🇬🇧 Leading with AI – In Conversation with Katja Spörl (MD NewNow Group)

00:00:03: Typically, the time saves potential is around seventy to ninety percent for a process.

00:00:11: Wow!

00:00:12: Being able quickly adapt and iterate.

00:00:16: I think that should be changed or improved in many aspects of our work we see today.

00:00:26: Hello and welcome to Today's Light For Love Podcasts.

00:00:30: It's great you dear listeners are with us again today.

00:00:36: We're exploring that is moving faster than almost any other development in business ever has.

00:00:44: We are talking about artificial intelligence and there was a lot of excitement, I think also a lot uncertainty around it.

00:00:53: some leaders worry about technology others invest in pilots but struggle to create real business value.

00:01:01: And many ask themselves what does AI actually mean?

00:01:06: for my business and from my role as a leader.

00:01:10: And in order to discuss these questions, it's my huge pleasure.

00:01:14: I'm really delighted to welcome very special guests this morning someone i know and respect very much Dear Katja Spell.

00:01:24: Welcome To The Lightwolf Podcast.

00:01:26: Thank you Stefan.

00:01:27: It is a pleasure to be here!

00:01:30: And

00:01:33: I'm excited you're here today.

00:01:34: Katja is the managing director of The New Now Group, wonderful to have you hear and share your experience because Katja's working on AI related projects day in-day out.

00:01:48: So let us first explore a bit.

00:01:50: who are you?

00:01:51: Katja?

00:01:51: so people understand as person.

00:01:55: Do you still remember that you were much younger than me?

00:01:59: Do you still remember who u were as a teenager kathya?

00:02:03: yes i do remember myself as the teenager.

00:02:08: Back then at school I would consider my third myself inert not necessarily the cool kid but very much focus on my smaller circles and totally in a word for myself.

00:02:21: so probably not engaged in the most hype topics, being focused on the things that I have to do, which is school and a lot of sports actually.

00:02:32: So every day i think had something else.

00:02:34: so i was participating in volleyball, in tennis, in dancing, in badminton... And that basically was occupying all my afternoons after school.

00:02:47: So yeah, that was basically my teenage time.

00:02:50: Yeah it went past quite quickly and every time if I reflect back nowadays when we talk with my friends back at school they will talk about people in our classes.

00:02:59: i would say i can't actually remember those people existed because ive so focused on my own world.

00:03:07: sometimes if you're not in a smaller circle what's the person really there?

00:03:15: Yeah,

00:03:18: and did you have a favorite among your sports?

00:03:23: Actually I do.

00:03:24: Um i like badminton the most because it's fast.

00:03:28: It is good for You don't have so longer distances at some point.

00:03:33: I realize I'm not a Good...I am a lazy sport person to be honest.

00:03:39: So all my trainers would say Katja you're good-you have good skills You're very precise.

00:03:45: And so on is how you play things and strategic about where you want to play, but your just very lazy sometimes.

00:03:54: don't get up out of it.

00:03:56: run for that last point.

00:03:58: So at some point I realized i need to smaller the playing field For myself before a plane.

00:04:05: That's why I landed at Batman now which one that I still pursue because this Is someone that I like The most?

00:04:12: yeah because it fits my character apparently.

00:04:18: What an interesting view on reducing the scope of a field to just match your preferences.

00:04:23: and if I may introduce you professional side in your academic achievements, Katja, you studied in Zangalen You received your PhD from the European Business School You've seen Mary Lynch, you've seen Morgan Stanley from inside and you got an outstanding management experience at the Boston Consulting Group.

00:04:53: So it's evident that what maybe at times may have been a play in sports so not always wanting to go the extra mile was the exact opposite of your professional and academic career.

00:05:08: because to get all these achievements and degrees?

00:05:17: Yes, yes.

00:05:19: I think i'm a very goal-oriented person so whenever I set myself the goal then im gonna stick through it like for other sports although I have a preference of badminton but still did in ten years.

00:05:31: that's not my first preference.

00:05:39: Also nowadays and across all dimensions, I would say.

00:05:43: I always need a clear

00:05:44: goal.".

00:05:45: That gives me also in the things of complexity or uncertainty for myself from certainty to know where we want it go.

