AI Is Breaking the Economics of Work. No One Is Ready

If AI can free up half a company’s labor capacity, what happens to the people doing the work? Ravin Jesuthasan describes AI transformations that have freed up 40–50% of labor capacity. Is your organization ready for what that means for its workforce? The futurist and bestselling author explains how AI is reshaping the future of work and why its productivity gains don’t have to translate into layoffs. Ravin joins Geoff on this episode of Digital Disruption to discuss generative AI, AI agents, and the impact of automation on jobs. He explains why entry-level roles are under pressure, how traditional career paths are changing, and why judgment, empathy, and curiosity are becoming increasingly valuable. Drawing on examples from Standard Chartered and Unilever, he explores how organizations can prepare employees for new opportunities through upskilling and reskilling. He breaks down what it means to build a skills-powered organization where learning becomes part of everyday work. Ravin also shares how leaders can reinvest AI productivity gains in employee wellbeing, better customer experiences, and continued innovation. Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 00:40 AI frees up half the work. what happens next? 01:12 How AI is reshaping the future of work 03:30 How AI changes the cost of work and access to talent 06:23 Will AI replace all human work? 09:40 Is the fear of becoming obsolete justified? 12:12 McLean & Company’s human-centric AI program 12:52 AI and the erosion of the entry-level career ladder 17:32 What does “work ready” mean in the age of AI? 19:51 Why human judgment is becoming an essential skill 20:58 How to build a skills-powered organization 23:20 Making learning part of everyday work 24:38 Reskilling employees for new career opportunities 26:23 Turning workforce transformation into action 29:56 Setting a vision and proving ROI with focused pilots 32:15 Who should own workforce transformation? 33:35 Involving employees and preparing them for what comes next 35:12 Unilever’s approach to reskilling and career transitions 36:43 Why digital transformations fail 39:17 Moving from one-time transformation to continuous reinvention 41:16 Making space for learning and employee wellbeing 42:34 How to reinvest AI’s productivity gains 45:44 Why IT, HR, and business leaders need to work together 48:15 Why adding AI isn’t enough to transform work 51:12 The value of outside perspectives in AI transformation 53:13 Final Advice: Learn, unlearn, and relearn 54:40 About Infotech Connect with Ravin: LinkedIn: https://www.linkedin.com/in/ravinjesuthasan/ X: https://x.com/RavinJesuthasan Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

• 0:01Speaker 00

  These AI-powered transformations don't yield 3% or 4%, they get you 40% to 50% capacity release. I said to one of my clients, you know, we freed up 50% of your labor capacity. You've got three non-mutually exclusive choices. You could take it as an opportunity to reset what is a pretty dire work environment with a 40% turnover rate. Or we could redeploy some of the gains so that we are improving what is almost an equally dire customer experience. And the CEO, to his credit, said, I think I'll have a little bit of all three, please.

• 0:41Speaker 01

  This is a show about the future of work and the future of tech. AI is radically reinventing how work gets done. But when a company can free up half its labor capacity, what happens to its people? Today, futurist and bestselling author Robin Jesu Thawson explains which jobs are most vulnerable, why judgment may become our most valuable skill, and how leaders can use AI's enormous productivity gains without simply turning them into layoffs. I'm Jeff Nielsen, and this is Digital Disruption.

• 1:12Speaker 01

  Well, Robin, thank you so much for being here today. Really excited to have you on the program. You know, I want to talk a little bit about AI in the context of the future of work, automation, the impact that it's going to have on all of our jobs. And so, you know, maybe to kick us off, I'd like to ask you more broadly. When you think about the future of work, how do you really conceptualize it? How do you conceive of it? What do you see?

• 1:37Speaker 00

  Yeah, so firstly, Jeff, it's truly a pleasure to be here with you. You know, it's interesting because I was recently asked for a retrospective on my last six books that I've written, and all of them are focused on the future of work and AI. And what started off back in the early 2010s as being this movement towards work being done outside of the traditional confines of what a job was, right? If you think of a job in an organization, the value exchange between company and person, and then how that job is designed, et cetera. That liberation, if you will, if I want to put a phrase, of the job into non-employee-type, non-employment-type work relationships.

• 2:23Speaker 00

  And then in 2016, we published our book, John Boudreaux and I, Reinventing Jobs, that looked at the impact of machine learning and deep learning, and this increasing human-machine collaboration that was kicking in. And then you fast forward, Jeff, to where we are today, where AI has reached a different level of capability with generative AI and AI agents. So, you know, when I think of the future of work, I think it's it's the bending of the demand curve of work in a fundamentally different way, different ways of getting work done that are exponentially more efficient, effective, and impactful than anything we've contemplated in the past.

• 3:06Speaker 00

  But also the opportunity to bend the supply curve of work in a different way, making work increasingly more inclusive and adaptable for human needs than we've ever contemplated in the past. So I don't know if that's too ethereal, but I think of it as, you know, in fairly positive terms if we choose to capture the opportunity before us.

• 3:30Speaker 01

  No, I appreciate that answer, and I think there was a lot wrapped up. You very quickly covered a lot of, I think, different and important concepts. So maybe just on what you called the demand curve of work and the supply curve of work. Can you unpack those a little bit? Like, what do those actually mean? And what's encompassed in those and what's actually changing?

