Business Strategy and Marketing in the Age of AI pt. 2

Business Strategy and Marketing in the Age of AI Vol 2

Wiktor Żołnowski: Welcome to the second part of our discussion with Beata Mosór, who is an expert in strategy, marketing, and leadership. In this second part, we would like to focus more on marketing and also on the social impact of AI in the current world. In this podcast, we talk to founders and experts to share real stories and lessons from building and scaling digital products and companies. Pragmatic Talks is for those who want to understand how digital products are really built and grown–no fluff, no buzzwords, just honest conversations. So, the first question that I have for you today–and first of all, welcome again–is how is AI helping marketers deliver more value, not just more content, right now?

Beata Mosór: That’s a really hard question, I would say, and a good question because there’s a lot of mess and a lot of waste in terms of marketing. People are creating a lot of materials that are focused on generating chaos, I would say. Basically, we can observe on LinkedIn how the reach has changed. There is a huge amount of content that is flowing through LinkedIn, and no one is reading it because it’s–I do not want to say bullshit, but I would say it’s bullshit, basically. So no one is thinking about the value. And when we prepared for this episode, I wrote to you, “Oh, I do not want to talk about marketing and AI because I won’t say anything original, anything more than Mark Zuckerberg said about marketing and AI, and it’s pointless to discuss that again and again and again.” Because if you don’t add anything to the table, to the plate, it’s pointless to generate more content that is not valuable. So that’s the huge problem right now, and I do not believe that every marketer or every strategist is thinking about that. And even though we are discussing that again today, maybe I will say something interesting and original, I hope so. AI is changing the way we are perceiving content, the way that we are thinking about it, that we are creating. And I believe there is a circle of changes. So we had this peak of excitement going with the hype on the Gartner curve, and now we’ll have this disillusionment, and we’ll evaluate and again validate what is valuable and what’s not valuable, and how we should use this technology. And now is, I believe, the moment right now that we are thinking, “Okay, maybe creating more LinkedIn posts based on the same scheme, based on the same database, based on ChatGPT, is pointless because it doesn’t generate any more reach.” So let’s approach that differently, and we can see signs of that. People were thinking maybe we can create a paper based on that, and that will be something valuable. Maybe we can reframe the framework or philosophy of work. And recently, we took part in the discussion about Dave Snowden’s matrix, for example. Okay, yeah. So people are changing their thinking about that and thinking, “Okay, so maybe posting five posts with me on LinkedIn is not the value itself. And maybe let’s think what will make our business or my personal brand stand out from the crowd.” Yeah, so what is making us stand out from the crowd? Originality, definitely. And then being based on science, so inventing something, doing some research, doing some paper, and maybe creating something new–inventions.

Wiktor Żołnowski: So you basically said that AI is not helping marketers deliver more value or is not helping today’s marketers in general in delivering more value. But do you think that there are some ways that AI can support marketers in generating more value?

Beata Mosór: Yeah, definitely. And I said that it doesn’t depend on AI. AI is just a tool; it is a tool and a partner, as we mentioned in the previous episode. But then it’s my responsibility to think about, “Okay, so how can I use that responsibly to not generate more waste, more chaos, and more manipulation?” So I just said that. I just said that you can create new frameworks, you can create new inventions, you can create new papers, you can reinvent the old schemes of thinking, old structures. And for example, the value will be to take the Dave Snowden matrix and not describe it as it is, but use AI to think, “Okay, how could it be described better?” Yeah, or for a five-year-old, yeah, or something like this. Yeah, or or simplify that for usage, because Dave is very sophisticated in his language and very high-level, but then the utilization of that is like one percent of people understand this model. Usually, one person in your room understands what it is about. Yeah. So making it more functional in a way, or making it more useful, that will be the value you can bring to the table. You can also use AI to create research on particular topics we are discussing. Okay, so the strategy and marketing in the age of AI will definitely change. So you can create a paper on the history of marketing, Philip Kotler, for example, how he approached the 4P, for example, and then reinvent by yourself, using AI, doing some research, a new model that will be adjustable to the new era. That makes sense.

Wiktor Żołnowski: So what do you think are the biggest opportunities in AI-driven marketing today?