00:05:55: For that goal you obviously go through up-and-downs what it takes to get there.

00:06:04: Then about two and half years ago You became the managing director of a company that I co-founded with six others five years ago.

00:06:16: And it's amazing to work with you Katja, Managing Director Of The NUNA Group in Frankfurt and Vienna.

00:06:22: And you combine deep understanding data on one hand side With experience applying them into business.

00:06:33: UNI went I know client a year ago in Vienna and explored working together.

00:06:41: And it's obvious to me that you see day-in, end-day out where organizations are on their way to move beyond experimentation and use AI to take better decisions?

00:06:54: To create measurable value for customers before the shareholders.

00:06:59: so i'm curious too to listen when you share your experience.

00:07:03: Let's start with a couple of topics regarding artificial intelligence.

00:07:09: If you look at what you see in the world, Katja, if you look new Nau's client portfolio now and where projects stand – you have complete oversight as R&D….

00:07:24: Where do we see our biggest challenge for business clients?

00:07:29: I think

00:07:34: there are definitely several ones that different businesses, depending on their size and the industry probably face.

00:07:43: And those challenges actually have changed since two or three years ago versus now.

00:07:51: When I reflect back to a few years ago many of them were still at the start.

00:07:58: they didn't know where it started.

00:08:02: Some of them might have not even got on the train in terms how important AI is and can be.

00:08:11: And some may say this is new technology that's not reliable, but will not be important for future.

00:08:23: That probably today I hear very rarely... So attention and focus on a management level is the first step as a challenge, I think for implementation obviously at this start.

00:08:39: The second one is the mindset.

00:08:41: so we're in Germany And as made of Germany it's very... It's a brand that basically based on precision of German engineering.

00:08:54: It's a mindset in those companies that is basically completely different to how AI works, because AI is all about approximation.

00:09:04: It's about iteration.

00:09:06: it's about being wrong at the beginning and getting better and better In as fast way possible And That Is In Contrary To What The Mindset Of Those Organizations.

00:09:22: So When They Start Off implementing AI, the businesses typically do better when they have people that obviously already understand that point and know how to start dealing with AI.

00:09:37: So when they come with a right mindset at the beginning implementation works a little bit better because otherwise it's you need a lot of culture change in order for AI really stick.

00:09:54: What is actually less of a problem, it's the technology because technology is getting better and better throughout time.

00:10:02: So quality output of AI will develop by itself with LLMs being smarter or more intelligent.

00:10:15: The things that typically are challenged in implementation everything around them so processes The data that you feed into AI and the people.

00:10:25: basically, they should use it.

00:10:28: And that's all above that mindset topic because its a mind set decides how do your processes are willing to change when you adopt new technology?

00:10:39: knowing probably is quite big of a change knowing it will lead to resistance and few responses within organization.

00:10:52: Is that something you are open to do, if we're willing as a change?

00:10:58: Or is it too much of a change for the organization so obviously also decides on how actually want go about implementation.

00:11:06: Then second off course... Shall I continue?

00:11:12: Yes please!

00:11:14: Second off course data topic i think I mean, it's quite a leverage actually in the media as well.

00:11:28: That data obviously is something that AI has built on meaning good data leads to better results.

00:11:38: and none of the organizations did their data strategy ten-twenty years ago with the mind or purpose for feeding some day into an AI.

00:11:50: so... The data unfortunately is not in a place where it's suitable for AI.

00:11:56: And that probably coming together with the data topics, structural topics and process topic of course.

00:12:03: last leadership mindset are things that work decides whether implementation works better or less.

00:12:09: Yeah very helpful.

00:12:13: so based on your perception technology no longer a barrier to tech.

00:12:22: The barriers you see are much more in mindset and data strategy, maybe data readiness.

00:12:34: Now on that first one regarding mindset.

00:12:38: what you described an IM German so I can acknowledge this somewhat stereotypical German mindset to be present at least of looking for precision and in fact, looking for a precision all along from start to finish is in contrast to the mindset you need.

00:13:04: To make AI work because it's experimentation at the beginning its oftentimes failing A lot of times early on And then only an iteration finding the right spaces in the right way.

00:13:22: So it's a completely different mindset.

