1: with few resources and people. but to what end and
• 4:58
  Speaker 1: what are the unintended consequences? If I've got 100 agents running,
• 5:01
  Speaker 1: I couldn't manage 100 people, let alone 100 agents. And
• 5:05
  Speaker 1: so I think that's where some of the danger comes
• 5:06
  Speaker 1: from is we haven't redesigned our orgs or figured out
• 5:09
  Speaker 1: how do we actually control this technology so we're still
• 5:12
  Speaker 1: in the driver's seat.
• 5:13
  Speaker 2: And one thing that's sort of occurred to me quite
• 5:15
  Speaker 2: strongly recently is technology leaders in organizations, they're being asked
• 5:20
  Speaker 2: to do two things, right, which I think speak to
• 5:23
  Speaker 2: what you're getting at, which is like simultaneously managing transform
• 5:27
  Speaker 2: very quickly and be very careful. It's a strange and
• 5:34
  Speaker 2: kind of disorientating remit, would you say? How can that
• 5:39
  Speaker 2: balance be struck properly?
• 5:41
  Speaker 1: Yeah, you know, and I feel so much right now
• 5:43
  Speaker 1: for CIOs and technology leaders. Because one of my favorite
• 5:48
  Speaker 1: exercises I do when I get in front of an
• 5:49
  Speaker 1: executive team is ask, who owns AI transformation for the organization?
• 5:53
  Speaker 2: Who's accountable? Yeah, that's a great question.
• 5:58
  Speaker 1: It's a lot of finger pointing. But I feel like
• 6:00
  Speaker 1: nine out of ten times a CIO or a technology
• 6:02
  Speaker 1: group is like, I guess it's us.
• 6:04
  Speaker 2: I guess it's us, right.
• 6:05
  Speaker 1: I guess it's us. But then you think about it,
• 6:08
  Speaker 1: and it's like, okay, well, the technology has already been deployed.
• 6:11
  Speaker 1: It's now... Workforce planning, how many people do you need
• 6:15
  Speaker 1: versus AI agents? How do we, again, redesign performance to
• 6:17
  Speaker 1: become an AI-enabled organization and incentivize the right behaviors for
• 6:21
  Speaker 1: employees to work differently? These then are all HR, people-oriented questions.
• 6:26
  Speaker 1: And so I think if my advice right now is CIOs,
• 6:29
  Speaker 1: this is actually very much a people issue. And how
• 6:32
  Speaker 1: do you better partner with CHROs and CIOs co-leading this moment?
• 6:37
  Speaker 1: Because it's both IT... And by the way, it's also
• 6:41
  Speaker 1: a lot of legal and governance. So we need to
• 6:42
  Speaker 1: make sure your chief operating officer is involved. Very few technologies,
• 6:46
  Speaker 1: I would say or argue, have truly been a shared
• 6:50
  Speaker 1: C-suite agenda item. And that is not going well for
• 6:54
  Speaker 1: most organizations. Misalignment, a lack of prioritization, and to your point,
• 6:58
  Speaker 1: a lot of finger pointing of who's actually on first.
• 7:02
  Speaker 2: So if you're doing it right, what does that look like? Yes.
• 7:07
  Speaker 1: Yes. So this is the plot framework. I'm just going
• 7:09
  Speaker 1: to take you real quick through the plot framework because
• 7:10
  Speaker 1: I think this is what it's doing right. P stands
• 7:13
  Speaker 1: for power. And so I think, you know, quick story
• 7:16
  Speaker 1: on that. Everyone's handed out a copilot, chat, GBT, Claude,
• 7:20
  Speaker 1: pick your, you know, tool. Everyone's got access to AI,
• 7:23
  Speaker 1: but most employees actually don't feel empowered to control AI
• 7:27
  Speaker 1: and do something with this. So one of my, you know,
• 7:29
  Speaker 1: examples I give right now during my keynotes is I
• 7:32
  Speaker 1: work with a financial services company, installed this great back
• 7:35
  Speaker 1: office agentic AI system. And all of a sudden, AI
• 7:38
  Speaker 1: was making an error. And, you know, junior analysts just
• 7:41
  Speaker 1: watching the error happen. Didn't do anything. And, you know,
• 7:44
  Speaker 1: during the investigation was like, why not? And I was like, oh,
• 7:46
  Speaker 1: I didn't know I was in charge of the agentic AI. Like,
• 7:49
  Speaker 1: I didn't realize that was part of my job. And
• 7:51
  Speaker 1: so they weren't empowered to do that. So to me,
• 7:53
  Speaker 1: it's all about getting power dynamics right and making sure, again,
• 7:56
  Speaker 1: humans have the power over the technology. Two, L is
• 8:00
  Speaker 1: for listening. So making sure leaders are still listening to
• 8:03
  Speaker 1: the humans. We have like totally had this like top-down
• 8:07
  Speaker 1: initiative of go figure it out on your own and
• 8:09
  Speaker 1: not actually get into the front lines of where the
• 8:11
  Speaker 1: friction is happening. O is for ownership. There is very
• 8:14
  Speaker 1: clear accountability and ownership across the C-suite in particular, all
• 8:17
  Speaker 1: the way down of who owns an AI plus human outcome.
• 8:20
  Speaker 1: And then T, Tom, is the hard part. It's truth.
