#28 How AI Augmented Leaders lead and what we can learn from them

Speaker A: Foreign.

Speaker B: Welcome to my podcast, Future of Work, Future Skills and AI. I'm Yasmin Weiss, professor of Artificial Intelligence and the Future of Work. This is no ordinary podcast I created using the AI tool NotebookLM. Um, the characters you hear are two AI voices. However, the content comes from me, Yasmine. Each week, you will learn how to work better and smarter with AI.

Speaker A: So we usually think of artificial intelligence as this, uh, looming force that's just coming for our jobs. Right. But what if we've got it completely backward? Like, I want you to think of it more like an industrial vacuum for our administrative nightmares. It's actually just coming for our busy

Speaker C: work, which is such a massive relief to hear, honestly.

Speaker A: It really is. And that's the core premise we're diving into today. We have this incredible research by Professor Dr. Yasmin Weiss. She's a massive authority in this space.

Speaker C: Oh, absolutely. A Future of Work strategist, a leading professor of AI at work. Her insights are just. They reveal this profound shift happening right now.

Speaker A: Yeah. She's showing how AI is stepping in to basically rescue management from total burnout, and in the process, making leadership fundamentally human again, which is our mission for this deep dive.

Speaker C: It's a vital read, especially in our current corporate climate. I mean, Professor Weiss isn't just theorizing from some ivory tower. She's looking at the hard data of what's happening to leaders on the ground, you know?

Speaker A: Yeah, totally. So if you're out there listening and you're just drowning in spreadsheets right now, or maybe you're actively dodging a promotion because your boss looks completely miserable.

Speaker C: It's so common right now.

Speaker A: Oh, it's everywhere. This research is gonna completely reframe your daily grind. It actually shows a way out of the current mess.

Speaker C: Yeah, and to understand the way out, we really have to look at how bad the mess actually is.

Speaker A: Right. Let's start with this baseline statistic she shares. It honestly stopped me in my tracks. In Germany. Among employees who currently do not have a leadership role, only 14% actually want one.

Speaker C: Wow. I mean, the broader implication of that number is just staggering. When you consider how businesses actually function,

Speaker A: it's basically a crisis.

Speaker C: It is. A thriving economy relies entirely on a robust talent pipeline. Organizations need this large, eager pool of ambitious people stepping up so they can select the most capable ones to lead.

Speaker A: And if only 14% even want the job, that pipeline is practically dry.

Speaker C: Exactly. You end up promoting whoever is left standing, not whoever is actually best suited for the role.

Speaker A: It's a massive red flag and she talks to her next gen university students about this, right, and they're actively rejecting the management path.

Speaker C: Oh, completely. They look at what it takes to be a boss today and just say, uh, no thanks.

Speaker A: Yeah, they see it as too demanding, exhausting, and just a guaranteed way to ruin any chance of a work life balance. And frankly, they just think it's uncool.

Speaker C: Which makes sense. There are barely any role models out there showing how leadership can actually be an attractive, sustainable lifestyle.

Speaker A: Which brings us to this phenomenon she identifies as quiet cracking.

Speaker C: Right, so we've all heard of quiet quitting, you know, stepping back from duties. But quiet cracking is much darker. It describes leaders who are slowly, invisibly breaking under the weight of chronic stress, severe sleep deprivation, and just a, uh, complete lack of balance.

Speaker A: You can picture it instantly too. I mean, the manager who sends emails at 2 in the morning, chugs coffee all day, looks 10 years older than they actually are.

Speaker C: Yep, that's the quiet cracking. Yeah, because they're trying to do two massive, totally contradictory things at once.

Speaker A: Right. They have to manage the day to day present emergencies while simultaneously trying to design and strategize for the future.

Speaker C: It's like trying to rebuild an airplane engine while you're actively flying the plane.

Speaker A: Oh, that's a perfect way to put it. And if leadership is currently breaking the people doing it, how do we fix the system before companies just, you know, collapse from a lack of direction?

Speaker C: Because filling vital positions in politics and the economy with unsuitable, exhausted people is a guaranteed way to completely mess up the future. Something has to give.

Speaker A: Okay, but let me push back on the proposed solution here for a second.

Speaker C: Sure, go for it.

Speaker A: If these leaders are already suffering from quiet cracking, if they're maxed out, exhausted, barely holding it together, how does introducing a massive, complicated technological shift like AI actually help?

Speaker C: I get that it sounds like giving someone who's drowning a heavier weight.

Speaker A: Exactly. Now they have to learn how to write prompts, understand new software platforms, change their whole workflow. If I'm already working 60 hours a week, telling me to learn a complex new AI system feels like tossing me an anchor, not a lifeline.

