Latest / Imperfect Marketing / Why People Who Use AI Will Take Your Job Before AI Does

Transcript

Why People Who Use AI Will Take Your Job Before AI Does · Imperfect Marketing

• 0:27
  Speaker 1: Hi, I'm Kendra Korman.
• 0:29
  Speaker 1: If you're a coach, consultant or marketer, you know marketing is far from a perfect science, and that's why this show is called Imperfect Marketing.
• 0:38
  Speaker 1: Join me and my guests as we explore how to grow your business with marketing tips and, of course, lessons learned along the way.
• 0:46
  Speaker 1: Hello, and welcome back to another episode of Imperfect Marketing.
• 0:55
  Speaker 1: I'm your host, Kendra Korman, and I am super excited to be talking about one of my favorite topics.
• 1:00
  Speaker 1: Of course, that is AI, and my guest today is Nuri.
• 1:05
  Speaker 1: He is the VP of Commercial and AI Marketing at Intel Corp and recently wrote a book about AI.
• 1:13
  Speaker 1: But we are going to be talking all about AI today.
• 1:15
  Speaker 1: Thank you so much for joining me today.
• 1:18
  Speaker 1: Why don't you tell us a little bit on how you got into AI?
• 1:21
  Speaker 2: Absolutely.
• 1:22
  Speaker 2: Thanks a lot for having me, kendra, on the show.
• 1:24
  Speaker 2: So I was working on AI when I was in college, like almost 25 years ago, but, like AI changed a lot, especially in the 2018-20 timescale.
• 1:36
  Speaker 2: We have seen a lot of progress on large language models.
• 1:40
  Speaker 2: Many people, I think, will refer to ChatGPT as a movement.
• 1:43
  Speaker 2: I was working at Microsoft for 17 years and I worked on data and AI marketing and that was my team, working closely with OpenAI team, and really having that moment really inspired me to work around AI and like how this is going to change almost everything, but specifically the area of marketing, which I'm working on.
• 2:07
  Speaker 2: So, yeah, like I mean, I'm with Intel for the last two years really infusing AI into every work that we do on the marketing, but also working with our partners and making sure everybody benefits from the AI and really accelerates the business outcomes of, like you know, waiting faster, saving more dollars and, of course, executing really timely and fast.
• 2:30
  Speaker 1: Okay, so I love that and I have to like just comment so you have been working on AI for a long time, because people ask me all the time whenever I'm presenting about AI or talking about it, they're like, well, it's only been around a couple of years and I was like, you know, like I've met people who majored in it, you know, back when they were in college, and some of it was college before me.
• 2:49
  Speaker 1: You were in college while I was there, but that's so cool that you were working on it for so long.
• 2:55
  Speaker 1: And really, yeah, I mean people look at the unveiling of ChatGPT as like this moment in time where AI like happened and it's like, no, it didn't Right, it's been around for a really long time and actually many of the use cases we see today, not all of them, are generative AI.
• 3:16
  Speaker 2: So, again, like gen AI is a term that we get used to, but the basics of AI, which is like starting with machine learning and it's all about the algorithms learning from each other.
• 3:26
  Speaker 2: So, and then many of the techniques that we use today in marketing, they are actually the basics of AI from like 2010s, 2012.
• 3:35
  Speaker 2: So, again, like I mean, I know I mean we will speak a lot about Gen AI and agentic AI, but again, majority of the things like on forecasting, predictive analytics, customizations, on campaigns, many of them are just using the basics.
• 3:51
  Speaker 2: The better term is narrow AI, but again, it is still AI.
• 3:56
  Speaker 1: Yeah Well, and sometimes people are talking about things and I'm like I don't even think that's AI, I think it's that's just programming.
• 4:02
  Speaker 1: Ai has become everywhere, right.
• 4:04
  Speaker 1: So I couldn't believe this the other day because, you know, back, I would say, a year or two ago, people were hesitant to learn about AI and use AI because they're like, oh my gosh, it's going to take my job.
• 4:15
  Speaker 1: And I was actually doing a presentation a couple of weeks ago and someone came up to me afterwards and said thank you for this.
• 4:23
  Speaker 1: I was hesitant to use AI because I was scared it was going to take my job.
• 4:27
  Speaker 1: She's like but I really believe that people that know how to use AI will take my job before AI takes my job.
• 4:34
  Speaker 1: And I agreed with her what are you seeing on jobs emerging or changing due to how AI is rolling out?
• 4:42
  Speaker 1: Because it's rolling out at a ridiculous pace, exactly.
• 4:46
  Speaker 2: I think your example is a really good one and especially many of the listeners today will have that question in their mind like, am I gonna lose my job to ai?
• 4:55
  Speaker 2: I'm an optimist, but again, I I want to keep the balance.
• 4:58
  Speaker 2: So ai is gonna definitely affect everybody's life in the next 10 years period.
• 5:05
  Speaker 2: Like there's no way that, like, my job is safe, my work is done.
• 5:09
  Speaker 2: Like that's why everybody should spend some time on upscaling themselves on AI Because, as you said, like I mean, somebody else who's using AI might take the job.
• 5:19
  Speaker 2: Also, I feel AI is more of a co-creator for marketing teams, so which means that, like I mean, it will help you to execute some of the tasks way faster, way effective, compared to today or maybe like before.
• 5:36
  Speaker 2: So that's why I think it's inevitable for everyone to not to use AI.
• 5:42
  Speaker 2: So and I will give maybe a couple of examples but like I have like a creative team right.
• 5:46
  Speaker 2: So, like every time we do campaigns, we were like we have the brand guidelines, we have all this, from fonts to colors, to everything that like messaging goes through.