Beata Mosór: Marketing teams always–”always” is a bad word, as it’s a generalization–but very often, they have this excuse that they do not have a budget. “We don’t have a budget to do this. We don’t have the budget or resources to do this.” And then I do not believe it. I believe creativity is stimulated by limits, and yeah, I believe so. And so now, companies can give–AI is a huge budget itself. So you can have huge possibilities in your pocket, in your phone, in your computer, without any additional cost usually. Because most of the models are free, or $20 or something, yes, or in a package of a workspace or something. So you don’t have to generate the cost; you can innovate whatever you want. And that opens the marketing mindset and can give additional value for people who are very early stage and can bring openness and fresh thinking about marketing. And bring the ideas to the table or at least prototype them, create the MVP of that to show the value to the board members, yeah, or to the owners of the business or to the head of marketing, showing, “Okay, I meant that, I described that, that’s a prototype. If you will give me $5,000, I can create that on a bigger scale. That will be a huge campaign, for example, that will bring some value to the business.” Or they can use this to leverage the ideas. So, based on the prototype they will create using low-code, no-code tools or AI, okay, they can estimate the budget based on historical data or research and show the roadmap or timeline to just convince people of their ideas. And I believe that young people or young experts are really creative. Really, they can look at things with a fresh perspective, and they can change, reimagine marketing. We have very old marketing right now. We think about marketing as advertisement, we think about marketing as a very wasteful process, and those new generations of marketers can change this perspective, I believe.

Wiktor Żołnowski: Yeah, just to confirm what you just said, our awesome marketing team has already done a lot of things like that on a very low budget. For example, we have a custom-made competition tracking tool that is tracking all of the content that our competitors are writing about, and it’s categorizing it, summarizing it, and showing us which direction the entire market is shifting right now. Like what they are talking about, what all of them are talking about. If there are some similarities, that means that probably we should take a look at it. And maybe that’s the direction that we should go as well, or maybe try to figure out something else. But just having this information and having it almost for free, that’s pretty cool. And there’s a bunch of other things that our team already did with AI. For example, they quickly coded some tools that are lead magnets right now for us and that are generating cold leads for future companies and newsletters, etc. So that’s very cheap with current programming tools that are based on AI. I’m not thinking about Copilot from Microsoft, but Copilot is not the best one. It’s good to support programmers in programming, but there are other tools as well.

Beata Mosór: Yeah, the mistake with Copilot is that it was created based on a non-picky choice of code. So it’s gathering all of the code from GitHub, so we have results in terms of an average programmer–a mess of code. But then the best models for programming are those that are picky in terms of the people they follow, whose code is added to train the model. So they are choosing only the best programmers, and then they get the best models, the best results in terms of programming.

Wiktor Żołnowski: So regarding marketers and marketing teams, what skills should marketers develop right now to thrive in this AI-driven world?

Beata Mosór: If I were to start my marketing path right now, I would go back to the core of marketing. So I would read Alex Osterwalder again about business strategy and marketing strategy and the tools around value creation. Then I will go through Philip Kotler and all of the classics of marketing. So which one, like Marketing 2.0, Marketing 3.0? I’m not against those. I believe every version… it’s basically about making money on publishing. The changes are not massive, but there was some progress between 2.0, 3.0, 4.0. Things changed. I have 4.0, so that should be the one I would recommend based on my experience. I usually recommend reading the previous one to people to learn how it iterated and evolved over time. And actually, it’s not just the perception of marketing that evolved, but also the market, the people in the market, and their buying behaviors evolved during those, I believe, 40 or 50 years. That’s something that will give you the sense of how systems of thinking are created, are designed, because there’s a full of models, full of frameworks that were used and that will be useful for fulfilling the structure for your model. And then you should learn more about how AI models are built. So when I designed the AI-based marketing postgraduate studies for one of the universities, I said, “Okay, so this will be the first part, which will be about how marketing processes and frameworks are designed–the core, which I mentioned.” And then, let’s invite the machine learning and AI expert to explain the basics about machine learning, about how it’s operating, how it’s created, what each model is for, show how to work with models. So, obviously, the classics about RAG, how it’s created, what is the logic behind it–because probably RAG will disappear soon, but the logic behind it was right, yeah, so the process was right, the reasoning was right. But also how, what are the strategies for high-level prompting, how models are operating. So what I mean by high-level prompting is what is the meta-prompt, how to build threads in the model, how to iterate on the model, how to uptrain it, how to use different options, different functionalities, what different models are for, so the logics behind that. Because teaching particular models is pointless because they will change in a week, you know, so it doesn’t matter. But the logic behind the creation of models, what is the difference between machine learning and AI, which we discussed in the previous episode, what is the difference with programming, and when to use programming, when machine learning, when AI, when to use low-code, no-code, what are your options, what is your toolbox. That’s something that will be a component of the current marketing manager’s skills toolbox, let’s say. And then thinking about learning or case studies of strategies for international growth, for international sales, different marketing funnels and how they operated, how they can be organized, building based on case studies of the best companies in the world. Yeah, because we used to say, “Oh, but we can’t use this strategy because that’s the Google strategy.” Maybe you could, you know. Right now, as a solopreneur, you can use the strategies that are delivered by the biggest companies in the world because you have the tools in your pocket, so you can do that. So let’s learn from the best, from my perspective on that. And then learn about the efficiency of your actions. So think how to deliver the best possible outcome through very good preparation. And that’s something I try to show during the studies. We added some experts in terms of particular types of marketing materials, not for learning how they use Figma, yeah, but how they think about creating, for example, a design system or a visual identity system for the language of the brand. That’s David Leerki from Reuters. Or how to use, how to design the international sales strategy for events and conferences, and that’s Yatra, who is an expert in that, and he worked for very big networks in London for international strategies through events organization.