Speaker C: And a lot of people feel exactly that way. It seems incredibly counterintuitive to add a learning curve to a burnout cris. But Professor Weiss argues that AI is not just another, uh, clunky piece of enterprise software you have to wrestle with. It's fundamentally an enabler for more pleasant and effective leadership. Because you can interact with it, uh, using natural language, it becomes the tool that actually alleviates the very pressure it seems to create.

Speaker A: So the idea is that it actively shrinks the to do list rather than adding another software integration task to it.

Speaker C: Yes. And Professor Weiss actually tested this paradox on herself.

Speaker A: We.

Speaker C: Which is fascinating.

Speaker A: Right? She didn't just write about it.

Speaker C: No. For about nine months, she has been operating with her own personal agent workforce, constantly expanding its capabilities.

Speaker A: Wow.

Speaker C: Yeah. And she divides this concept of the AI augmented leader into two distinct dimensions to explain how it works.

Speaker A: Okay, so if the goal is shrinking the to do list, Vice found that AI attacks this from two angles, like boosting your strategic vision and handling the grueling administrative grunt work.

Speaker C: Spot on. So the first dimension is increasing effectiveness. That means actually improving leadership performance, making better decisions, maintaining a clearer overview of what is happening both inside and outside the company.

Speaker A: So the AI just gives you a wider, A, uh, sharper lens to see the whole board.

Speaker C: Right. And then the second dimension is providing relief. This is about improving job satisfaction and reallocating time by having AI handle the annoying time consuming administrative tasks.

Speaker A: So it literally saves time and nerves.

Speaker C: Exactly. Skill augmentation on one side to make you sharper and task automation on the other to make you less bogged down.

Speaker A: I love that. And she gives a real world example of this from the absolute top tier of the corporate world, Right? Microsoft CEO Satya Nadella.

Speaker C: Yes. And she details his actual workflow as an AI augmented CEO. His setup is incredibly revealing about where management is heading at the highest levels.

Speaker A: Okay, lay it on us. How does he work?

Speaker C: According to her research, Nadella opens his mobile agent platform before he even opens his email inbox in the morning.

Speaker A: Wait, let's pause there for a second. When she says mobile agent platform or agent workforce, what does that actually mean mechanically? Because we shouldn't confuse this with just, you know, pulling up a standard chatbot on a phone.

Speaker C: Oh, totally. An agent isn't just a chat box you type questions into. When she talks about an agent workforce, she means autonomous software programs running in the background.

Speaker A: Like digital interns?

Speaker C: Exactly like digital interns. They have specific permissions to read your emails, check internal company databases, scan the Internet for market news, and generate analytical reports while you sleep.

Speaker A: That is wild.

Speaker C: So Nadelli uses his mobile agent platform to check the results his AI agents have, uh, prepared for him overnight. He relies heavily on what he calls data driven support.

Speaker A: What does that look like?

Speaker C: In practice, he has research and analyst agents that help him process the massive reports and presentations directed at him. This directly supports his opinion forming and decision making processes before his day. Even really begins.

Speaker A: And beyond those morning reports, she notes, uh, he uses copilot and cowork. Right?

Speaker C: Yeah. Which are AI agents integrated directly into his daily tools. He uses them as a sort of personal data analyst.

Speaker A: A personal data analyst that's just always

Speaker C: there, permanently by his side, continuously evaluating company wide data and linking it with external analyses.

Speaker A: It's just wild to think about. It's really like waking up to a world class sous chef.

Speaker C: Oh, I like that analogy.

Speaker A: Right, like while you were sleeping, the sous chef was in the kitchen chopping all the vegetables, reducing the sauces, prepping the garnishes. So when you walk in, you don't have to do any of the tedious prep work.

Speaker C: You just get to do the actual creative cooking.

Speaker A: Exactly. You just get to be the head chef.

Speaker C: The AI does the prep, the human makes the meal. But, uh, I guess the question is, what does this mean for a typical manager who isn't running Microsoft?

Speaker A: Yeah, what does that prep work actually look like for the rest of us?

Speaker C: Well, Professor Weiss lays that out by identifying seven core management tasks that possess a high potential for automation. Right now. Yeah, uh, and she doesn't just list them. She shows how the workflow fundamentally changes.

Speaker B: Okay.

Speaker A: She groups these into heavy logistical lifts. Let's look at the first big bucket. Gathering information and building situation reports.

Speaker C: Right. I mean, think about the sheer volume of time leaders spend just hunting down information.

Speaker A: Oh, it's endless. You have to check market data, internal key performance indicators, project statuses, customer feedback.

Speaker C: Yeah, and instead of manually digging through spreadsheets or waiting for a subordinate to build a PowerPoint, AI agents can continuously collect, condense and build those situation reports automatically.

Speaker A: Which naturally spills into the second task, which is meeting management. And this one is a notorious time sync.