• 8:23
  Speaker 1: Is there enough psychological safety in our organization that we
• 8:26
  Speaker 1: can actually surface when things are going wrong? Can we
• 8:29
  Speaker 1: actually state, hey, maybe we've overspent here, or maybe this
• 8:32
  Speaker 1: isn't working, or maybe we need to bring the humans back,
• 8:34
  Speaker 1: you know, that sort of thing. So I think companies
• 8:38
  Speaker 1: that are distributing power, listening, owning the outcomes, and ensuring
• 8:41
  Speaker 1: truth is being spoken are the ones getting this right.
• 8:43
  Speaker 2: I thought you said T is Tom for a second.
• 8:46
  Speaker 2: I know.
• 8:46
  Speaker 1: I mean, no, I did too.
• 8:47
  Speaker 2: I made the acronym. I couldn't believe it. You did.
• 8:49
  Speaker 2: This is huge. I'm going to be spreading myself thin,
• 8:53
  Speaker 2: especially as your new hype man. I, you know, it
• 8:56
  Speaker 2: was something when I, when I was reading about the
• 8:59
  Speaker 2: book and such, like, yeah, I was struck by something
• 9:02
  Speaker 2: I sort of harbored for a while. I realized, I
• 9:05
  Speaker 2: kind of invite you to destroy this a little bit even,
• 9:07
  Speaker 2: which is like a degree of cynicism with regards to
• 9:10
  Speaker 2: the notion of AI training. Like, you know, like it's
• 9:14
  Speaker 2: such a sort of my definition of it. I'm not
• 9:16
  Speaker 2: saying I don't really belong in the acronym, right. But
• 9:20
  Speaker 2: it is just so intuitive. It's as smart, as you are.
• 9:25
  Speaker 2: It's as wise as you are. It's as imaginative as
• 9:27
  Speaker 2: you are. It's as incautious as you are. But it
• 9:34
  Speaker 2: amplifies all of those things. It scales all of those
• 9:37
  Speaker 2: personal qualities that you bring to it. The notion of
• 9:44
  Speaker 2: having to imbue that, it always defeats me. What does
• 9:49
  Speaker 2: good AI training really look like? Should I be less
• 9:52
  Speaker 2: skeptical about this concept?
• 9:54
  Speaker 1: You know, it's so funny. I was on another conversation
• 9:57
  Speaker 1: this morning talking about the book, and one of the
• 9:59
  Speaker 1: things that came up was fear and how fearful and
• 10:02
  Speaker 1: how do you employees handle the idea that they may
• 10:04
  Speaker 1: be training their replacement with AI? Because we all want
• 10:07
  Speaker 1: to train AI, but that means we're training them to
• 10:09
  Speaker 1: do exactly what we do. And the analogy that I'm
• 10:12
  Speaker 1: giving to people right now is I think we need
• 10:16
  Speaker 1: to rethink what it even means to train AI. AI
• 10:19
  Speaker 1: is really great at helping us, if we have efficiency,
• 10:22
  Speaker 1: do the exact same job and free up people's capacity.
• 10:25
  Speaker 1: If listeners today aren't having 25% to 30% freed capacity
• 10:29
  Speaker 1: from AI today, something's wrong. You should have that much
• 10:32
  Speaker 1: freed capacity at a minimum.
• 10:34
  Speaker 2: Agreed.
• 10:35
  Speaker 1: The question is, where do you reinvest that? And I
• 10:37
  Speaker 1: think that is where, to your point, we're just trying
• 10:39
  Speaker 1: to then reinvest back into AI and training AI to
• 10:42
  Speaker 1: do more of the same, faster, better, cheaper, as opposed
• 10:45
  Speaker 1: to saying, what new value can we create? How do
• 10:48
  Speaker 1: we actually redesign the economics of our business and scale
• 10:52
  Speaker 1: our business? What would I do with that freed capacity?
• 10:55
  Speaker 1: That is a harder question. And that is a human
• 10:57
  Speaker 1: training question, not an AI training question. I think that's
• 11:00
  Speaker 1: what we're getting wrong a bit. We can train AI
• 11:03
  Speaker 1: all day, every day to do the same thing we're doing.
• 11:05
  Speaker 1: It's what is the new frontier? What's the emerging market?
• 11:07
  Speaker 1: What's the new value proposition? That is a pretty human
• 11:11
  Speaker 1: challenge in many ways that I think AI can help supplement,
• 11:13
  Speaker 1: but we need to train humans to think that way.
• 11:15
  Speaker 2: It's such an entrepreneurial mentality. It is. And again, I
• 11:21
  Speaker 2: suppose it's like that brings me back to can that
• 11:24
  Speaker 2: kind of disposition be taught?
• 11:28
  Speaker 1: Well, listen, I will tell you this. I come from
• 11:30
  Speaker 1: the organizational design aspect. I think you can design an
• 11:33
  Speaker 1: organization with the right performance incentives to enhance that culture.
• 11:38
  Speaker 1: I think when you look at most organizations, it is
• 11:41
  Speaker 1: designed for the exact opposite. We don't want innovation in
• 11:44
  Speaker 1: many of our organizations. We incentivize people who do the
• 11:47
  Speaker 1: same thing over and over again without any sort of
• 11:50
  Speaker 1: deviation from that. We reward efficiency and scalability and just
• 11:54
  Speaker 1: things on repeat. That, I think, is what needs to
• 11:57
  Speaker 1: change because people will behave in how they're incentivized. And
• 12:00
  Speaker 1: let's be incentivized entrepreneurship, risk-taking, learning. Most big organizations don't
• 12:05
  Speaker 1: want that. At the end of the day, they want stability.