00:13:25: now looking at though, that many projects you've managed led or supervised in new now Katja have you had cases of successfully helping C level leaders who are often decision makers change their mindsets from a Not helpful one to a helpful one regarding AI?

00:13:57: Yes, I think it takes time.

00:13:59: Yeah And often times takes explanation To open up what how AI is composed so the basic components of AI and how AI works?

00:14:11: The One case where they see that process off things getting better throughout Weeks as we are iteration cycles really seeing that it's working is something that obviously leads to changes in how people think and then.

00:14:31: It also requires their trusted people inside there own organization, too be there.

00:14:37: so the person responsible for eyes oftentimes very critical in guiding top management and the organization, and the conversation around AI inside the organization to really lead the transformation of change.

00:14:53: And continuously ready... ...to inform on how AI is developing because at the end-of-the day, AI is a technology that's new.

00:15:05: We're adopting AI.

00:15:07: Everyone is adopting AI while the technology is still developing meaning at this point in time actually what you want to have is actually to encourage exchange and really being able.

00:15:22: And take the time to talk about it with everybody learned because through technology improvement obviously there are other risks, challenges that evolve.

00:15:33: i think as I said two years ago was more about can the technology deliver?

00:15:40: Because quality of it still not as of today usable, easy and good.

00:15:51: What then changed is obviously the speed technological improvement that basically erased that worry or concern.

00:16:03: when things get better with technology and LLM are implemented into AI systems It obviously triggers other concerns in terms of security, roles and permissions inside organizations.

00:16:22: How processes need to change?

00:16:25: And how you actually start to rethink about your organizational structure or make decisions is something that's evolving.

00:16:41: try it out and to learn from it.

00:16:44: And that's probably something that is not very comfortable for many organizations, I have been successful in the things they do but now its basically an open playing field where everybody starts fresh and fast learners will probably succeed yeah?

00:17:01: Great!

00:17:02: If you look across our project-inclined portfolio Katja distinguish and segment those projects that are moving slowly, laggers where things move slowly.

00:17:21: And there was others.

00:17:23: were projects already pretty advanced and starting to show tangible value.

00:17:30: maybe two questions what symptoms do you see in terms of results or the lack off results?

00:17:39: In this low ones?

00:17:42: What first evidence of real business value can you see in the advanced ones?

00:17:48: In terms of symptoms, I would say an unclearity on goals that AI should bring.

00:18:00: Basically at the beginning and setup for things, set with a clear goal.

00:18:08: The experiment was there, but there is either clarity of ownership who would own the goal missing or an unclearity on the goals itself.

00:18:22: and ones that have our eye goal want to also process how they want achieve it so how AI actually developed implemented adopters scale.

00:18:37: Those typically are the ones that can move faster because they have thought about it in terms of the timeline how They want to go about.

00:18:45: and though The reason for that is actually at some point you ask About how much?

00:18:51: How much?

00:18:52: I'd some point a budget question were probably Would would would impact this beat off implementation Because of regularly regular planning cycles inside organizations.

00:19:08: And if you don't have that our eye number at the start, it is already very clear to all stakeholders.

00:19:15: At some point somebody will ask where are we actually?

00:19:19: how can you verify?

00:19:20: The value that your ready created and what I'll be getting out of this?

00:19:24: and then dad that can trigger some questions and then It ultimately than can hinder or slow down the implementation just because of that un-clarity, how much are we willing to invest for what outcome and where on our journey.

00:19:44: The ones who have done this typically know exactly what value they want to get out of

00:19:49: it.".

00:19:52: So you highlight the importance of having a clear goal up front?

00:19:58: And ideally your goal is ROI related so that you define up front what return on your investment, from artificial intelligence.

00:20:10: It sounds so simple but it is powerful and at times forgotten to just set the goal before we start right?

00:20:21: Maybe because people want to experiment with AI.

00:20:25: why don't sensitize me again for the importance of having a clear goal early on so that you have clarity what your trying to achieve?

00:20:38: now another question Katja anonymous but real.

00:20:43: You and I about a year ago met in now client off new now for the first time i remember, And I remember asking you, hey should we really go when there are so many do they really know what they want?

00:21:08: You encouraged me to say Stefan yes.

00:21:10: We should go and said okay fine i'll take another flight that come into the place... ...and presented together again anonymous but.. ..I remember where the company was because it had started working on AI.