Speaker C: Huge time sink. An AI can handle agenda proposals and pre briefings. Then during the meeting, it writes the protocols, distributes tasks, manages follow ups and documents decisions.

Speaker A: So you literally never have to write meeting minutes or chase down someone for a status update again.

Speaker C: Never again. And then task three is reporting and performance monitoring status reports, KPI dashboards, variance analyses, forecasts, early warning signals, all generated or prepped by AI agents.

Speaker A: So the AI is constantly watching the dashboard so the human doesn't have to stare at it all day.

Speaker C: Exactly. Then you move into the truly complex logistical tasks like task four, resource and capacity planning.

Speaker A: This sounds like where AI would really excel.

Speaker C: Oh, it does. Agents can analyze team availabilities, match specific skills to specific project needs, track deadlines, monitor priorities, and spot bottlenecks to suggest how work should be distributed.

Speaker A: Wow. So instead of a manager manually checking 15 different calendars and cross referencing them against a skills matrix on a spreadsheet,

Speaker C: the AI agent just does it in seconds.

Speaker A: That is incredible. And task five is standardized communication, right?

Speaker C: Yeah, we're talking about project updates, reminders, summaries, stakeholder briefings, answering frequently asked questions.

Speaker A: So those routine emails that eat up half your day are just drafted and managed by the agent?

Speaker C: Yeah. Now, the sixth task is crucial to understand because it touches on higher level strategy. It's decision support.

Speaker A: Okay, how does that work without crossing a line?

Speaker C: The AI can look at a problem and provide options, map out scenarios, identify risks, offer counterarguments, and pull benchmarks. It prepares the decision.

Speaker A: But, and Professor Weisz is very clear on this boundary, the AI does not take the final responsibility.

Speaker C: Exactly. The human still has to make the call.

Speaker A: Important distinction. And finally, task seven. Process optimization.

Speaker C: Right. AI agents can analyze how work is being done, spot inefficient workflows, identify where more automation is possible, and help restructure processes.

Speaker A: And she points out something vital here. I think this isn't just about plugging AI into your old clunky processes.

Speaker C: No, you aren't just speeding up a bad system. It is a fundamental restructuring of work itself. It's designing a totally new interplay between humans, agents and systems.

Speaker A: Because if a task is predictable, if you can measure it, standardize it, repeat it, and AI can automate it.

Speaker C: And therefore it has a massive potential to provide relief for a stressed manager.

Speaker A: Okay, but I really have to stop and look at this division of labor for a second.

Speaker C: Uh oh, here comes the pushback.

Speaker A: Well, yeah, think about it. The AI is gathering all the information. It's writing the meeting agendas, it's doing the capacity planning, tracking the bottlenecks, drafting the emails, mapping out the decision scenarios.

Speaker C: Right.

Speaker A: If the algorithm is practically running the logistical side of the team, what is actually left for the human manager to do? Aren't we just handing the steering wheel over to a machine? Like, are managers becoming obsolete?

Speaker C: I get why you'd ask that. It feels like a loss of control on the surface, but Professor Weiss argues the exact opposite is true.

Speaker A: How so?

Speaker C: By stripping away the administrative burden, the pure management of processes, you finally leave room for actual leadership of people.

Speaker A: Okay, management versus leadership.

Speaker C: Exactly. If a task is predictable and repeatable, the machine does it. But leading human beings is incredibly unpredictable.

Speaker A: That is very true.

Speaker C: She outlines 10 specific traits of excellent people leaders that are incredibly difficult, if not impossible, for AI to replicate in the Same quality.

Speaker A: Let's explore those human traits, because this really answers the what's left for us question. She groups these into areas that require deep emotional intelligence, ethical grounding, and interpersonal connection.

Speaker C: Yeah, let's start with the first one. Building trust. An algorithm simply cannot build genuine mutual trust with a human being.

Speaker A: Right. Trust requires vulnerability, shared experience, mutual risk. Things code simply does not possess.

Speaker C: Exactly. What was the next one that stood out to you?

Speaker A: Oh, I found reading the room fascinating. I mean, an AI can generate a flawless word for word transcript of a meeting. It can summarize the action items perfectly. But only a human leader can look around that table and notice that a key team member is sitting completely silent or arms crossed, just holding back a ton of frustration.

Speaker C: Yes, the AI misses the physical tension. The human feels it intuitively.

Speaker A: The human intuition to grasp the unspoken is just irreplaceable.

Speaker C: And that directly connects to the next trait, which is the ability to conduct hard, difficult conversations with genuine empathy.

Speaker A: Oh, definitely. You need real tact and intuition to navigate complex interpersonal clashes. Or deliver bits bad news.

Speaker C: You certainly don't want a chatbot firing someone. Or managing an employee's personal crisis.

Speaker A: Yeah, which ties into solving conflicts. When two team members are clashing over a project, an AI might look at the data and say who is technically

Speaker C: right, but it can't navigate the bruised egos and actually rebuild the working relationship.