• 3:52Speaker 00

  Yeah, absolutely. So when I think of the demand curve of work, think of it as the mapping of the volume of work against the total cost of work, whether that cost is from a human versus a machine, et cetera. And as you think about, you know, my little retrospective there of these different options for getting work done, as those options have increased from the use of gig workers to other types of non-employee labor, to alliance partners, to AI and, you know, agents, et cetera. The cost of work, which is the Y-axis, has now expanded to include all these options. And what that's done is changed what was that traditional calculus of whereas the volume of work went up,

• 4:38Speaker 00

  the cost would linearly go up to actually now where there is now the separation where as the volume goes up, the cost actually starts to decline as we add to those options. As we substitute, for example, and this is purely an example, the work of employees with agentic AI, the cost of the token cost, the compute cost, is often a fraction of the cost of the human labor that might be substituted. So that would be one example of that demand curve bending, if you will, from its traditional relationship, what we've had in place for, you know, several hundred years, right? Of as work increases, the cost of work increases.

• 5:23Speaker 00

  Equally, I think with AI, if we think of the supply curve and you think of that inverse relationship, right? Of where, you know, when you think particularly of what it takes to attract people to do work, you know, the use of AI allows us to bring a lot of non-traditional talent into the mix, you know, reducing that total cost of acquisition because we're now catering to a more diverse and broader pool of talent. Talent we might traditionally have closed off from opportunities now are in the mix because we can see their skills and capabilities, and we can see how their adjacent skills and capabilities

• 6:05Speaker 00

  might allow them to take on new bodies of work that perhaps they haven't done, but might be uniquely qualified for. Where perhaps they might not have the right degree, but they actually have the right skills and capabilities to do that work. Is that helpful at all in terms of the double click on both those curves?

• 6:23Speaker 01

  It is, and there's a word you said that really is, you know, I think encompassing of your answer, which is options, that feels like in the last 10 years, a lot of options have opened up around what work could be in terms of how it's actually fulfilled. It's not just, hey, you have people working, you know, 40-hour-a-week jobs. It's, you know, as you said, it's, you know, non-labor work, it's AI, it's gig work. There is a narrative out there that in the next handful of years, all of those options are going to collapse and it's just going to be, you know, just hand it all over to AI. And the future is, you know, all AI, no people functionally. And I'm deliberately painting this in extreme, but I'm curious,

• 7:08Speaker 01

  do you subscribe to some version of that? Or do you continue to see it be a future full of options?

• 7:16Speaker 00

  I think the future is incredibly nuanced, and I know the word nuance is not good for the, for, you know, that's the popular press, right? Who, it's where it's beneficial to paint things and start contrast. I actually think, Jeff, that the future is incredibly nuanced. I think for the foreseeable future, certainly at a minimum, the work requiring judgment, empathy, and presence, human presence, is going to be with us, I believe, you know, for at least my lifetime, if not beyond. I think AI is growing in capability and capacity by the day, as we know.

• 7:58Speaker 00

  But there are so many, but we all know of the jagged frontier of AI. There's certainly many things that can be done, but there are so many impediments to this notion of artificial general intelligence where every body of work can be subsumed by the technology. You know, and it's not just that the work itself has these nuances that get in the way, but I also think we're starting to see in many instances, you know, obstacles get put up, you know, to the deployment of AI. We're seeing that with the data centers, right? The energy consumption, the water usage. We're seeing that with AI acting, you know, badly in some instances

• 8:42Speaker 00

  when we think about, you know, some of the unsanctioned activities that we've seen. We're starting to see the backlash from schools and the workforce as a result of the cognitive decline from the use of AI.

• 9:00Speaker 00

  The last barrier, I will say, that we're seeing is the impact on the psyche of the worker. You know, we're seeing this, this phobos, if you will, this fear of becoming obsolete, rising by the day as more people start to use AI, as they see, as they shift from seeing, oh gee, it's great at substituting some of my work today and making my life easier to, my goodness, it is so much more evolved today than it was yesterday, and I can see it taking over my work, you know, for, for certain types of work. And, and so I do think all of those barriers or risks, if you will, will act as constraints on the evolution of, of AI, if that makes some sense.

• 9:41Speaker 01

  Do you think that fear of becoming obsolete, that, that phobos, I haven't heard that, but I like it, is that well-founded? Like, is that a rational fear? Or is it something that we just need to kind of train out of people?

• 9:54Speaker 00

  It's a really good question. I think for certain types of work, it is, it is a very rational fear. There's, there's emerging data, particularly in the United States, of how in professions like, you know, finance, finance, insurance, professional services, consulting, law firms, et cetera, over the last four years, as we've had generative AI in place, there has been an absolute decline in overall employment, and it's, it's, it's a very significant decline. And we're seeing that, you know, I lead a large consulting business, I'm seeing before

• 10:35Speaker 00

  my very eyes how our traditional pyramid is starting to morph into more of a, of a diamond shape, right, where the work we might have relied on a bright young analyst coming in, having her make her mistakes for three years with applying her strong technical skills, analytical skills, acquiring those domain and enabling skills that make that person, you know, a, a senior consultant, that work is rapidly being substituted by AI. So, quote unquote, the new entry level is someone who actually has been doing the work for a while, who can apply judgment, who can apply a knowledge of the domain to the problem, who can apply an understanding of the cost, how the customer is going to receive

• 11:17Speaker 00

  a particular piece of insight to the actual development of that insight. So you're starting to see, you know, in, in some of these professions, the evolution of the technology be very visible to both organization and employee. So, so I do think that phobos is well-founded in some domains. But again, this is where the nuance is really, is important, right? Because it's work that was highly repetitive, it was rules-based, it was technical in nature, it was often analytical and quantitative in nature, so it lends itself well to the deployment of AI. I think there are other professions where, you know, that, that phobos is, is probably

• 11:58Speaker 00

  not as, as pronounced, because, again, those professions I mentioned, right, where it's judgment, it's empathy and it's presence, where, you know, that AI is just not there yet.