• 12:08
  Speaker 1: But now we're in this wild, wild west with AI
• 12:10
  Speaker 1: where big organizations have to become this. And so I'm
• 12:13
  Speaker 1: going to say you can design a system that brings
• 12:16
  Speaker 1: this out in people. A lot of it, to your point,
• 12:18
  Speaker 1: you're probably arguing is a bit of a personality trait,
• 12:20
  Speaker 1: which is indeed true. But a system will always win
• 12:24
  Speaker 1: over personality, I believe, over time.
• 12:28
  Speaker 2: You know, look, it's almost, there's no denying that that
• 12:34
  Speaker 2: kind of mindset is the one that's going to benefit
• 12:36
  Speaker 2: most from AI or thrive in this era. Sure. And I,
• 12:41
  Speaker 2: you know, I wonder if it comes down to even,
• 12:43
  Speaker 2: let alone like company training, but education. Do you know
• 12:46
  Speaker 2: what I mean? Like our systems of education, of learning
• 12:50
  Speaker 2: and with expectation have to be completely overturned, right? Like
• 12:54
  Speaker 2: if you think you're just going to start your career
• 12:57
  Speaker 2: and simply spend a career being told what to do, right?
• 13:01
  Speaker 1: Yes.
• 13:01
  Speaker 2: Like that's probably not what a successful career is going
• 13:04
  Speaker 2: to look like in any way, shape, or form, would
• 13:06
  Speaker 2: you agree? Yes.
• 13:08
  Speaker 1: You know, it's so funny. Think back to like this
• 13:10
  Speaker 1: book that came out in the 1960s about the concern
• 13:13
  Speaker 1: of the, you know, organizational soul and that people were
• 13:17
  Speaker 1: losing their sense of grit and entrepreneurship and individual responsibility
• 13:21
  Speaker 1: because they expected the organization to take care of them.
• 13:23
  Speaker 1: And I think we had that model for many years
• 13:25
  Speaker 1: until we didn't. And I think that's part of the
• 13:27
  Speaker 1: transition we're in right now is there isn't going to
• 13:30
  Speaker 1: be this corporate entity that's going to take care of you,
• 13:32
  Speaker 1: that's going to provide for your basic needs. Like you
• 13:34
  Speaker 1: can't depend on one organization to keep you employed for
• 13:37
  Speaker 1: your lifetime. That's just not going to happen. And, you know,
• 13:41
  Speaker 1: it's tough. Like everyone's comparing this to the industrial revolution.
• 13:43
  Speaker 1: And we look back 100 years later, 150 years later,
• 13:47
  Speaker 1: being like, well, thank God for the industrial revolution. Like
• 13:49
  Speaker 1: all this great things happened. For the people in the
• 13:52
  Speaker 1: generation that went from agriculture to industrial revolution, that was
• 13:55
  Speaker 1: really terrible. So I'm also like, let's not forget we're
• 14:01
  Speaker 1: the generation where it's going to get rough of how
• 14:03
  Speaker 1: we transition from a free AI economy to a post
• 14:07
  Speaker 1: AI economy. And there's going to be great benefits. And
• 14:09
  Speaker 1: hopefully 100 years from now, people will say we did
• 14:10
  Speaker 1: a great job. But like this generation, it's going to
• 14:13
  Speaker 1: get tough.
• 14:14
  Speaker 2: Out of interest, you obviously have a background. I remember
• 14:17
  Speaker 2: the first time we met, I think you were working
• 14:19
  Speaker 2: with MED. The first time we spoke, you were working
• 14:21
  Speaker 2: with MED.
• 14:21
  Speaker 1: Yes, sure, yes.
• 14:22
  Speaker 2: Sure was. So you have a great kind of background
• 14:26
  Speaker 2: in big tech and seeing some of the most innovative
• 14:30
  Speaker 2: organizations work from the inside. When we think about that
• 14:34
  Speaker 2: entrepreneurial spirit, is that something that was then or presently nurtured?
• 14:39
  Speaker 2: in these larger, more innovative organizations? Or is that going
• 14:43
  Speaker 2: to be as much of a challenge for these kind
• 14:45
  Speaker 2: of orgs as others, do you think?
• 14:48
  Speaker 1: You know, that's a really good question. And so here's
• 14:51
  Speaker 1: how I would answer that. And again, my time at Meta,
• 14:54
  Speaker 1: I would actually say it was a very innovative organization.
• 14:56
  Speaker 1: And here's why. I came from consulting. You don't ship
• 14:59
  Speaker 1: product or services in consulting until every T has been
• 15:03
  Speaker 1: crossed and every I has been dotted. And you look
• 15:05
  Speaker 1: at a PowerPoint deck or you look at whatever that
• 15:07
  Speaker 1: is that you're delivering and it has to be perfection. Like,
• 15:10
  Speaker 1: I remember just rolling conversations with senior partners of like,
• 15:14
  Speaker 1: the page number is just slightly, you know, off by
• 15:17
  Speaker 1: a fraction of a margin. I'm like, no one's even
• 15:19
  Speaker 1: paying attention. So I think what Meta got right in
• 15:22
  Speaker 1: their culture, which I really respect, and actually I think
• 15:25
  Speaker 1: about this for Beyond the Desk, of shipping products that
• 15:28
  Speaker 1: are 75 to 80% done. And so it's much more
• 15:32
  Speaker 1: of that MVP type, ship it and see what happens.
• 15:35
  Speaker 1: Because then guess what? You're getting customer feedback really quick.