00:21:24: They have start creating solutions database but they had not yet seen significant or any value coming out of it, because at least partially the solutions they designed were never used by our employees.

00:21:44: Now if you reflect on progress this client made since how far have they come now?

00:21:52: in their first year What do you see has changed in the way they work before working with us?

00:22:02: Yeah, it's a very interesting example because as you said Before we actually joined.

00:22:09: They already started was The topic of AI year ago and basically In the end all that year off investment or implementation tools is some cost now.

00:22:23: And when we started off the first thing we did was.

00:22:28: Setting up the structure setting up an ambition knowing on a bit level profitability so company wide profitably level to say what is it?

00:22:41: Improvement that we want to achieve with AI in three five and seven years?

00:22:46: of course, five to seven years as unlikely will be correct but I think you have to start with the ambition level in order to drill it down.

00:22:56: To this singular use cases that you want to implement and was a portfolio of use cases, and to say okay are we actually getting there?

00:23:04: Do We need more?

00:23:05: what is actually needed?

00:23:07: because then you become implementation becomes much more concrete And you can see whether the plan and the rollout is actually feeding into that overall target.

00:23:18: Basically, what we did was setting up all of our structure processes in place with ambition, portfolio use cases... The structure how to get from a use case through a whole roll-up tracking down HRI of the use cases linking it back to financial numbers for companies.

00:23:38: And then actually in parallel, starting with five quick-wind use cases that are already now some in use.

00:23:48: Some pass due to data issues... That needs to be systematically built up before it can be used again and some basically scaling out across different regions.

00:24:03: So and they are now from the first year with a single digit of use case implementation.

00:24:10: They're also building up their AI capabilities internally because off that structure when you have an ambition, You know how much do want to invest?

00:24:19: And then you can also decide in terms of what is it capabilities internal unit.

00:24:26: With that plan in place, you can actually accelerate the implementation.

00:24:29: So from single-digit use case implementations they are now moving into a second year to double digit use case implementation and next year it's going be yeah medium sized double digits use cases implementation as well.

00:24:44: so we will see really getting foundations right?

00:24:47: We'll accelerate your implementation adoption fast.

00:24:51: Yeah

00:24:56: What time Katja, did you see or do you expect to see business value resulting from this use case adoption in terms of saving costs?

00:25:11: Saving time increasing revenue creating real ROI.

00:25:15: As of when Do You See Signals and as Of When Do You Sees Results?

00:25:23: I think the first results you can already have in the piloting phase, where obviously track down our eyes that we want to measure.

00:25:32: And typically at the beginning when talking about NVPs of use cases... The focus is very much on efficiency gains and there you typically track time saved Um, and then obviously the next thing what you do is once it's been in use.

00:25:54: It needs to be connected with your business planning.

00:25:59: The next step is actually to secure the financial performance and value out of it.

00:26:04: It need to go into your planning cycle that way.

00:26:08: Actually this how you make or transit from a potential And the quantified of KPIs into real business value.

00:26:17: And that probably takes some time.

00:26:19: so it will show the use cases that we started off implemented rolled out last year are the ones probably this.

00:26:27: yet i would first go into the planning cycle.

00:26:31: Yeah and what is a realistic dimension in size of business value to be expected?

00:26:38: kind over realistic ballpark of commercial value generated, buy these by this time saved.

00:26:47: For example, I know there's one case it is not to be generalized at all but might give a ballpark of the value that can be created.

00:26:57: so when you see the times savings now and assume really majority gets translated into PNL what potential?

00:27:09: So typically the time saves.

00:27:11: potential is around seventy to ninety percent for a process.

00:27:18: Yes, it's quite a lot.

00:27:24: Yeah

00:27:26: we're talking about days or weeks of work that can be then now generated in an hour yeah?

00:27:34: Or less than an hour.

00:27:38: And that obviously provides a lot of potential, because you typically what we see is the use cases.

00:27:47: We start off with are the ones where people say I can't even make sure That i do everything that it's supposed to be in order To ensure our growth within The time.

00:28:01: And by using AI, suddenly they can grow their potential.

00:28:05: They can monitor more market signal and serve most segments.

00:28:10: Um...they don't need to reduce the portfolio because of a lack of resources but rather it can grow much faster.