• 12:12Speaker 01

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• 12:53Speaker 01

  You hit on another fear that sounds like it's starting to be borne out in data, and I've, I've seen some reports that suggest this recently, which is that, that diamond-shaped organization, right? And, and this is sort of the erosion of the entry-level role. And one of the fears I have, and, and I guess it's, you know, a broader societal issue, is this sort of erosion of the economic contract of there's this track from education early in your career to we will train you, you will learn, you'll get these skills and you'll kind of move up this ladder. It, it's starting to appear as though that's fundamentally breaking, and that feels like

• 13:35Speaker 01

  it has implications for firms, and, and maybe frankly, firms get off easy, but for, for people, for demographics that are going through this, that's a really, that's a really, I think, powerful fear. Is that something you worry about? And, and what would your reaction be to people who are experiencing this?

• 13:54Speaker 00

  Yeah. Oh, I worry about this all the time, actually. I've got a, a 28-year-old and a 25-year-old and a relatively new grandchild, so I see this on a personal level. So I actually think, and this is a bit of the thesis, Jeff, of my upcoming book, it's called Navigating the Intelligent Age, and it'll be published by the MIT Press in 2027. And it, it looks at it from both the lens of the individual, the organization, academia, broadly defined, as well as public sector leaders. And I have the privilege of having worked with the Singapore government for the last, gosh, more than 10 years now, on their transformation journey towards becoming what they would

• 14:38Speaker 00

  call a, a skills-first economy. And, and so I absolutely see it. I do think there are, from a company perspective, there are, and, and an educational sector perspective, there are two things changing. One is companies in the past used to, I'll go back to my example, right? This, this tacit recognition that I'm going to hire someone out of MBA school, and I'm going to spend the first three years letting him or her make their mistakes as they learn our craft. But in that time, you know, and, and they may not be the most revenue-generating, most productive person in the world, but in three years, they're going to know all of our stuff, coupled with all of this deep, extraordinary technical knowledge that they already have,

• 15:22Speaker 00

  and they're going to be this extraordinary consultant. And I could wait those three years. I think the calculus is shifting in two ways. One is the definition of work-ready is changing really quickly. And I think I'm, I'm seeing a couple of things happen. I'm seeing companies start to place the burden on the academic sector to say, we need you to produce work-ready talent that looks very different from the ones you've produced for the last 150 years. We actually need people who in the past, we might have considered a two-year consultant. We need you to produce that person today when we hire them. And that's changing academia in really radical ways.

• 16:05Speaker 00

  Interestingly, there are some great models in Switzerland and Germany that have been, been around forever, that are coming back into vogue, because they are explicitly geared for providing that work-ready talent. In a number of instances, kids in Switzerland, when they graduate, actually have worked with, in some cases, three to four different employers doing the work before they come into full-time employment, as we would classify it in, in the United States or Canada. So the definition of work-ready, I think, has some, has, has some good examples there. The other change that's happening is companies, as they're shifting this entry-level burden

• 16:44Speaker 00

  to the academic sector, are increasingly prioritizing, how do I keep my existing workforce, who I've invested billions in for the last decade or so, how do I keep them relevant for a changing world? Because my operating model is changing, all of those human and enabling skills that, that that workforce has developed over the last 10, 15, 20, 30 years are incredibly valuable to me. So how do I keep teaching them the new technical skills as AI plays out, as the work shifts, as new skills emerge, so that they can stay relevant? So those are the two big shifts I'm seeing as, as organizations and academia, the public

• 17:28Speaker 00

  sector, start to adjust to this new reality.

• 17:32Speaker 01

  With both of those answers, you know, the notion of skills is really sort of coming to the forefront. And I want to, I want to come back to the, to the first one you said there, which, which is to me, the definition of work readiness. Can we dig a little bit deeper into that? Like, what is the gap there? What does work ready mean in 2026 that it is fundamentally different? And what do educational institutions need to be doing to close that gap?