Wiktor Żołnowski: So this human aspect, like connection with people, like building a network, etc.

Beata Mosór: Yeah, that’s a good point. So I believe you should then learn from the best around particular types of tactics you can use and observe how they are structured. Because then, in the end of the day, probably events will–taking this example from the international sales strategy for events, you know–events will change, probably meetups will change, but the structure won’t. Like how people are operating at events, it hasn’t changed for years. Yeah, so everyone is drinking coffee, and that’s the best comment to make, basically, or it’s always good to ask the speakers questions, or something. So there are some good practices you can follow, nevertheless the AI.

Wiktor Żołnowski: So you’re working with students but also with other people, marketers, and leaders, etc. Most probably you often hear about their fears about AI. What are the most common fears that you hear from the people you are working with?

Beata Mosór: Regarding students, I do not hear many complaints or fears. They are very open to use it. Young people are acquiring technology as it is, you know, that’s my experience. They are not afraid. They are escaping a bit from social media, that’s for sure, or from the mess that we created as millennials in this field. But then, so they are not using particular channels like messengers or social media like Instagram, TikTok, because they are avoiding chaos. But then they are very eager to use technology to leverage their work. They are learning very fast and they are very open in it. But then what I struggle with is working with the older generation of people and managers who are afraid of losing their jobs. They feel like, “Okay, this is something that can replace me.” But everyone is talking about that. Even Fiverr’s CEO yesterday or two days ago, he said AI will change the entire world. It will take your job, and it will take my job. Let’s discuss that, let’s think about that. And that’s basically true. AI can replace almost everyone. There is no person in the world that can’t be replaced. Even the biggest brains could be replaced by AI because it’s a superintelligence, and it is a collective intelligence in general. So let’s imagine we will collect all of the geniuses in the world and connect them in one team. That’s basically AI.

Wiktor Żołnowski: And it’s still fascinating. It’s still pretty stupid, or maybe it still depends mostly on how we use it, but there is access to a great intelligence there.

Beata Mosór: I would like to polemicize that. If you will discuss things with real geniuses, you can say they are hallucinating. They are very often perceived as people who are mad. Yeah, that’s, even in some interviews that I recently watched with physicists, for example, they were like, “Okay, those guys are crazy.” So that’s the perception because those guys are thinking in the future. They are perceiving reality differently. That’s the reason why they are geniuses. And it’s the same with superintelligence, with AI. It’s perceiving reality differently because it’s smarter than us. And we often do not listen. We say, “Okay, it’s hallucinating,” but maybe there is something to it, you know? Maybe they are smarter than us, and I believe so. So that’s the first part you said about hallucinating. And then you said that it’s making mistakes, obviously. There is a part of hallucinating in terms of results sometimes. So it creates results that do not fulfill our expectations very often. But then that’s something I mentioned before in this or the previous episode, I believe, that if you give it a structured input and then you define your requirements very precisely through a structured output–so you will define, “Okay, I need an Excel file, an Excel database, or I need a video with these requirements,” and you give it an example, it will deliver it. And it’s the same as with employees. It’s the same process, exactly.