• 15:38
  Speaker 1: You are able to not hold it so precious in
• 15:42
  Speaker 1: some ways and realize it's totally an iterative process. And
• 15:46
  Speaker 1: if you go on like Meta's campus, the walls aren't
• 15:49
  Speaker 1: finished because it's just meant to be this building innovative culture.
• 15:53
  Speaker 1: And so at first I was like, oh, wow. And
• 15:54
  Speaker 1: coming from, again, like a Deloitte University where it's a
• 15:56
  Speaker 1: five star experience to like, why haven't we finished your
• 15:59
  Speaker 1: drywall here was a bit of a culture shock. But
• 16:02
  Speaker 1: I think that's what big organizations need to become is like,
• 16:05
  Speaker 1: let's bring down the drywall. Let's start shipping things. Not
• 16:08
  Speaker 1: 100 percent. But again, I mean, I have a big
• 16:11
  Speaker 1: caveat to that, which Meta, I think, has learned, too. Safety,
• 16:14
  Speaker 1: governance and trust are a big part of that. And
• 16:16
  Speaker 1: you can't sacrifice shipping at speed if you're going to
• 16:20
  Speaker 1: actually diminish that trust in that process.
• 16:24
  Speaker 2: Naming no names or naming names as you like, because
• 16:27
  Speaker 2: it's a positive question I'm going to ask you. Who
• 16:30
  Speaker 2: fits your definition of like a platonic ideal of a
• 16:34
  Speaker 2: suitable leader for this era in 2026? What catches your
• 16:39
  Speaker 2: attention and stands out in the way they lead organizationally
• 16:42
  Speaker 2: or individually? inside the organizations?
• 16:45
  Speaker 1: Yeah, there's a couple organizations that I think have been
• 16:48
  Speaker 1: surprising who are doing this, I would say, very well.
• 16:53
  Speaker 1: First is TIA Financial Services. I've had the opportunity to
• 16:57
  Speaker 1: work with Satri, who is their CIO over there. I
• 17:00
  Speaker 1: love his perspective on AI transformation. Claire is a CHRO,
• 17:04
  Speaker 1: owns AI Transformation. Like it's just, it's a really good
• 17:07
  Speaker 1: example of HR and IT figuring this out together. And
• 17:11
  Speaker 1: I think moving at speed, but also moving in balance
• 17:15
  Speaker 1: and making sure they keep that workforce. There's a great
• 17:16
  Speaker 1: checks and balances there. And so I think they're a
• 17:18
  Speaker 1: great company to work, you know, look at. And they
• 17:20
  Speaker 1: also have like so much tech deck that they have
• 17:22
  Speaker 1: to figure out. It's not like there's a startup that
• 17:24
  Speaker 1: can be an AI native organization. So they're pretty cool.
• 17:27
  Speaker 1: The other one I think a lot of too is Walmart,
• 17:30
  Speaker 1: which is again, is maybe a bit of a surprise.
• 17:33
  Speaker 1: but they have so many AI tools. They've adopted so quickly.
• 17:36
  Speaker 1: They've empowered their frontline staff. Like it's just, it's another
• 17:39
  Speaker 1: good model of here's how we re-event an existing business
• 17:43
  Speaker 1: model and put AI in the hands of people and
• 17:45
  Speaker 1: let people go be people and give her, deliver better
• 17:47
  Speaker 1: customer value and growth. So I just love that both
• 17:50
  Speaker 1: of their missions are much more growth reinvention as opposed
• 17:53
  Speaker 1: to how do I take costs out of business.
• 17:55
  Speaker 2: And, uh, any, like cool novel secrets of adoption, of
• 17:59
  Speaker 2: fostering adoption, of nurturing it, but you see that you
• 18:02
  Speaker 2: think are really sort of just smart and sharp?
• 18:06
  Speaker 1: Well, I think number one, which I mean, I know
• 18:09
  Speaker 1: this sounds so crazy, but like, or simple, they have
• 18:12
  Speaker 1: a change management program in place. Like we have just
• 18:14
  Speaker 1: so many leaders have just skipped over. This is a
• 18:17
  Speaker 1: massive change management overhaul that we have to do. And
• 18:21
  Speaker 1: so I think one recognizing that and like, keeping an
• 18:24
  Speaker 1: eye on that and having a program in place to
• 18:26
  Speaker 1: help people through that is huge. Second thing is having
• 18:28
  Speaker 1: a skilling and training program. Like most organizations today have
• 18:31
  Speaker 1: no clue the skills within organizations. They know headcount and
• 18:35
  Speaker 1: they know jobs, but they have no clue of actual skills.
• 18:38
  Speaker 1: And so Accenture is another really good model who has
• 18:41
  Speaker 1: a technology quote and program, who it doesn't matter who
• 18:44
  Speaker 1: you are in the organization, you have to stay at
• 18:46
  Speaker 1: a level of like technology IQ in order to stay employed.