• 18:00Speaker 00

  Yeah, I think there's, there's a number of things here. Educational institutions have been really good at teaching people technical skills. And, and I think there are so many new, more efficient and effective ways, if it's purely about teaching technical skills. What has often been minimized or gone unnoticed is the value of those academic institutions in teaching community, in teaching about how we collaborate together, in sharing the burden of that productive struggle of learning, right? Because learning is difficult. Learning is hard, you know, but when you're doing it in a, in a cohort, in a community with the right tools and capabilities,

• 18:41Speaker 00

  we, you know, it's misery shed, right? And so these academic institutions build a community that learns how to grow together, that relies on each other, that is supportive of each other. And it also starts to build those enabling skills, right? Curiosity, learning agility, all of those things that are required for someone to be successful going forward. And so I do think the academic sector is shifting pretty quickly, you know, to sort of recognize that the real value is not in teaching someone how to become an accountant. My goodness, you know, there's much cheaper ways of teaching someone to become an accountant. You know, I don't need to spend,

• 19:24Speaker 00

  you know, my son's going through his MBA and I think it's costing him something like $250,000. You know, this need to pay that money for advanced mathematics or, you know, advanced finance, et cetera. But it's the community, the learning agility, the curiosity, you know, forcing people to sort of develop these broad enabling skills, which is what's going to stand them in good stead for the next 50 years of their working life. So some of the skills that I'm seeing that are incredibly important are, as I mentioned, learning agility and curiosity. The one that, when I talk about work ready, if there is one skill that, that employers are

• 20:05Speaker 00

  looking for in this new definition of work ready, is does the person have, have judgment? Can they express judgment, which requires them to have depth in the technical skills, requires them to have seen those skills, operate in different environments, to have seen the consequences of a right decision and a wrong decision, because that's how you develop judgment? It's also why I'm very intrigued. I think it was Ernst & Young that announced this, I believe, a 12-month internship. So actually having people come in and learn in their environment and make all those entry-level consulting mistakes over the 12 months, and then going

• 20:45Speaker 00

  back to school and continuing. That, to me, is such a brilliant idea, because you teach, you teach judgment, right? That's what you, people build up in through those 12 months.

• 20:58Speaker 01

  A phrase like teaching judgment is something that is easy for me to be like, yes, that sounds good. And in practice, at scale, I, I think it's a lot harder to do than just everybody. Look for judgment, teach judgment. Like, it's, to you, to use your word, it's very nuanced, and it is a very refined skill. And I'm coming back to that word, skill, because we've talked about skills being developed in academia. But you've also written pretty extensively about, you know, skills-powered organizations.

• 21:29Speaker 00

  Mm-hmm.

• 21:30Speaker 01

  What does that mean? How do you actually build an organization that can do this at any sort of scale? What, what does that look like?

• 21:38Speaker 00

  Yep. So let me, let me actually give you a real life example. And this is, that, that book you referenced, which came out in October of 24, was written with a woman who's now the chief operating officer of Standard Chartered Bank. And Tannaj and I worked together over a four-year period where Standard Chartered generated a total shareholder return of 332%. One of the highest performing financial services, if not organizations on, on the planet. And they would say that at the heart of their transformation was this journey to becoming a skills-powered organization. And that journey had three, three legs to the stool. But more importantly,

• 22:18Speaker 00

  it started with one number. And, and that number is, to my earlier point about companies focusing their efforts on keeping the existing workforce relevant. When, when companies typically transform, what has traditionally happened, Jeff, as you know well, is there is this restructuring or reduction in force, where talent with legacy skills are, you know, are, are eliminated, people are sort of rendered redundant, and then talent with new skills are, you know, hired into the organization. That is a very expensive disruptive proposition. What Tannaj

• 22:59Speaker 00

  showed their board was that instead of doing that, that they could actually save £50,000 per employee by reskilling talent from their sunset roles to their sunrise roles. That was the impetus for their transformation. That then triggered this three-legged, three-phase journey, if you will. The first was to say, if we're going to reskill people, how do we make upskilling and reskilling? How do we make learning a habit of the organization? Not something that Jeff does on a Saturday night when the kids are in bed at 10 o'clock, not something that Robin does when he's on holiday, because he has no other time to, you know, acquire new skills,

• 23:41Speaker 00

  but something that is a part of how we run our business. So that included expanding the number of learning days that they have, that included in their strategic plan being really explicit about how investments in learning were going to drive the development of new skills and new capabilities for the organization. That was phase one. So this, this consistent messaging, and as an, as an anecdote, it, it is, I've participated in these sessions, they have learning week. They've gone from 20 hours mandatory learning a year to 120. They have learning week, where everyone from Bill Winters, the CEO, down to the tellers, actually take time out to

• 24:25Speaker 00

  participate. And, you know, and I've heard from some of the tellers, my gosh, I was on the same call as Bill was. And he's learning the same stuff that I'm learning, which is, as you might imagine, incredibly motivating for people. That's phase one of the journey. Phase two was to say, how do we make this tangible and economically, and delivering an economic return? So they identified some high priority roles, where that reskilling would happen, from the sunset to the sunrise roles, specifically taking tellers out of a shrinking branch network and reskilling them into becoming relationship managers in their high net worth businesses. The enabling skills, communication, empathy, care for the customer, were entirely consistent. What they

• 25:10Speaker 00

  were spending the, the reskilling dollars and time on was in the technical skills. Does that person understand the product portfolio? Do they, can we teach them some basic financial analysis, so they can actually help the customer navigate that portfolio and understand the risks and the return available to them? The other priority role was in tech operations, reskilling people from cloud administration into AI development. The core skills of understanding the company's tech architecture, understanding how the different customer bases, internal customers engaged with the platform, and their data needs were all the same. They were teaching the technical skills. And then the last part of the journey was around, how do we ensure

• 25:55Speaker 00

  that this is not an event, but that this is sustainable? So how do we make sure that all of our core processes actually have skills as part of the currency? From strategic planning to workforce development, to budgeting and accounting, how do we make sure that skills, as the currency for work, for how people are deployed, how resources are managed, are a part of our lexicon and how we run this business?