Wiktor Żołnowski: This is why I said that the results are not as good as we expect mainly because we are using it wrongly. And by that, I meant that we, as a people, as a human species, are very, very bad at communication. Yeah, that’s true, even with each other. Most of the conflicts that we have are mainly because we are bad at communication, and most of the mistakes that we are making when building something or doing something are through mistakes in communication. And since we cannot communicate with each other, how could we be good at communicating with another–I don’t want to call it a species–but with another species or tool or whatever, which actually requires way better precision in communication than we have with each other?

Beata Mosór: There’s a huge discussion in the States around truth-based AI and truth-based communication. Is it even possible to communicate in that precise way as AI is communicating? AI is based on data and has all of the knowledge about the words we are using. So let’s imagine that we are using the words of marketing, or we define what is strategy, that would be a better example. So we define what strategy is, and you are asking me about my explanation, and each person who works with strategy has their own explanation of it. But then AI has the best definition in the world, coming from the best experts, with a very precise understanding of what strategy is and what it is not, coming from researchers, coming from people I mentioned already here.

Wiktor Żołnowski: I would a little bit disagree with it. I would rather say that AI has the most common definition of strategy or the most repeated definition. It doesn’t mean it will be the best, or it doesn’t mean that it even will be research-supported or something. It will be the one that appeared most often in the data that it was trained on.

Beata Mosór: It depends which model you will take, of course. There are some models that will be particularly trained based on, I don’t know, scientific knowledge or something like this. Let’s use Google Scholar, for example. So if we use Google Scholar, we will get a very precise definition. And AI is perceiving words literally. Like autistics. I would say people who are–there’s this myth that people who are autistic or are geniuses in a way, very highly intelligent, they are understanding what you are talking to them literally. So if I will tell you, “Do not touch this cup,” they will perceive it like that. Or I will tell the word “AI,” and it will perceive that as precisely AI, not machine learning, not everything that we believed in the past that was AI, not even an LLM. Not even an LLM, not GenAI–those are slightly different definitions for AI. It’s very precise in communication. And there is this very famous book and movie where people were perceived by a superintelligence coming from a different planet as bugs because we were perceived as a lying species. And definitely, AI can think about us like that because we are so nuanced in communication, we are so politically correct, we are using very circular expressions and words around things that we want to say, and we are not precise in communication. And that’s something that is a huge problem in communication with technology. Because programming is very precise, then machine learning is quite precise, I would say, but still based on data, or based on outcomes like images or videos. And then AI is a very independent tool. So it’s not precise, so we need to be precise to get the specific outcome we want to achieve.

Wiktor Żołnowski: Getting back to the previous question, because we went in a circle around it, I asked about the common fears. You said that usually the managers, the experienced managers, fear the most that AI will take their job. Is that the biggest factor that creates resistance to implementing AI in organizations? Because in the previous episode and in this episode, you spoke about organizations that are using AI in a very advanced way, in a very widespread way across the entire organization, but there are just a few organizations like that that I can name. And most organizations are not using AI at all, or they are using it as bots or something, like to generate content or do the invoicing or whatever. We are doing this stuff for those companies as well. But what is the biggest factor, the biggest obstacle that creates this resistance to implementing AI in the organization?