• 18:50
  Speaker 1: So like, that's another good example of just like We're
• 18:52
  Speaker 1: not going to just have a nice mission statement of
• 18:54
  Speaker 1: adopt AI. It's you have to do the training and
• 18:58
  Speaker 1: the curriculum and the hands-on exercises to prove proficiency in
• 19:01
  Speaker 1: these tools. And I think it's great because then you
• 19:03
  Speaker 1: know what? You can go be marketable no matter where
• 19:05
  Speaker 1: you want to go because you truly have like AI
• 19:07
  Speaker 1: fluency today. So change management and actually putting your money
• 19:11
  Speaker 1: where your mouth is with the workforce and development is
• 19:13
  Speaker 1: a huge thing. And again, this is what I get
• 19:15
  Speaker 1: fearful of. If the CIO and IT fully is like
• 19:18
  Speaker 1: responsible in owning AI transformation and they're not great at
• 19:21
  Speaker 1: this stuff, right? Give it to the HR people, give
• 19:24
  Speaker 1: it to the people or CEO office who does this. Like,
• 19:27
  Speaker 1: I just think this is where IT gets stuck is
• 19:30
  Speaker 1: they're trying to do it all. And I just also
• 19:31
  Speaker 1: don't think it's a fair ask on their side.
• 19:36
  Speaker 2: Speaking of IT and change management, what outcomes and what
• 19:41
  Speaker 2: metrics do you think organizations should be prioritizing around now?
• 19:46
  Speaker 1: Well, here's where you get a little bit nervous because
• 19:48
  Speaker 1: I think we have gotten a little bullish on implying
• 19:52
  Speaker 1: AI-agentic solutions in both the EX space and the CX space.
• 19:57
  Speaker 1: And they're measuring, oh, my customer's service reps don't have
• 20:01
  Speaker 1: as much time on the phone anymore with people. That's
• 20:05
  Speaker 1: because your customers are stuck in a hyperloop trying to
• 20:07
  Speaker 1: figure out how to talk to a person and And
• 20:09
  Speaker 1: they're getting spun around with an AI agent. And like that,
• 20:11
  Speaker 1: to me, if you don't have the metrics right, you've
• 20:13
  Speaker 1: actually just diminished the customer experience, but it's not showing
• 20:17
  Speaker 1: up anywhere in your dashboard, if that makes sense. And
• 20:19
  Speaker 1: so I think we have to figure out when it
• 20:21
  Speaker 1: comes to the digital experience, what really makes a great experience?
• 20:25
  Speaker 1: Like what does good look like? And making sure that
• 20:28
  Speaker 1: we're using AI in such a way to amplify that,
• 20:30
  Speaker 1: to use your word earlier, not diminish that. And if
• 20:34
  Speaker 1: we use classic metrics, like time spent on phone or
• 20:37
  Speaker 1: minutes to resolving problems some sort of complaint, how many
• 20:41
  Speaker 1: minutes we're spending online, even like in some engagement metrics.
• 20:43
  Speaker 1: I just don't know if that's the right area of
• 20:45
  Speaker 1: our focus. I think, again, we've got to push ourselves
• 20:47
  Speaker 1: of what does good look like? What is value? And
• 20:50
  Speaker 1: how do we get better at measuring some of those
• 20:52
  Speaker 1: qualitative aspects of the experience?
• 20:54
  Speaker 2: Yeah, I was going to say close to.
• 20:56
  Speaker 1: It's all qualitative today. And guess what? AI can actually
• 20:58
  Speaker 1: help us. AI is great at qualitative research. And so
• 21:01
  Speaker 1: I think we can probably actually use AI to crack
• 21:03
  Speaker 1: that code.
• 21:05
  Speaker 2: Very true. Very true. You know, I was going to
• 21:06
  Speaker 2: start the whole conversation, Kelly, asking you about Beyond the Desk,
• 21:10
  Speaker 2: but then the book fell and so we had to
• 21:12
  Speaker 2: dive in. But I think since we last spoke, you've
• 21:14
  Speaker 2: also launched Beyond the Desk. Yes. And tell us a
• 21:18
  Speaker 2: bit about the inspiration behind it and maybe how it
• 21:20
  Speaker 2: complements the Reclaim the Plot as well. Yes.
• 21:24
  Speaker 1: So, you know, Tom, last fall I was sitting just
• 21:27
  Speaker 1: looking around Silicon Valley, you know, where I was working,
• 21:30
  Speaker 1: and I thought to myself, really losing the plot here
• 21:33
  Speaker 1: of what this is about. Like, you know, the whole
• 21:36
  Speaker 1: holy grail of, I think it was the billboard that
• 21:38
  Speaker 1: has got me one day of like, we're building the
• 21:40
  Speaker 1: first $ 1 billion company with one employee and all AI agents.
• 21:45
  Speaker 1: And I'm like, you know, like that's in some ways
• 21:48
  Speaker 1: like interesting, but I think a part of business is
• 21:50
  Speaker 1: creating economic opportunity and jobs and And we just, that
• 21:54
  Speaker 1: narrative seems to be shifting. And like the whole premise
• 21:56
  Speaker 1: of agentic AI in Silicon Valley is to replace people
• 22:00
  Speaker 1: with AI. And like, we're all plotting like, that's so great.
• 22:02
  Speaker 1: And I'm like, that's not what this is about. Like,
• 22:05
  Speaker 1: you know, like there's elements like, yes, I'm not naive.
• 22:08
  Speaker 1: Like we will absolutely have less share, I believe, of
• 22:11
  Speaker 1: knowledge workers in the next five to seven years than
• 22:13
  Speaker 1: we have today. And we'll have to figure that out
• 22:14
  Speaker 1: and rebalance labor markets. We told everyone to go get
• 22:17
  Speaker 1: a coding degree. And guess what? AI is great at coding.