• 26:23Speaker 01

  I really like that approach. I really like the model. It resonates very deeply with me and in terms of my beliefs around, you know, adaptability, reskilling, the core skills that are important for folks. Let's, um, so abstractly, I'm completely bought into that. Let's get like really nitty gritty, hands dirty with this stuff though. So if you want to do that, if you're leading an organization or a function, you say, yes, I'm all in on, on learning, on skills. I want to do this. How, how do you actually execute that? Do you need a specific, you know, learning centric team? Do you ask HR to do it? Is it up to like the land, the, um,

• 27:05Speaker 01

  is it up to the line managers or, you know, in your example, folks in IT? Do you bring in, you know, consultants or trainers in some capacity? How do you actually implement this in your organization?

• 27:17Speaker 00

  So I, I think there's, I think of it as a three plus three, Jeff. So the three plus three is what are the core capabilities that you as an organization need to have? To be that AI driven, skills powered organization? And then the other three is how do you get started? So the first three, the three core capabilities that we explored in, in, in the skills cloud organization book were this notion of work design. Do I understand how the demand for my work, the demand for my customers, the changing external environment? Do I understand how the demand for work and thus the skills, human or machine, is changing? And then do I understand how the supply of skills, again, human or machine?

• 28:01Speaker 00

  Humans could be either employees, gig workers, global capability centers, outsourcers, alliance partners, et cetera. And then meshing the two together in the redesign of work to ensure a, an optimal combination based on costs, capability, risk, et cetera. So this understanding of the design of work, demand of skills and supply of skills. Secondly, when I do that, I see gaps, right? I see where the, the demand is over here and the supply is over here. Can I make development of, of, of, of skills, the closing of those gaps and organizational capability?

• 28:39Speaker 00

  Can I make that rapid upskilling and reskilling of, of, of the workforce and, and machine skills as well? A core capability and can I do it at scale and speed? That's the second capability. And then the third capability is because we're not just developing skills because it's a nice thing and it's a good thing. It has to be deployed back to productive work. So can I deploy those skills as they're developed, whether it's machine skills, human skills, back to productive work as quickly as possible? Back to where those gaps were first observed? And that could be, you know, upskilling someone in an existing job. Could be upskilling or reskilling someone for a different job.

• 29:21Speaker 00

  It could be through an, an, an internal gig marketplace. It could be through a more agile talent pool that instead of being stuck in jobs, is now flowing to where the demand is. And that's the other big shift that we're seeing, Jeff, is companies moving away from, you know, when I think of my employees, you know, an employee is synonymous with someone in the job, to actually recognizing that there are now not just that fixed model, but more flexible models and flow models of work that allow me to create much higher velocity in how work, work gets done and how people get signals as to how they need to develop new skills.

• 30:01Speaker 00

  So those three capabilities of work design, skills development and skills deployment would be the first three. The next three is how do I get started quickly? It's really important that there is a naught star that anchors this journey of becoming AI driven and skills powered. A naught star that says, over the next three years, pick a timeframe, here's the economic impact of this transformation. Here's what this transformation is going to look like to my customers and my shareholders. Here's what it's going to feel like to my leaders, my managers and employees. And here are the core foundational elements that we absolutely have to nail to make sure this transformation actually delivers.

• 30:45Speaker 00

  You know, it could be, we have the right AI stack. It could be, we have the right skills taxonomy. We have an internal talent marketplace. There's multiple key foundational elements. Secondly, just like Standard Chartered Bank, these things can be incredibly, can be, can become very theoretical unless they deliver quick results. And that's why I think piloting in narrow areas is really important. So Standard Chartered Bank going deep and focused with the relationship managers and going deep and focused with the tech operations folks, delivered quick results in six months, real economic ROI, which then brought the rest of the organization along.

• 31:28Speaker 00

  Because if this is about generating your usual three, three percent increases in efficiency, you can do that in annual headcount reductions that companies go through. The gains that we're seeing, and I've written extensively about this, are not three percent, but 30 to 40% capacity release, 25% productivity increases because of that bending up the demand curve that I talked about. And then the third dimension, very similar to Standard Chartered Bank, is how do we make sure that this is not an event? That this is a transformation that continues into perpetuity by building in skills and AI into how we run every facet of this business?

• 32:13Speaker 00

  Is that helpful?

• 32:15Speaker 01

  It is, um, and it makes sense to me. I, I want to talk in just a minute about the notion of this as a transformation, but just before I do, all of that's made sense to me abstractly. I, I want to come back and just kind of hammer on the, the specific question that I was trying to learn more about, which is, if you're actually going to do this transformation, who in the organization needs to own it and, and who do you need executing it for it to be successful?

• 32:42Speaker 00

  Yep. So I think it has to be owned by three, three critical stakeholders. You have to have the business leaders actually initiate this with a clear understanding that it's going to deliver an economic return. You have to have your line managers be the ones who actively manage it in a day to day basis because they're the bridge between what the customer's looking for, what leadership's looking for and what actually gets delivered. But perhaps the most important stakeholder is who's actually doing the work. Too many transformations, particularly digital transformations, tend to be top down initiatives that are disconnected from how the day to day operates.