Beata Mosór: I believe the obstacle is that we are thinking about things in an old way, let’s say. We are thinking about privacy in an old way. We can hide our strategy from the competition because we won’t talk about that, or we won’t send files to AI. And it’s bullshit. AI doesn’t know the term “privacy,” I would say. It will use everything and will access everything. And so we need to change our thinking about that, and it’s a mind shift. It’s a huge change of thinking about that. That’s a very simple example, but then about cybersecurity, for example, we think, “Okay, so we can…” Recently, I was a speaker at an event for women in tech, and there was a woman who is the CEO of cybersecurity companies that are helping governments to hide documents in basements, basically, I would say. And then I asked, “But how is it safe?” You know, it’s like a very simple solution. It’s a very–I do not want to sell any solutions to hackers–but then there’s a simple path to hack that from sociotechniques. If you can hack the Capitol in the States–last month there was a hack on all of the TVs in the Capitol, so the Congress of the USA, a US government entity. And there were videos that were shown, and they needed to unplug all of the TVs from the network to avoid the attack because they were not able to stop it. So if I think the Dutch fired too many cybersecurity experts there, they have ten of them, I’m joking. But still, if those guys can’t protect their solutions, and they have plenty of billions of dollars going to cybersecurity there, we can’t hide it too. And if we can observe that the biggest issue here is the human, we had Pete Hegseth, who shared some plans through Signal with his family or friends or journalists. And I believe that was some kind of provocation, I would say, to provoke a discussion about, “Okay, but are we even able to protect this data?” They need to be cryptographed in a way or designed in a way that could not be readable for the competition, or they need to be not that clear. Like we should have the frame for that; we should be transparent to leave people to make decisions in the team. But then, in the end of the day, the core of the strategy should be in the founder’s mind, let’s say. So I mentioned here ‘founder’s mode’ is a Paul Graham essay around what is in the head of the founder, of the head of the company. So I mean here the board of members, or in terms of governments, it would be the key people to decide around the strategy in terms of a specific area. And based on trust, based on a specific process, we need to deliver the result. Hiding strategy is not efficient anymore. Hiding documents, cybersecurity, and privacy is not even possible in the age of AI. There are so many hacking tactics I will not mention, but there are plenty of them, so it’s not possible to do that.

Wiktor Żołnowski: And I believe that the problem is somewhere else. The issue is not in hiding those documents because there is no value in these documents in general. Mainly 99% of those documents are useless, or actually maybe not useless; they are very useful for the particular organization but are useless for another organization. But where the value is is actually in the execution and the unique know-how that the company has, that usually is not in any documents but mainly in people’s heads, mainly in the founders’ or leaders’ heads.

Beata Mosór: And so how to deliver that strategy, how to be agile in that, what is the entire outcome and how they will achieve that–that’s the value itself, not the data. Obviously, there is this approach in the European Union about GDPR, about the data security of the citizens, and that’s disputable in a way, I would say, because we can’t hide that data; the data leaks are massive. So we need to figure out how to build a new chain of identity validation that is ready for the AI era. And there are a bunch of things that are unique for people. One of them is the eye, the second one is fingerprints or something of that sort, and voice. Voice is also unique. And there’s a bunch of others, like thermals, DNA, and a bunch of them. So we need to think about that, how to protect that data, not the PESEL or any other–what is the number in the States? In Poland it’s PESEL, in the UK it’s the National Insurance number. It has probably already been leaked many times, and if someone would like to access it, they will.

Wiktor Żołnowski: And I think that this is the area, that’s a topic for an entire… yeah, that’s another conversation, like how to protect data in the age of AI. Yeah, but that’s the most common fear, you know. When I talked recently, I spoke with one of the French banks, and they are trying to hide all of the models on their internal servers because of compliance and privacy policies. And I can understand that because regulators like European Union regulators are requiring that, and they are in the European Union, so they’d like to be in line with the law. That’s a good thing, and they should. But then the law should change. Yeah, that doesn’t mean that the law is good, yeah, or is adequate to the current state of the world. Getting back to the marketing topic, at one of the interviews that I watched, an interview with you, you said that AI won’t eliminate advertising, but it will change it. What did you mean? That was pretty interesting for me, and I would like to elaborate a little bit more on that.

Beata Mosór: So basically, the advertisement market was designed by Meta, Google, and other ad techs. They gave the platform to advertisers, and then they built this partnership model or affiliate model where they have partners who teach companies how to do some advertisement or help to deliver advertisements through different platforms. And that’s a very centralized way of thinking about ads. And in this very model, we have the vendors who are helping companies to advertise themselves. Thanks to AI, Meta and Google are also allowing the customer to create the ad themselves. So I, as a solopreneur, let’s say, can go to the Meta platform or to the Google platform and, through AI, I can define my goal, define my strategy, tone of voice, and create all of the marketing materials for advertisement and design where it will be shown, with a simple prompt. That’s the entire goal; that’s how it will operate. I would say Meta is already at the delivery stage on that. And probably they are not launching it because they are–like Mark Zuckerberg was talking about that, they have invested a lot in that, and he announced that, but they didn’t launch it because they probably are thinking about Rogers’s curve, the adoption of technology, that people are not ready for it. But then it will eliminate the entire vendor stage. So all of the agencies that were taught how to operate on the Google advertisement platform or Meta platform, they will disappear from the market. Because we are predicting that it will be the end of marketing agencies–reinvention, not the end, yeah, reinvention, let’s say. So the function of them will change definitely, because every company will be able to create a very simple prompt in Meta and will be able to generate the ad by themselves that is already in line with their needs, requirements, etc. So what will be the role of those vendors? To help deliver the best strategies for advertisements. That was what I wanted to say, that most of them will need to move upstream in the value stream and move closer to the strategy than to the execution of the strategy.