• 22:20
  Speaker 1: So now what do we do? And how do we
• 22:21
  Speaker 1: rebalance wages and all that stuff? So these are big,
• 22:24
  Speaker 1: messy questions that I couldn't tackle without being independent. Because
• 22:29
  Speaker 1: I was a spokesperson for Upwork and these are not
• 22:32
  Speaker 1: Upwork questions, right? These are much bigger societal level issues
• 22:36
  Speaker 1: that I actually think executives want to face head on.
• 22:38
  Speaker 1: And I think there's an appetite to get advisory and
• 22:42
  Speaker 1: workshops around this space. So I have a co-founder. She's
• 22:45
  Speaker 1: an IO psychologist and executive coach. And so we've been
• 22:48
  Speaker 1: working with the Fortune 100 this year, advising on how
• 22:51
  Speaker 1: do you not lose the plot is simply with AI.
• 22:53
  Speaker 1: How do you make sure that as you think about
• 22:55
  Speaker 1: the plot framework, you're accounting for the power dynamics, that
• 22:57
  Speaker 1: you've got the right listening mechanisms in place. You have
• 23:00
  Speaker 1: the right ownership and governance plan before just handing out
• 23:02
  Speaker 1: more copilot license. And that there's enough culture in here
• 23:06
  Speaker 1: that you can actually surface back truth. So there's not
• 23:09
  Speaker 1: two shared realities. Like there's two shared realities right now
• 23:12
  Speaker 1: with AI adoption. Leaders who think it's going great, who
• 23:15
  Speaker 1: don't actually use the tool and can't wait to take
• 23:18
  Speaker 1: costs out of the business. And then there's the friction
• 23:20
  Speaker 1: on the front line and employees who are actually using
• 23:21
  Speaker 1: this every day. Beyond the Desk helps merge those two
• 23:24
  Speaker 1: realities into one to hopefully better value proposition on both sides.
• 23:27
  Speaker 2: I had an interesting conversation with Maccabi today, going to
• 23:32
  Speaker 2: be about, you know, preparing our respective children for the future.
• 23:40
  Speaker 2: And what, you know, he.
• 23:43
  Speaker 2: What skills, what form of education is right, you know,
• 23:48
  Speaker 2: and such like. And I was curious, out in Silicon Valley,
• 23:53
  Speaker 2: what are the trends in parenting there? What are the
• 23:56
  Speaker 2: trends in education? How do you think the expectation as
• 24:00
  Speaker 2: to what the future looks like is impacting the way
• 24:05
  Speaker 2: parents in that part of the world are preparing for
• 24:08
  Speaker 2: the future?
• 24:08
  Speaker 1: Yeah. You know, I think it's, it's so funny, right?
• 24:11
  Speaker 1: Cause like, even when I think about my time at Meta,
• 24:13
  Speaker 1: like most of the executives didn't allow their kids to
• 24:16
  Speaker 1: be on social media.
• 24:18
  Speaker 2: Right.
• 24:18
  Speaker 1: Like it's just like, again, like they knew I'm like,
• 24:21
  Speaker 1: all right, this is going to.
• 24:22
  Speaker 2: Be a really different technology.
• 24:24
  Speaker 1: You know what I mean? Um, and so I think what's,
• 24:27
  Speaker 1: what's interesting is I think in many ways they're preparing
• 24:31
  Speaker 1: for a big labor market shift. And I think there's
• 24:33
  Speaker 1: two pathways. One, you can prepare children today and, you know,
• 24:37
  Speaker 1: teenagers and to build and work with AI. I think
• 24:40
  Speaker 1: there's still going to be a very viable, healthy, vibrant
• 24:43
  Speaker 1: knowledge worker economy that is controlling AI. I think there's
• 24:47
  Speaker 1: going to be a very scary middle part of our
• 24:51
  Speaker 1: white collar knowledge worker class that is being controlled by
• 24:54
  Speaker 1: AI and doing work on behalf of an algorithm. And
• 24:57
  Speaker 1: I think that is where Silicon Valley is trying to keep, obviously,
• 25:00
  Speaker 1: their children from. And I think there's also this resurgence
• 25:04
  Speaker 1: of being back in the physical world and providing arts
• 25:08
  Speaker 1: and providing humanities and providing physical labor and services and
• 25:11
  Speaker 1: trades and apprenticeship. And so I think there's actually kind
• 25:14
  Speaker 1: of two really particular pathways of doubling down and providing
• 25:17
  Speaker 1: value back in the real world versus, hey, I'm going
• 25:20
  Speaker 1: to stay in the digital world and actually help build
• 25:22
  Speaker 1: this next digital revolution. Those are the two pathways I
• 25:25
  Speaker 1: see laser focused on and avoiding what I'm calling the
• 25:28
  Speaker 1: messy middle of people who still, we still need to
• 25:31
  Speaker 1: push the buttons. We still got to deliver work. My
• 25:33
  Speaker 1: problem is AI make, much more be controlling that realm
• 25:37
  Speaker 1: of work in the coming days, in years.
• 25:40
  Speaker 2: Coming days.
• 25:41
  Speaker 1: Days. I was like, well, I've been in Codex way
• 25:44
  Speaker 1: too much. We got to get people. But listen, I
• 25:47
  Speaker 1: would say the next couple of years. I mean, it
• 25:49
  Speaker 1: is a short runway if you're paying attention.
• 25:52
  Speaker 2: Agreed, agreed, agreed. Um, uh, we, uh, really enjoyed, uh,
• 25:56
  Speaker 2: your recent, uh, ask me anything. It was AMA over
• 26:01
  Speaker 2: on the next thing subreddit, by the way, sat out
• 26:03
  Speaker 2: to the next thing subreddit and our mutual friend Quentin,
• 26:06
  Speaker 2: who's doing such a great job.