00:28:19: Uh..and that's basically something we're seeing in particular with those efficiency gains.

00:28:27: Yeah That is amazing.

00:28:29: I mean, this is a dimension of business benefit that now illustrates the huge potential.

00:28:36: That's behind all of these and listening to you...I knew it all along but it makes transparent again how systematically work out to get that value visible defined identified created unleashed and then realized brilliant.

00:28:53: Now This is leadership podcast.

00:28:58: Many people are used to dialing into the Lightwolf podcast with something related to leadership, which AI absolutely is.

00:29:08: So based on your experience Katja how does AI change?

00:29:16: The way leaders should think decide and act?

00:29:23: Yeah, it's definitely going to have an impact on how you lead.

00:29:29: And I think when your management and team is using AI... You will actually see it quite quickly because what we hear is that suddenly there are much more output things that I'm supposed to review.

00:29:57: So it's going to change quite a lot also from a leader perspective and some leaders as an anecdote probably, how they respond is that they would use another AI to look at it.

00:30:13: but i think what is important here is you keep your own judgment of the things, and you know when to trust AI.

00:30:25: And why not?

00:30:27: That's not always simple because some think it is visible in terms where they say okay I know that AI was wrong.

00:30:40: Often times we wouldn't know whether or if something went wrong as a result is reasonable.

00:30:53: The difficult part that sometimes you don't know what are the hidden assumptions in AI itself, if it's not transparent to your judgment becomes very difficult because AI results can be very reasonable and logical If you don't know that underlying data and the underlying assumptions to it, sometimes its a little bit difficult to keep your judgment.

00:31:26: So what I think important is judgement.

00:31:29: actually The second one i would thing how you interact with your team.

00:31:45: As I said at the beginning, adopting AI for an organization is somewhat a huge transformation.

00:31:55: That means change management guiding team of using AI but also changing to whole new organizations something very important as leader-to-do.

00:32:09: and in that aspect and showcase oneself as an AI learner, probably is a good sign actually how you can take on the team onto that journey.

00:32:26: Because I think at the end of day AI it's technology going to change the world.

00:32:32: everybody is seeing it And um... That gives rise for a lot uncertainty and i think fear just natural response.

00:32:42: And that's basically something as a leader, you should also address.

00:32:48: So being human and also guiding the team is very critical in that phase.

00:33:00: What resonates with me, Katja, are many more decisions than before dear leaders... ...and much faster during shorter periods of time.

00:33:16: I just learned it yesterday when i had the pleasure to have a conversation with Elia Werner from Sixth, who shared that.

00:33:23: The number of assets in communication has increased by upto a factor of a million right?

00:33:36: So and I started my career cat.

00:33:38: yeah was...I grew up in marketing..I grew even the internet was available.

00:33:45: At that time, you work on a great idea and do TV advertising or some print visualizations behind it compared to this one nowadays.

00:34:00: go into social media look for shareability with help of AI.

00:34:07: create one million more assets at a fraction cost.

00:34:14: that dimensionalized it to me yesterday and listening to you is just opening my eyes to it.

00:34:21: And I'm hearing many more decisions in much less time, consciously change the way you work with your team... ...and be human!

00:34:34: Let's not forget this.

00:34:37: On this last aspect of being human acknowledging fears as this change is at a pace that probably is unprecedented in mankind's history.

00:34:52: It's the fastest period of technology, let change.

00:34:56: I can look back to it my life.

00:34:59: there are fears.

00:35:01: There was laziness as we can't believe you had it on the end sport Katja but I learned from You!

00:35:09: There were laziness and comfort.

00:35:11: people prefer not to change because it costs energy.

00:35:14: I think you elaborated very well on how this will change the work of leaders.

00:35:21: Get familiar with many more decisions in much less time, there is one more aspect and what you share resonates with me a lot and evokes an old case or out-of-the times before AI when i took a business decision that mistrusted.

00:35:41: The data was reported by the market-leading, market research company in the world.

00:35:48: So that data was accurate.

00:35:51: still the conclusion drawn from the data Was inaccurate like I just couldn't prove it yet But i could smell it And then went back Challenging the assumptions under the data.

00:36:07: spending time with a great person like you.

00:36:11: It was not my idea.