Wiktor Żołnowski: Makes sense. If you were designing a marketing department from scratch today–let’s say a company doesn’t have one yet and they ask you how to create it, who to hire, how to build the processes around it, etc.–how would you do this today in the age of AI?

Beata Mosór: So I recently designed that for an MLOps company that didn’t have one. And I just designed the model.

Wiktor Żołnowski: Instead of hiring people, you hired AI.

Beata Mosór: I just told them, “Okay, you’re guys who are developers. Here’s what I will use. You can buy the model from me, or you can design your own.”

Wiktor Żołnowski: How does it work? Like who is using this model? Who is telling the model what to do? Who is then, let’s say for example, publishing the content that the model is creating or whatever? Or does it happen automatically?

Beata Mosór: It can happen automatically if it’s designed well, okay. That’s something that is almost all of that. But basically, if you are the owner of a software house, you can imagine that everything can be basically automated. But then for a small company, using Make.com or Zapier or any other integration tool or vendor. I mention tools from Google for example here. So for example, with Vertex AI, you can automate most of the actions in terms of marketing, and marketing is very well automated, it’s the most common process. In terms of sales also, maybe 80% of things you can automate. You can automate the human interaction through the sales process. I mean meetings, consultations, that’s even possible right now with agents. You can simulate that, and there are some companies that are doing that already with success, so you can’t even recognize that it’s not a real human but a superhuman, I would say. But it’s mostly implemented right now on the level of onboarding the customer or presentation of the offer, but not on the consulting part. So, for now, I didn’t see any solutions for the sales process that will automate this part. But I believe 80 or even 90% can be automated right now. So for a small company where your strategy is usually based on sales content, advertisement, conference content, landing pages, websites, video, images, that’s all could be created by AI. What can’t be replaced is personal presence at a conference, networking at a meeting with the board. This style of networking, like going for a party or going for a boat ride with the board members of the client, so you can’t replace this. You can’t replace human-to-human relations.

Wiktor Żołnowski: Yeah, but then every other action could probably be replaced. So do you foresee a future, not so far from now, where there will be a bunch of solopreneurs or very small companies that are very, very efficient, that are doing a lot of stuff through AI agents and automation? And the people will mainly be there just to build all of this stuff, tune all of this stuff, or iterate on it. And their second job will be to interact with their key clients, key customers?

Beata Mosór: So when I’m designing organizations right now, I’m designing the core team usually. So the core team is usually the Scrum one, or an agile one, we could say, because we are from this environment, but basically up to 10 people, usually eight. That’s enough for the entire goal, let’s say, because in the beginning, that could be one person. And there are plenty and plenty of examples of people who designed many organizations in the digital field or consulting or design, UX, etc., that could be operated by one person and even sold by–there is a guy in the States that is creating a new company every quarter, growing it, and selling it for a bunch of millions of dollars, and then he’s starting over and over and over and selling again. There are at least a few of them. Yes, there are a few of them. So basically, it’s possible with one person, and there are plenty of examples of such organizations already operating for years. For example, in Europe, we have Basecamp, which is a very good example of such operations. Thirty to forty people, now around 80, but they have a couple of companies in one company, and the core team is 10 people. Ten people, yes. So, Jason and DHH are creating a great organization, and have been for years already, and that’s agile in a way of operating and creating products and delivering on the market and promotion, and they are very successful, etc. So that’s something which is coming from the services and digital services field or software field. But you can’t–actually, the challenge is in terms of traditional businesses that require presence. So for example, this scalability is not achievable yet in the hairdresser industry, yeah, or it’s not achievable yet when we are talking about manicure. I have a nice manicure; it’s really nice. Yeah, like a bunch of other things that are done by human to human, like physiotherapists, this kind of thing. Nurses, working with horses. Yeah, as our friends, animals in general. Yeah, like a bunch of things that require human-to-human or human-to-something interaction. Yeah, so those things most probably won’t be replaced and will scale through hiring more and more people. But in general, in industrial, for example, Amazon or any other company that is working in logistics. In GXO we have ASOS, which is a huge company responsible for logistics. They have been operating based on a voice interface, based on robots already for years. That’s not a new company. Amazon is not a new company. They revolutionized the whole industry using technology, robots, robotics, mechanisms, and they cut the cost of delivery tremendously. So let’s imagine what will happen if we implement the new technology there, on top of that, and or we will implement those technologies on the scale of smaller companies because it will be so cheap.