• 26:07
  Speaker 1: He's doing a great job.
• 26:08
  Speaker 2: Um, how did, how did you find the experience? However, however,
• 26:11
  Speaker 2: Reddit is with you out there.
• 26:13
  Speaker 1: You know, I have to be honest with you. I
• 26:14
  Speaker 1: was not a heavy Reddit user until that experience. Um,
• 26:17
  Speaker 1: and I loved it because I think I am trying
• 26:19
  Speaker 1: to find something. a place where I think right now
• 26:22
  Speaker 1: there's so much more dialogue that needs to be had.
• 26:24
  Speaker 1: Like we don't know the answer, right? Like we don't
• 26:27
  Speaker 1: know what the world's gonna look like in two years
• 26:28
  Speaker 1: from now. We don't know what the power dynamics are
• 26:30
  Speaker 1: gonna be like, the geopolitical situation, the economy. And so
• 26:34
  Speaker 1: I think the more that we can get curious with
• 26:36
  Speaker 1: each other and have open dialogue and just honesty, I
• 26:39
  Speaker 1: think that's great. I think Reddit is a great community
• 26:40
  Speaker 1: for that. I mean, I think that is what I'm
• 26:42
  Speaker 1: missing from LinkedIn these days, which it just feels so
• 26:45
  Speaker 1: like AI slop and ads and algorithm testing changing. It
• 26:49
  Speaker 1: was just really nice to be in Q & A
• 26:52
  Speaker 1: and actually like human to human, like right back and forth.
• 26:55
  Speaker 1: We had some dialogue going on, interactions. It was a
• 26:57
  Speaker 1: wonderful experience.
• 26:58
  Speaker 2: It feels a lot more real, doesn't it?
• 27:00
  Speaker 1: It does. And I think that's going to be at
• 27:02
  Speaker 1: a premium as more and more AI takes on our world.
• 27:06
  Speaker 2: Agreed. you, uh, you, you told a great story actually about, uh, somebody, uh,
• 27:12
  Speaker 2: I will, I will tee you up for the story.
• 27:16
  Speaker 2: Somebody dying at Meta. I know it sounds a bit grim,
• 27:18
  Speaker 2: but it's not as grim as it sounds. Yes.
• 27:22
  Speaker 1: So, um, talk about digital, uh, experience gone wrong. Um,
• 27:26
  Speaker 1: so one of my jobs when I was at Meta,
• 27:28
  Speaker 1: which was grabbing, I loved it. Uh, you know, it
• 27:30
  Speaker 1: was back when we all thought the Metaverse was going
• 27:32
  Speaker 1: to happen. And, um, you know, we were working in
• 27:36
  Speaker 1: the VR. And so we were running these different meetings
• 27:40
  Speaker 1: and trying to figure out, like, how do we make
• 27:41
  Speaker 1: more work happen here in the metaverse? And, like, for context,
• 27:44
  Speaker 1: this was also during COVID. So, like, we were also
• 27:46
  Speaker 1: desperate for, like, getting people back together. Like, it sounds
• 27:49
  Speaker 1: a little more absurd today.
• 27:50
  Speaker 2: Working in the metaverse during COVID. That's a vibe, Kelly,
• 27:55
  Speaker 2: I have to say.
• 27:55
  Speaker 1: That is a vibe, let me tell you.
• 27:57
  Speaker 2: Vibe on vibe there, yeah, yeah.
• 27:59
  Speaker 1: It is. And so we were working with these engineers
• 28:01
  Speaker 1: who all had a background in game design. And so
• 28:04
  Speaker 1: it was like one of these moments, I was actually,
• 28:06
  Speaker 1: it was actually like a pretty high powered leadership meeting.
• 28:09
  Speaker 1: And one of the person's battery died on their headset.
• 28:13
  Speaker 1: And like, we were around this like fake conference table
• 28:16
  Speaker 1: and they're just like, body went immediately gray, their avatar,
• 28:20
  Speaker 1: I should say. And they like kind of, you know,
• 28:21
  Speaker 1: like slumped down and, you know, a ghost appeared, you know,
• 28:25
  Speaker 1: in rows above. And we were all like, oh my God,
• 28:29
  Speaker 1: that was so traumatic. And the game designer was like,
• 28:32
  Speaker 1: how do I tell someone that their battery's dead? They're
• 28:34
  Speaker 1: no longer present. I'm like, I don't know, but that's
• 28:36
  Speaker 1: definitely not it.
• 28:37
  Speaker 2: Bit strong, bit strong maybe.
• 28:40
  Speaker 1: Yeah, I don't know. Maybe a little battery's fine, I
• 28:43
  Speaker 1: don't know. But it goes to show you how hard
• 28:45
  Speaker 1: it actually is to create these human experiences in a
• 28:48
  Speaker 1: digital environment that aren't cringe.
• 28:52
  Speaker 2: True. True. One of the things I always love about
• 28:55
  Speaker 2: catching up with you, Kelly, is that you always force
• 28:59
  Speaker 2: me to think about what's next in the workplace.
• 29:02
  Speaker 1: Okay.
• 29:03
  Speaker 2: Sometimes, in a way, it even frightens me a little
• 29:05
  Speaker 2: bit in our past conversations. So come on, to round
• 29:08
  Speaker 2: our conversation out, hit me with something truly cutting edge
• 29:12
  Speaker 2: in the current workplace that you've recently encountered, or as
• 29:16
  Speaker 2: many as you like.