00:36:12: We took us two times, two hours to find the one wrong assumption in the data that led to the wrong conclusion right?

00:36:22: So at the time there were two calendar years being compared and the assumption was that universe is defined same way in year One and Year Two which it wasn't because acquisitions distorted the comparability but were not corrected in hindsight.

00:36:46: And my partner found it and I then went back, took twenty thousand euros to recalculate the universes?

00:36:57: What a surprise!

00:36:59: Suddenly there was completely different conclusion.

00:37:02: so you touched on it under sidelines.

00:37:08: regarding interpretation of AI What would you advise leaders like me and those thousands on the call, what do leaders need to learn new in terms of really understanding the composition of data?

00:37:29: To inform.

00:37:32: The right conclusions and interpretations.

00:37:35: I think one thing is obviously critical thinking so taking much more time to go through probably the complete different scenario, so what if everything here is not sure.

00:37:56: What would be must-be case?

00:37:59: So basically reversing what I'm seeing and say that's not right then conclusion out of it.

00:38:12: That is probably something we, in day-to-day as a management don't necessarily do us often.

00:38:21: As lengthy at probably when we have so much AI output coming out would need to due because AI outputs are becoming better and better.

00:38:31: And that actually leads to the second point Is there some point?

00:38:36: We also need AI To help us to decipher those assumptions and decisions.

00:38:44: And because of the speed of things coming up, it will require us also use AI in itself to probably challenge what another AI has done?

00:38:58: I think third is monitor AI as well underline assumptions.

00:39:06: What i observe Organizations have not really started to systematically, typically thinking about the new data sources that the interaction with AI actually creates.

00:39:21: As we have learning systems, We say AI is getting better.

00:39:24: they remember They can learn from your feedback.

00:39:29: I'm Not seeing that Organization are systematically tracking those feedbacks.

00:39:34: because in those feedback Those other assumptions Because you're distilling basically assumptions into it when you say, okay this is good.

00:39:48: This is not good because your giving a preference in to the AI system and I think that's just being done yet but i do see that will become very important actually be able explain every decision that AI has made implicit Surround its activities actually going forward.

00:40:15: Yeah, very good Very helpful.

00:40:17: on this note I have a suspicion and also partly i would say supported by some Evidence as i've seen with my clients.

00:40:26: yeah With leadership and strategy clients working on team productivity?

00:40:31: I see slightly Significantly increase increasing time pressure in clients.

00:40:38: I see change, fatigue.

00:40:41: The number of transformations per year experienced by employees in two thousand fifteen was too.

00:40:49: In twenty-five was ten.

00:40:51: so there is an increase of the sheer number of transformation.

00:40:55: So people get a bit tired at times.

00:40:58: They take less time for the same piece of work and i wonder whether we are still taking enough time to do exactly what you suggested Katja, which was Take Time To Track Your Assumptions.

00:41:13: take time to understand the assumptions in The first place and then to monitor the assumptions afterwards?

00:41:21: To take the time to ask insightful questions And truly listen.

00:41:26: yeah so that's one of the skills I think is potentially at risk In this ever-faster time And the other one is in terms of capabilities, I sometimes wonder whether the broad presence now of LLMs and our lives risks to make us lazy in thinking.

00:41:48: Yeah?

00:41:49: So that people just get used to delegating the hard work of condensing.

00:41:56: a huge amount was done by humans and only by humans until ten years ago, has been done data more in the last ten years but is now delegated to AI.

00:42:16: Do you see a risk that we become lazy thinking?

00:42:23: I think there are many research about it... There's one research I've seen.

00:42:32: that said, if you use AI just by really replacing the things we're doing and using output getting out of it.

00:42:46: It will definitely make your... You'll become lazy in terms of brain capacities.

00:42:54: but If don't do it then use AI to challenge thinking To make yourself more productive.

00:43:00: then is actually expanding your brain activities.

00:43:04: And it's the same for, actually children because in San Francisco they open up an eye schooling where children are only taught two hours a day instead of five or six I think which is normal curriculum and there basically seeing the same diamagnomics in children They're teaching children with AI by pure replacement.

00:43:32: that is actually having less advantage of using AI and the other ones are becoming more productive, expanding their intelligence.