Speaker A: Exactly.

Speaker C: Professor Weiss also highlights serving as a role model. You know, creating identification and living the standards. You said AI cannot be a role model for human behavior.

Speaker A: It also can't create a meaningful vision. I mean, it can draft a corporate strategy document, sure, but a vision that people understand in their heads and actually buy into with their hearts, that requires a human touch.

Speaker C: The same goes for shaping values. Anchoring central values in the corporate culture means consistently acting on them and living them out.

Speaker A: Because an AI doesn't have a culture, it just has training data.

Speaker C: Such a good point.

Speaker A: Yeah.

Speaker C: And that leads to building loyalty. Professor Weiss phrases this brilliantly. She says it is about leading people in a way that turns them into fans of the company, rather than just paid mercenaries.

Speaker A: I love that. Fans, not mercenaries.

Speaker C: Right. An AI can process payroll for a mercenary, but it cannot inspire a fan. People don't leave companies, they leave bad managers. And conversely, a great manager creates lasting loyalty.

Speaker A: Then there is taking responsibility, like, real ethical responsibility for the strategy, the process, and the final outcome.

Speaker C: Yeah, the AI might suggest a strategy that increases profit by 10%, but, uh, requires laying off 50 people.

Speaker A: The AI doesn't feel the moral Weight of that action, the human has to balance the ethics against the business goal and actually own the consequences.

Speaker C: And finally, the tenth trait is showing kindness, offering warmth and appreciation to other human beings precisely when they need it most.

Speaker A: So if we pull all of this together, the ultimate art of AI augmented leadership, as Professor Rice sees it, is this perfect division of labor.

Speaker C: Yes, you ruthlessly delegate all the automatable, standardizable tasks to your AI agents, and

Speaker A: you use all that newly freed up time and mental energy to double down on those deeply human skills.

Speaker C: It represents a complete paradigm shift. For decades, we've conflated management, which is organizing resources, spreadsheets, tasks, with leadership, which is inspiring, guiding and supporting people.

Speaker A: Because managers were so buried in administrative management, they had absolutely no time for actual leadership.

Speaker C: And AI, uh is finally splitting the two apart.

Speaker A: Looking at the big picture, Professor Weisz makes three massive predictions about where the future of work is heading once this shift truly takes hold. Let's break those down.

Speaker C: Sure. So first, she predicts leadership will become significantly more attractive again by stripping away the busy work. Exactly. Leaders can actually focus on the true purpose of their roles. It becomes a job about connecting with people and driving a vision, not just managing spreadsheets and hunting down bottlenecks, which

Speaker A: hopefully solves that 14% crisis we talked about at the beginning. Like people might actually want to step up and lead again if the job description doesn't sound like a punishment.

Speaker C: 100%. Uh, her second prediction is that leadership will become much more compatible with private life.

Speaker A: That would be amazing.

Speaker C: By utilizing an AI agent workforce to handle the heavy administrative lifting, leaders will experience a massive relief in their time constraints. The quiet cracking stops because the workload is fundamentally redistributed.

Speaker A: You aren't working until midnight just to catch up on emails and capacity planning.

Speaker C: Right. And her third prediction is that leadership will become fundamentally more human because you

Speaker A: aren't spending eight hours a day acting like a human calculator.

Speaker C: Exactly. You actually have the time and the emotional bandwidth for interpersonal connection and showing real appreciation to your team.

Speaker A: So where does she see this going in the long term?

Speaker C: She predicts that by the year 2030, all top executives will be working as AI augmented leaders. But she stresses a crucial point here. The real journey isn't just about implementing the technology for efficiency's sake. It is about using the technology to win back the smart, warm hearted, purpose driven individuals who are currently opting out of management.

Speaker A: We all profit when those are the people steering our organizations.

Speaker C: Absolutely.

Speaker A: It's incredibly empowering when you look at it that way. And if you're listening to this right now, this isn't just theory for 2030. You can start exploring your own agent workforce today to take back your time.

Speaker C: You really can M But it does

Speaker A: leave us with a fascinating and maybe a little provocative thought to end on today. If AI eventually strips away all the cold calculating, analytical and administrative tasks of management and leaves behind only the requirements of empathy, vision, emotional intelligence and conflict resolution, yeah. Will the most successful high powered CEOs of the future look less like the traditional aggressive, hyper analytical business tycoons we're used to and more like therapists or philosophers?

Speaker C: Wow. That is a completely different image of a CEO.

Speaker A: We will leave you to mull that over. Thank you so much for joining us as we unpacked this incredible research. Don't forget to turn on that industrial vacuum and start clearing out your busy work.

Speaker B: If you enjoy the podcast, please subscribe, leave a review and recommend it to your friends, family and colleagues.