• 29:17
  Speaker 1: You know, I am.
• 29:20
  Speaker 1: This is cutting edge for me right now, but I
• 29:23
  Speaker 1: am a heavy Codex user. And I would say as
• 29:27
  Speaker 1: a researcher and a keynote speaker and somebody who's growing
• 29:29
  Speaker 1: their business, 75% of all my work I'm doing through
• 29:34
  Speaker 1: agentic AI today and vibe coding, which is like everything.
• 29:40
  Speaker 1: I'm talking keynote presentations. And I think what I have
• 29:42
  Speaker 1: realized so deeply in the last 45 days is software
• 29:47
  Speaker 1: is a constraint. Software has constrained us so much as
• 29:52
  Speaker 1: people to actually deliver and execute what is in our
• 29:55
  Speaker 1: minds and what we actually want to have. And so like,
• 29:58
  Speaker 1: I am off of PowerPoint. I'm off of beautiful AI,
• 30:01
  Speaker 1: all these different, again, software systems that help bring presentations
• 30:04
  Speaker 1: to life. And I just vibe code because it's like,
• 30:07
  Speaker 1: I have an idea of what I want this to
• 30:08
  Speaker 1: look like. I'm even off of Canva. Like all these
• 30:11
  Speaker 1: tools that I thought were like great to help us
• 30:14
  Speaker 1: are really constraining and holding me back. And so I
• 30:16
  Speaker 1: think the very new term future, if people are not
• 30:21
  Speaker 1: vibe coding, if you're working with any sort of software,
• 30:24
  Speaker 1: it's time to like start thinking through what part of
• 30:26
  Speaker 1: that looks like. Now, I think software is still going
• 30:29
  Speaker 1: to be here because a lot of times my agentic
• 30:31
  Speaker 1: AI is working within the software. So I don't have to.
• 30:34
  Speaker 1: And it can speak code on code, which I can't.
• 30:37
  Speaker 1: And so it can actually work around some of these constraints.
• 30:39
  Speaker 1: But I imagine a world of work very soon where
• 30:44
  Speaker 1: we are not really working through software as much as
• 30:48
  Speaker 1: we truly are working through agent to agent. And I
• 30:51
  Speaker 1: used to thought that sounded weird until I got into it.
• 30:54
  Speaker 1: And I cannot imagine doing my job today. Like I
• 30:57
  Speaker 1: do not want to go back to not having a
• 30:59
  Speaker 1: gentle guy at my fingertips.
• 31:01
  Speaker 2: Awesome. Good shout. Good tip. Good steer. Yes. All right.
• 31:05
  Speaker 2: I like it. I like it. Kelly, best of luck
• 31:09
  Speaker 2: with the book. Thanks so much.
• 31:10
  Speaker 1: Thank you.
• 31:11
  Speaker 2: Time for the deck show on launch day. It's a real,
• 31:13
  Speaker 2: it's a real privilege.
• 31:14
  Speaker 1: Yes. Thank you, Tom. Thanks so much for having me back.
• 31:18
  Speaker 2: You know before actually before i let you go um
• 31:20
  Speaker 2: yes uh we i have to make a plug kelly
• 31:22
  Speaker 2: because next week in orlando is the big yes i
• 31:27
  Speaker 2: think it's experience we're out there we're all excited about
• 31:30
  Speaker 2: it and we are hosting uh the deck show we're
• 31:34
  Speaker 2: doing a live um it nerd mastermind it's going to
• 31:39
  Speaker 2: be amazing quiz show come game show at the expo
• 31:42
  Speaker 2: stage in the expo hall that is See if I
• 31:45
  Speaker 2: get this right. That is Monday night at the opening
• 31:49
  Speaker 2: reception in the Expo Hall on the Expo stage at 5.30 p.m.
• 31:57
  Speaker 2: We look forward to seeing you all there if you're
• 32:00
  Speaker 2: listening to this. Do come along. It's going to be
• 32:02
  Speaker 2: great fun. We've got special contestant guests who are answering
• 32:06
  Speaker 2: questions on fun things like the X-Men and Star Wars
• 32:11
  Speaker 2: and other things we all like and enjoy. And there'll
• 32:14
  Speaker 2: be prizes and it'll be just a lot of fun.
• 32:17
  Speaker 2: And we get to see our listeners and some of
• 32:20
  Speaker 2: our listeners too, which is always a great pleasure. So
• 32:22
  Speaker 2: we hope you join us there. Thanks for hanging in
• 32:26
  Speaker 2: for that plug, Kelly. Does it sound like fun to you?
• 32:28
  Speaker 2: Sounds good, eh?
• 32:29
  Speaker 1: Listen, and you know I'm in Orlando. I would be
• 32:31
  Speaker 1: there if I wasn't. I'm on this book tour. I'm
• 32:33
  Speaker 1: going to be on the other side of the country.
• 32:34
  Speaker 1: But I am so excited and having major FOMO.
• 32:37
  Speaker 2: Awesome. Thanks, Kelly. See you very soon. Best of luck.
• 32:40
  Speaker 1: Sounds good.
• 32:41
  Speaker 2: Take care. Bye-bye.
• 32:45
  Speaker 1: That's it for this week's deck show. We'll be back
• 32:47
  Speaker 1: next week. And if you don't already, be sure to
• 32:50
  Speaker 1: follow the show so you don't miss an episode. Until
• 32:53
  Speaker 1: next time.