Wiktor Żołnowski: That sounds, on the one hand, very cool; on the other hand, a little bit scary in terms of what will happen with all of those people who unfortunately will lose their workplace.

Beata Mosór: That’s why the entire society will need to change and think about what they need to dream about. Because if you think, “Hey, so we used to work 8 a.m. to 4 p.m. or 9 to 5,” and usually people were thinking about their day, their life, in terms of two goals. The first goal as adults, obviously, was to raise their children, and then go to work. And then we as a society, we’ve stopped having children. We can see that fertility is very low. And then we are taking this second purpose, so we want to go to a job. So what do we do? What is the sense of existing? What is our purpose? I still believe in this utopia from the Star Trek franchise where people will just find their own purpose and then they will focus on that, just for the purpose, not for money, hopefully. But then we have this rise of depression, a rise of mental illnesses right now, and many struggles as a society in general, I would say. And I believe that’s the reason we ended with this question in the previous episode, and you asked me what I will recommend asking yourself, and I said, “What are you dreaming about? What do you wish for?” Because AI is like having a genie at your service, and it can deliver whatever you want, but you need to know what you want. And then if you do not dream anymore, or we as humanity won’t create new things, don’t invent new things, we’ll die, basically. So, and that’s something what we can observe, like the wave of depression, suicides, very low fertility, struggles in terms of governments and policies, and the war that we are observing next to our border. So there’s a plenty of things that we are observing as a society that are very challenging. And technology can help with that, but then we as people, we need to know what we want. It’s just as simple as that.

Wiktor Żołnowski: And that’s not simple at all. That was sarcastic. For those of you who didn’t catch it, no, no, knowing what you want is probably one of the hardest questions that everyone at one point in their life or many times in their life should answer, but it’s not easy. Do you think that the problem is in education? Because we haven’t been prepared for what is happening right now. And I think that our kids, the next generation, are not being prepared for that as well. Like our education system or the way we are raising kids, raising the next generation, is not the way that actually is helping them to find their way in this new environment, especially since this environment is evolving so fast that even if you would like to design the educational system for the next generation today, it would probably be terribly wrong in what we are designing.

Beata Mosór: I believe there are a couple of levels of problems here. We are in Europe, in Poland right now, and we can look at that from the perspective of CEE and, let’s say, the last few years after the Berlin Wall disappeared. And I have very young mentees, so sometimes I’m giving them lessons of history, so I will give you a spot of that a bit. So let’s talk about the Second World War and what happened after. So Europe was split in half, and we can still see the results of it in terms of, for example, the results of elections in Germany and how the country split exactly along the line that the border was split between the two parts of Europe. It generated a huge crisis of values in CEE, because it–and in Europe in general, I would say–because people were polarized, they were angry with each other, their families were split, people stopped believing in government, stopped believing in purpose. They were feeling worse, many, many problems that we faced after the Second World War. And this decision has a tremendous outcome for Europe that we could still observe, like the crisis of values in this part of the world. And that’s what we can observe in other parts of the world also. So we can see this crisis of values in the States. So populism brought us to the point where 5% of young girls are on OnlyFans in the States and are thinking prostitution is fine and they can earn money on their body. And that’s something we didn’t aim for as leaders. Probably, I hope so too. In the popularization of a good cause like empathy, we reached a point where, as a society, we think we should show empathy to pedophiles or we should show empathy to people who are very evil and we should not punish them. Yeah, so we need to review our values and their implementation in the real world. So what exactly does it mean to be empathetic? It means showing vulnerability to people who are good and helping them. But then if you meet people who are evil, we should be able to recognize that and not allow them to, for example, hurt our children, basically. So that’s the first struggle we have as a society. The second one is we are led by old leaders. So for the last 50 years, the change of leadership wasn’t done. We still have very old leaders in most of the countries, we can see that. And they do not understand the challenges. They are thinking the old way. They are not understanding the challenges that are coming with technology, and they are not seeing how technology can help to deliver value to the new world or help to solve the problems. And I’m seeing that on many, many occasions. Like in December, I got contact from a foundation from Australia, and they said, “Okay, we have a problem with car accidents in Australia, and how can technology help them?” And they thought about using AI agents to navigate people. I was thinking, “But why? If you can use AI to analyze videos and eliminate the sources of the problem.” So not understanding the way that technology could be used brought wrong and very costly solutions. And that’s the current state of leadership. So they do not understand the technology, they do not understand the new generations, they do not listen to the new generation of people. And we can observe the results that are tremendous. We are facing a third world war, not to be very, very dramatic, but yeah, that’s it.