• 33:26Speaker 00

  You know, it's, it's transform versus perform. It has to be connected to the perform and nobody knows the perform better than the people actually doing the work. And so I always say to my clients, um, the organizations that I advise, the people doing the work absolutely have to be in the sausage making gear, right? Because as you might have the most well documented processes, you might be a lean Sig Sigma organization. That's all great. The person actually executing knows where all the bodies are. They know where stuff gets wrong and they need to be involved. They need to have an incentive to actually participate and they need to have the opportunity

• 34:09Speaker 00

  to, to, to make a difference and an opportunity to stay relevant as the work is changing. Whether that's staying upskilling for the job that they're in today, being rescaled for something different, or if the business model is changing so dramatically, how do we outscale them? How do we ensure that we're not doing the traditional reduction in force where I give you a check and a phone number? To actually saying, my promise to you is that I will keep you relevant and ready for opportunities. So outscaling means I'm going to find you an opportunity. I'm going to make sure that your skills are relevant and I'm going to help you get placed in that opportunity. I've got a number of clients that actually do that now

• 34:52Speaker 00

  because it's an extension of their mission and purpose that my obligation to you is not just as long as you're an employee, but it's to get you ready for post employment.

• 35:03Speaker 01

  It's a really nice sentiment. I'm, I'm like, I'm, I'm excited to hear that people are actually doing that in practice because I've, I, I could see it being written off by organizations. So it's exciting to hear.

• 35:12Speaker 00

  Actually, let me give you a real life example, right? Unilever. Unilever has always held itself out as being a company of mission and purpose. And it goes back to when Alan Job was CEO and Lena and I were C H O role. I had the privilege of working with them on their framework for the future of work that explicitly had those three types of reskilling, if you will. The upskilling for the job I'm in today, reskilling for something different within the company, or the opportunity to move beyond. A number of years back, this was really put to the test and they came through with, um, with bright shining colors. One of their factories in Germany had reached its end of life, I think a 50 year life.

• 35:56Speaker 00

  And they had made the commitment, you know, as a company of purpose might do, to not just lay waste to this factory. And, um, they actually made the commitment to turning it into a recycling plant. But it didn't just end there, right? So my, the, the sense of mission to the environment, the sense of mission to the community. 80% of the people who worked in the previous plant found employment in the recycling plant. So they rescaled them for the jobs that the recycling plant was looking for. The others chose, you know, retirement, chose to move on to something different. But 80% of the workforce in that old plant were employed by the recycling plant. That to me was the proof in the pudding.

• 36:43Speaker 01

  It's a really cool story and I'm sort of smiling to myself because I feel like recycling is an apt metaphor for a lot of what we're describing. So it's amusing that it's actually a recycling plant.

• 36:55Speaker 00

  Indeed.

• 36:56Speaker 01

  Let's talk, though, about digital transformation, which, you know, functionally this is. It's transformation, probably if you're doing it in, you know, this year, it's there's some digital component to it as well. You know, transformations are just, they're absolutely notorious for their failure rate. And there's been a lot of literature over a lot of years just, and we can debate exactly what the failure rate is, but it is exceptionally high. Is this starting to change? Are you seeing organizations get better at this? And, you know, maybe more broadly, why, why are they failing to begin with?

• 37:32Speaker 00

  I would actually say, and not to be too difficult about this, Jeff, I actually think the failure rate has increased. And, and, and it's increased for a couple of reasons. One is the velocity with which transformations now need to deliver are much, much greater. You know, I, I'm a 35-year consultant. I was doing BPR at Accenture back in the early 90s, when that was all the rage and so had a front row seat to transformation, albeit in a very different age, when you think of the velocity and volatility of change. The velocity of change makes it really difficult. The second is the volatility of the external environment. You know, the world's always

• 38:17Speaker 00

  been a complicated place. We are in probably the most complex period of human history, which, which actually deserves, you know, some recognition with, it's not just the speed of AI, but it's the, the, the global conflicts around us. It's the climate crisis. It's the demographic crisis in certain parts of the world. You know, there, these, all of these crises, if you will, act as multipliers on, on each other as, as we know. And so the velocity and volatility of change have accelerated, which makes the risks of transformation

• 38:56Speaker 00

  much greater. But I think even more than that is seeing so many organizations continue to perpetuate the same mindset, skillset and toolset to driving transformation. You know, that to me adds yet another obstacle to the success rate of digital transformations.

• 39:17Speaker 01

  It's a bit bleak. I absolutely believe you. But it's a, you know, I think, I think a lot of leaders feel this very deeply and very viscerally, right?

• 39:27Speaker 00

  Yes.

• 39:28Speaker 01

  You're verbalizing something that I think a lot of listeners will say, yes, that does describe how I feel. And, and yet, for better or for worse, we can't just say, well, then no transformation, then me, then for me, then, right? I'm just going to sit this one out, right?

• 39:43Speaker 00

  Yep.

• 39:44Speaker 01

  Because I think the reality of, of, of this environment is transformation is probably more important than ever, even if it's harder than ever.

• 39:52Speaker 00

  Precisely. Absolutely.

• 39:54Speaker 01

  So how do we make sure that we get it right? If we're going to start, and you, you talked about, you know, outlining the broader journey, but if you're really committed to this type of transformation, how do you make sure that you get it right? And what do you have to do to make sure you're not another one of these failure stories?