00:43:43: I'm not sure how hard to think about with using AI in childhood education if it's a result.

00:43:51: but as an adult... definitely already, I've already showcased that you need to be careful about AI and how your use it basically.

00:44:03: Yeah,

00:44:03: of course we need to Be Careful exactly in How We Use It right?

00:44:07: And You Are A Parent Katja!

00:44:09: You Have a Young Boy.

00:44:11: i'm a parent as well.

00:44:12: my boys are young men still...i think..we Need To Be Careful but i Think its My Hypothesis is less About Concern Towards AI In General.

00:44:25: Its Not About whether we use it, but its about how to use.

00:44:29: Because like you say the research seems suggest depending on how your using can even widen and increase your brain capacity in your ability to think depends upon how are used.

00:44:43: so let's be careful and be choice for and be smart learning.

00:44:47: how do you sit which this is all about?

00:44:50: that conversation is terrific.

00:44:52: Let me zoom into another part of your career so far and into a related topic, Katja which is the topic of culture.

00:45:02: You with your career path have had business experience as leader in two different kinds and sizes of companies.

00:45:15: BCG is one of most successful and reputed consulting companies on the planet And based on my experience working with PCG, being a client of PCG.

00:45:26: Very deserved very rightly so.

00:45:29: it's an excellent company.

00:45:31: now you joined us then you know group more than two years ago and your our managing director in A more senior role In the smaller company.

00:45:44: if You compare Your work experience between The two?

00:45:48: If you compare the culture you experience in those Two companies BCG and NUNA, how would you compare your experience?

00:45:59: As you said I think one thing that stood out at BCG is obviously the people that you encounter there.

00:46:09: The standard of thinking...the speed of thinking..the abilities to structure....The people.

00:46:20: that And that has made the experience actually taught me quite a lot of things, but it makes my experiences very exciting.

00:46:33: At points obviously is large organization with hierarchies and structures as processes.

00:46:40: That's good I think at the beginning.

00:46:44: for some people like structure process know when to expect.

00:46:50: what do you need achieve in order get toward point?

00:46:53: It is definitely something that will serve the preference of people and wish they had for certainty, predictability.

00:47:03: At NuNOW.

00:47:04: what excites me was I didn't have it at the same time as probably one key learning areas to experience at NuNow.

00:47:16: Obviously being in a more senior role with smaller companies facing quite a lot of uncertainty.

00:47:24: It's definitely the opposite to what was given actually at BCG, but I find that exciting and it is an opportunity for me grow myself in terms of culture.

00:47:33: as team we are much smaller teams And its remote set up both taking together.

00:47:43: Its another great experience.

00:47:46: Small team means We experienced each other.

00:47:51: So we have two, three weeks in a year where we are on retreat and will all live under one roof.

00:47:58: I think you get to know each other in a much intimate way.

00:48:02: On the other hand not seeing an remote setup Not being able to do coffee chats or just talk across the hallway is obviously also something that impacts culture as team.

00:48:20: So you really need those anchor points in those weeks to come together, to formulate a culture.

00:48:26: Culture is something that's made out of groups.

00:48:28: You need people who have come together To live their culture In the remote setup.

00:48:35: sometimes it's difficult At some point I think through our time now basically become befriended with everyone And sometimes it's also relatable back to BCG times.

00:48:54: because, It is.

00:48:56: Because at BCG although you're in a large organizations You are always stuffed with the team project team and that as group of five six people Sometimes ten and that group actually Spends quite lots time together when you're on a project, working alongside each other.

00:49:26: And

00:49:26: sometimes that reminds me of the Nuh-Nau spirit where we get to know one another in very short period of time and very closely with friends.

00:49:39: Cool!

00:49:39: Thank you so much for this inspiring comparison between these two.

00:49:46: Now it's obvious that you develop yourself by your path.

00:49:51: I can see it and hear it, feel by the way you communicate Katja.

00:49:56: But more specifically would you mind sharing with a group here?

00:50:01: What do you do to develop yourself?

00:50:05: Development obviously happens across different layers.

00:50:09: The best school for content development like actual content knowledge doing things is by actually carrying out the things that you want to learn.

00:50:24: And then obviously, I think throughout time as a leadership personnel it's also good to take time to reflect and have someone that you can talk to and really talk about this situation experience That can bring fresh perspective challenge some of decisions because we are all little bit We.