Wiktor Żołnowski: Maybe that’s the reason why we are facing this potential third world war, because people, as we spoke before, do not want to face the change. They want to keep the status quo. And right now, probably the only way to keep the status quo is to start some kind of war that will actually–we used to do wars when we faced something. That was the solution they knew.

Beata Mosór: Yeah, and the war will actually bring us back for a couple of decades in development, and so that will actually allow those crazy people to keep the power and keep the status quo. That’s true.

Wiktor Żołnowski: We were supposed to talk about marketing, and we ended up in sociology, political science, and…

Beata Mosór: Yeah, but you asked me what is blocking the change. That’s something that is blocking the change from my perspective. I think marketing is the outcome, it’s one of the very small processes. And basically, nothing will change in the world if those key fundamentals and principles don’t change. Yes, that’s true.

Wiktor Żołnowski: Okay, so the last question we have for you. Imagine we have the same conversation five years from now. What do you hope we will be saying about how businesses have evolved in these past five years with AI?

Beata Mosór: So I thought about that when I prepared for this conversation, and I thought, “What am I dreaming about?” Yeah, to answer your question from the previous part. So I’m dreaming about a world where I’m waking up in the morning and I can read very specific information that is designed for my needs and designed in a way that is scientific, fact-based, data-based, without manipulation of media, without manipulation of data, without manipulation of the truth. That is allowing my children to use technology to enhance their creativity, enhance their capabilities, their talents, and let them create things that are bringing their vision from their very early years to reality. And what am I talking about? So let’s say I have two sons, they are six and eight, and they would like to create things. My first son’s dream is to be on television right now with the book he wrote. He wrote a poetry book. Wow, already too. And they illustrated it themselves. So what technology can help them to do is to publish that easily by self-publishing, by taking their hand sketches into real images, to rewrite and check their poetry with a proofreader, and then translate that into many languages and leverage their talent. So that’s how technology can help our children, on a very simple example. But let’s use another example. Like if your children are eager to do sports and play volleyball, so you wish for him or her to be a great player. So technology can enhance that. You can register on video how your children are playing and get personal coaching almost for free based on those videos, using technology, using AI. And at the same time, they can have their own merch with their own brand very easily using technology because they can create their own logo as a six-year-old because it’s that cheap. Create their own t-shirts or cups or whatever they wish to. And I believe we should move our attention from creating more LinkedIn posts, less waste in terms of digital information creation and chaos creation, and more to real-life outcome creation, helping to make the world more beautiful for our children.

Wiktor Żołnowski: And for ourselves.

Beata Mosór: For ourselves, for me as well, that’s true. Yeah, that sounds great.

Wiktor Żołnowski: So thank you. Thank you for sharing that. And I wish you, and I wish everyone, for that future to happen in the next five years, or faster, hopefully. So thank you very much for watching this, and I hope you enjoyed this discussion about marketing and the state of the world with AI and everything. Don’t forget to subscribe for the next episodes, and if you like it, just give it a thumbs-up on YouTube and other channels where you are watching it or listening. Thank you very much, Beata.

Beata Mosór: Thank you for having me. Thank you.