• 40:10Speaker 00

  Yep. So I think there are probably three things that organizations that I've had the privilege of working with, you know, at this time, doing it right. One is just absolutely pivoting from the mindset that transformation is an event, to transformation actually being the start of a journey of perpetual reinvention. We are going to need to, and it's not just continuous improvement, it's actual reinvention. How do I ensure that as we transform here, we get that big gain in, in, in productivity and profitability, that I am creating the

• 40:49Speaker 00

  space for radical reinvention of work on a going forward basis? What that means is a couple of things. Collapsing the run transform cycle. So mentally, you know, practically, that line leaders, managers and employees fully understand that in the flow of work, we need to actively be looking for opportunities to reinvent radically and quickly. It's one of the reasons why my fourth book, Work Without Jobs, was focused on a new work operating system that is geared to sort of enable organizations to actually make that perpetual

• 41:29Speaker 00

  reinvention part of their core operating processes. The other key requirement, I think, is that we explicitly account for and build in space for learning and space for wellbeing in the flow of work. So, you know, practically what that means from a number of organizations I work with is not redesigning every job to 100% of every waking moment, that we're going to explicitly set aside time for learning, upskilling, reskilling, time for wellbeing in the flow of work, because the sheer intensity of the, that period that we're in requires

• 42:09Speaker 00

  the opportunity for a reset, because as we all know, the, the, the burnout rates have shot through the roof in most organizations. The level of disengagement have shot, shot through the roof, you know, in many organizations. And so actually building in space for learning and wellbeing in the flow of work, I think is, is essential.

• 42:34Speaker 01

  I subscribe to that belief as well. Now, I can hear already leaders saying, so we need to move faster than ever, and the solution you're proposing is for us to slow down, right? You, you, you can frame it somewhat cynically as that.

• 42:51Speaker 00

  Yes.

• 42:51Speaker 01

  How would you respond to that criticism?

• 42:55Speaker 00

  I would say the, yes. I would say it's going fast and going slow at the same time. I think what you need is for people to have that mindset, skillset and toolset to continuously challenging and reinventing the work, but actually having the space to think about it, the space to plan for it, the space to actually be, to have the energy, the energy to actually go through that continuous reinvention and challenging. The good news, I think, Jeff, is that, as I said, you know, early on, that these AI-powered transformations don't yield 3% or 4%, that we need to keep generating every single year. They get you

• 43:39Speaker 00

  a sizable dividend. They get you 40% to 50% capacity release. So they get you that big bump that allows you then to, that maybe allows you, maybe challenges you with the hard question of, how do I share the dividend from that bump? And I, as I said to one of my clients, you know, we freed up 50% of your labor capacity. You've got three non-mutually exclusive choices. You could take all of it as margin. You could take it as an opportunity to reset what is a pretty dire work environment with a 40% turnover rate by designing in space for learning and wellbeing in the flow of work. So people actually want to stay

• 44:23Speaker 00

  and they actually want to keep reinventing the work going forward. And they actually have the resources to keep reinventing. And/or we could redeploy some of the gains so that we are improving what is almost an equally dire customer experience, so that we're retaining our best customers, we're deepening our share of wallet. And the CEO, to his credit, said, I think I'll have a little bit of all three, please. And that's actually what they did, you know, freeing up their more senior people to improve the customer onboarding experience and work with the customers on deepening their relationships. Freeing up some of the analytical folks from doing data entry with a new agentic AI platform with computer vision

• 45:08Speaker 00

  to actually now do the analysis. And then getting their leaders, managers and employees the space to keep challenging the existing environment. 5% of time every week was a specific stand-up to say, great week, what did we learn? What are the opportunities we're seeing that we need to start putting the building blocks in place to retool, whether it's a week from now, three months from now, a year from now, so that we aren't just staying static. And we're not just looking for continuous improvement, but we're looking for exponential improvement.

• 45:44Speaker 01

  And when we talk about exponential improvement, it really feels like AI is the game changer here that just unlocks these opportunities that haven't been available to us historically. Now, the challenge with that is, you know, the AI is a new technology. It's something that's not inherently understood by everybody in the organization. And, you know, in my view, at least, it necessitates bringing IT or the enterprise technology team into the conversation in some way. When we think about reskilling, when we think about how people are being deployed or org design, you think of that traditionally more of sort of, I guess, an HR function. And these two functions, IT and HR, you don't typically have them doing a lot of,

• 46:29Speaker 01

  at least historically, interactions together. I feel like they live in very different models of the world, if I can call it that. So for this view of transformation, if you're actually going to end up in a place where you're designing to free up 50% of labor capacity or have 40% better margins, you know, order of magnitude, in your words, exponential changes. Who has to come to the table here? And how do you structure that in a way where people are, you know, doing this collaboratively, you know, rowing in the same direction versus, you know, people just showing up and not actually knowing what role to play?

• 47:09Speaker 00

  Yeah, absolutely. And I would add, you know, I think this is a three-part partnership, if you will, Jeff, between the operation, so the folks actually doing the work, HR, who are the stewards, as you say, of skills and perhaps even the architecture of work, and then IT, who are the stewards of the technology, its deployment, et cetera. You know, we've certainly seen in a number of instances, companies like Moderna, who have put IT and HR together under Tracy Franklin. I think there is a strong case for that integrated resource management view of technology, of machine capability and human capability next to each other.