00:50:49: we are all human.

00:50:50: We'll have blind spots somewhere aware of some where not aware.

00:50:54: So it's always good to have that someone and be a mentor be at a coach.

00:51:00: they can go through with you on those topics, and just Sometimes only for use by yourself explain how things actually happened And to rationalize on topics That will actually make you learn from the situations you are experiencing.

00:51:22: So I think that is probably one of those things, like... ...I've come to notice just probably also not so long ago That it's a very essential part in leadership To actually talk about these situation and dissect In terms what has happened And how go-about going forward

00:51:43: Got it Thank You!

00:51:48: And coming towards the conclusion of this exciting interview, I have two more things that i'd like to ask.

00:51:55: Two sets of questions.

00:51:57: one is five quick questions also asking you for a short response and then i would like to hand over it to you in the closing section.

00:52:11: so five quick question to Katja What are your best advice?

00:52:19: Probably, someone once told me that it's not about to avoid mistake but actually make original ones.

00:52:30: So you should always look out for mistakes as others have already made and learn from them.

00:52:37: But if its okay... You should be the one making new ones basically And learn form it and serve is learning from other.

00:52:46: Yeah I like a lot.

00:52:49: Second You lead leaders also in you now.

00:52:53: What quality do your value most and leaders?

00:52:58: I think one thing that I really appreciate is telling the tough, tough truth clearly like many experiences in situations where i've seen that leaders can are very articulate Can say a lot.

00:53:20: But if you think about it, there was also not a lot of things said.

00:53:28: And sometimes it's uncomfortable or the content that you want to convey is very uncomfortable.

00:53:37: I Think in particular those moments You have to be clear and That something now i value quite a lot

00:53:44: okay?

00:53:45: Very good thank you.

00:53:47: What does your personal go-to tool when things get stressful?

00:53:51: I'm not sure if it's a tool, but what i do is... I probably zoom out and Zoom Out.

00:54:00: For example, I would just spend time playing with my son And go to an indoor playground.

00:54:06: Just be a chat again.

00:54:09: What book?

00:54:10: Podcast or quote has impressed you recently?

00:54:15: Probably many ones.

00:54:18: But one that comes into mind that is related also to our topic today, I think we don't have to fear the AI as replacing any of us but rather someone who was just very good at using AI.

00:54:41: And if you could change one thing about the world of work tomorrow what would it be?

00:54:47: Change one thing.

00:54:55: I think there are two things that's actually come to mind.

00:54:59: One thing would be how we define competence, going forward with AI.

00:55:05: it is less about what you know and whether you understand the results or ask the right questions.

00:55:14: The second one is a mindset.

00:55:20: the really agile mindset or failure mindset of being able to quickly adapt and iterate is something I think that should be changed, what improved in many aspects world-of work we see today.

00:55:42: Awesome!

00:55:43: Thank you so much.

00:55:44: So thank you for sharing this.

00:55:46: i really thoroughly enjoyed this Katja.

00:55:52: In closing, I would like to invite you... ...to either leave the audience with a key message that you'd like to share or question.

00:56:04: You'll ask your audience to reflect about it.

00:56:08: So what do we want?

00:56:11: How every leader is using AI To become better as leaders or using it actually to avoid parts of leadership?

00:56:25: that is hard.

00:56:27: Because I think AI can do a lot of things, but it cannot develop judgment and take away the decision.

00:56:41: so owning the decisions should still be part be given away to AI too much.

00:56:56: Yeah, I think the perfect conclusion of this conversation.

00:57:01: absolutely agree very inspiring to have you on call.

00:57:06: thank you very much dear Katja Spörer.

00:57:09: Thank You Stefan.

00:57:09: it was a pleasure talking with you and it's been nice exchange.

00:57:13: And to you, our dear listener.

00:57:16: If you are interested in getting in touch and having an exchange with someone who knows how to start working on AI creating business value or accelerate your journey.

00:57:28: please do not hesitate To get in touch with Katja.

00:57:30: You will find the direct link to her and to new now In The Show Notes.

00:57:35: Thankyou very much.

00:57:36: Take care!

00:57:37: See you soon Bye bye.