• 47:51Speaker 00

  We've seen other instances of where HR has expanded its remit to being focused on the AI enablement of the organization. So the utilization of AI by leaders, managers and employees, et cetera, the redesign of work. So I do, I do think, though, that the three parts of the operation, HR and IT, are integral to the success of this journey, though.

• 48:16Speaker 01

  You mentioned the Moderna example, and that's one I've heard a couple of times before, and it's fascinating to me. Now, just coming back to something we were talking about earlier, which is that this is not, the future of work is not necessarily as simple as, you know, add more AI or don't add more AI. It's not just like a, you know, kind of a two-dimensional spectrum. But it's a whole range of options in terms of how work actually gets done. I'm curious if you've seen any creative, you know, work transformations or any configurations that organizations have moved to that aren't just, yes, we added more AI to it. That's a little bit less black and white than that.

• 48:56Speaker 00

  Yeah, so I wrote a piece, the Sloan Management Review last year, of a large financial services organization I worked with, where they had, you know, introduced a new agentic platform where there's, I sort of alluded to the example earlier, you know, a combination of agents with process automation, computer vision for data ingestion, et cetera, and then struggled to realize the full business case for the technology platform. And what was missing was, so IT had deployed the technology platform with the business. What was missing was HR's role in helping the line leaders and IT redesign the work

• 49:39Speaker 00

  for where the technology would substitute some of the human labor, where the technology would augment the experience of people there, and where the technology would radically transform the customer experience or the work of the employees. And when they did that, that's where, not only did they realize the business case in terms of the ROI that was expected, they actually went three times beyond that. Because what it allowed them to do was to recognize that not only are we optimizing for the humans versus machines, we now have an opportunity to organize the humans in different ways. We can shift some of the work from a high-cost location like the United States to a global capability center in India.

• 50:23Speaker 00

  Because as the work is augmented by the technology, we have capacity in that capability center to take on that augmented work. And we can now free up the more senior-level people who used to be doing the work in the US to deal with the onboarding of customers. And I think that's where, when those three entities come together, you get all parts of the triangle being complete. Because otherwise, what you've got is often, you know, literally and metaphorically, a big gaping hole in one end that either gets in the way of realizing the base-level business case. And secondly, lets you, makes you miss out on the exponential opportunities that come

• 51:07Speaker 00

  when all three perspectives are brought together.

• 51:12Speaker 01

  Yeah, I'm just, I'm just digesting all of that because it makes, it makes complete sense to me. And yet, it's, it's still a tall order. I can see how they become self-reinforcing. But again, it requires the right level of planning and, and, you know, getting everything right from the beginning to the end to do that. So it's, yeah, well, and to just, you know, I'll say, I'll say the quiet part out loud, but I have to imagine, you haven't actually said this, but it seems like there is an important role for a lot of companies at having some sort of outside support with experts to do this versus trying to do it all internally. I mean, I don't know, do you buy that? Can you, can you read a, can you read a few articles or a book on that and do it yourself?

• 51:55Speaker 01

  Or do most organizations traditionally look for more outside support?

• 51:59Speaker 00

  I think an external stimulus is always helpful, whether that's an academic, whether that's someone who's done that elsewhere, like another executive or a consulting firm or something else. I, because to me, the three parts of this journey, Jeff, are you need to shift the mindset, the skill set and the tool set. The tool set's the easy bit. There's plenty of tech vendors who will sort of sell you their product in a heartbeat, right? But that's the easy bit. The shifting of the mindset and the skill set is what is much, much harder. And, and the mindset often need, always, I would say, needs an external stimulus to see the art of the possible.

• 52:41Speaker 00

  Because we're all constrained by our experiences and our imagination will only stretch so far. And I personally found it really, you know, I think we all benefit from engaging with people who have a different frame, different industry, et cetera, because it forces us to stretch, you know, the paradigms that have traditionally limited us.

• 53:04Speaker 01

  It was reminding me of a quote from another guest I had on the show who said, you know, "You can't read the label from inside the jar." And that-

• 53:13Speaker 00

  That's really well said.

• 53:14Speaker 01

  I thought that was very illustrative of the, of the role of getting outside support. As we start to wind down the conversation, Rob, and I wanted to ask, you know, we've covered a lot of ground here, lots of ideas that'll, you know, keep the wheels spinning for people. What's your best advice for business and for technology leaders who say, "Yes, all of this makes sense to me. I want to be, you know, building the organization of the future." What's kind of your capstone advice for them?

• 53:41Speaker 00

  I would like to leave them with, you know, with, with a quote that has shaped a lot of my just personal beliefs. It's, it's from Alvin Toffler's book, Future Shock, where in it he said, you know, "The illiterate of the 21st century will not be those who can't read and write. It'll be those who can't learn, unlearn and relearn." And I think we are in that perfect storm of where the continuous challenging of our frames of reference, our beliefs, and then sometimes reminding ourselves of things that we've forgotten that have helped shape how we've gotten here that continue to be relevant.

• 54:23Speaker 01

  I love that. It's so encapsulating of what we've been talking about and I think really just drives home the importance of the skills of the future. Rob, and I wanted to say such a big thank you for joining today. This has been a really interesting and insightful conversation.

• 54:36Speaker 00

  My pleasure, Jeff. I really enjoyed it.

• 54:40Speaker 01

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