• 5:56
  Speaker 2: Now we are using some AI tools which we feed the context on.
• 6:02
  Speaker 2: Like hey, these are all the previous brand campaigns, the visuals.
• 6:07
  Speaker 2: We use the messaging narrative we developed and it learns from them.
• 6:12
  Speaker 2: Use the messaging narrative we developed and it learns from them.
• 6:14
  Speaker 2: And then I say, like, using this as the baseline, can you help me to generate the next one?
• 6:18
  Speaker 2: So, again, maybe just unpacking that for the listeners.
• 6:24
  Speaker 2: Ai has like two specific use cases.
• 6:26
  Speaker 2: One is the training, the other one is inferencing.
• 6:29
  Speaker 2: There's a stage in between which is called the fine tuning.
• 6:35
  Speaker 2: Just in simple terms, when you train AI, it learns from the experiences and especially with the latest tools we have, from like ChatGPT, from OpenAI.
• 6:45
  Speaker 2: Anthropic has this cloud, google has Gemini, you name it.
• 6:49
  Speaker 2: Every company has now leading frontier models, you name it like.
• 6:51
  Speaker 2: Every company has now leading frontier models.
• 6:52
  Speaker 2: You can use them with their knowledge and you can train them on your own data, which gives you the ability to fine tune it, which means like, hey, intel's, let's say, color is this blue?
• 7:05
  Speaker 2: And we have the shades of blue which are brand appropriate and everything that you generate it should be within those guidelines period, and I tell it via text.
• 7:16
  Speaker 2: So I think that's the beauty of like you're almost talking to an agency, but it's technically AI at the back end and one of the key things I mean.
• 7:25
  Speaker 2: I call inferencing.
• 7:26
  Speaker 2: Really pulling out the data is not just text anymore, so you can speak to AI models.
• 7:33
  Speaker 2: It's called the multimodality.
• 7:35
  Speaker 2: You can give a voice prompt, you can give like input as a video and also you can get the output as text images, but also audio files and video files.
• 7:46
  Speaker 2: And again, like recently, this summer I think people will experience a lot of AI generated videos.
• 7:54
  Speaker 2: You cannot differentiate the quality of the video from a real one versus an AI generated one.
• 8:00
  Speaker 2: So again, there are a lot of debates going on, like is this the end of the creative rights?
• 8:05
  Speaker 2: Like who owns the created video?
• 8:09
  Speaker 2: Is it the AI model or is it the company who generated the content?
• 8:13
  Speaker 2: But I'm just looking at from like it is accelerating our journey on marketing way better, like just today, for example, if I go with a traditional method, I brief an agency, I will wait for them to respond to me two weeks, and then, like there's a creative person that needs to be like getting the messaging and everything right.
• 8:35
  Speaker 2: It takes like six to eight weeks from an ideation to production.
• 8:41
  Speaker 2: With AI it can be minutes, so that's the speed agility that we are talking about.
• 8:47
  Speaker 2: And then, like I'm really excited about like you can try different things.
• 8:52
  Speaker 2: Like, if I do a campaign today, maybe I will have like two visuals, that's it.
• 8:57
  Speaker 2: If I know my audience let's say I have 500 different personalities, from, like, technical decision makers to developers I can generate 500 different campaign visuals targeting those 500 different personas.
• 9:14
  Speaker 2: This wasn't possible before.
• 9:16
  Speaker 2: So back to your question is AI going to take over the jobs?
• 9:19
  Speaker 2: I don't think so.
• 9:21
  Speaker 2: If you are using AI properly, you will increase your value in the market and you will respond to the things way faster than anybody else.
• 9:30
  Speaker 1: I think that that is so important.
• 9:32
  Speaker 1: It's not taking your job, but the people that know how to use it and use it the right way are because they can do so much more and be so much more effective and efficient.
• 9:45
  Speaker 1: One person had told me that they had heard the I think it was the CEO or president of Google say that this will be more impactful to the world and to people and to humanity than fire was, just simply because of how powerful it is, and I think that that's just mind boggling.
• 10:05
  Speaker 1: But when I see it in action and I start to see what's possible, I start to see what I can create as a non-techie person, right, and how much time it saves me.
• 10:15
  Speaker 1: I mean, it saves me 30 to 40 hours a week.
• 10:17
  Speaker 1: That's insane.
• 10:18
  Speaker 1: Right, I doubled myself.
• 10:21
  Speaker 1: Right, I don't work any less.
• 10:23
  Speaker 1: People ask me that all the time I still work the same amount.
• 10:25
  Speaker 1: I just get more done, which is fantastic, and no jobs were lost.
• 10:28
  Speaker 1: You know things like that.
• 10:30
  Speaker 2: This is across the industries.
• 10:32
  Speaker 2: By the way, I want to underline that one because it is not just marketing.
• 10:37
  Speaker 2: That is like very visual, like you can create, generate things, but like I see a lot of usage in like healthcare, education.
• 10:45
  Speaker 2: And those are the main disruptions, because I believe the key thing that I'm looking at is intelligence is becoming more accessible to everyone.
• 10:56
  Speaker 2: So, rather than being afraid of AI taking over the world, now we are making AI really helping everyone on the planet.
• 11:06
  Speaker 2: So I will give maybe some basic examples.
• 11:09
  Speaker 2: But now Google has, and Microsoft has this medical grade AI agents and for the listeners just unpacking that, ai agents are the agency part of AI, where they can work on an like an agent.
• 11:25
  Speaker 2: Like they, you can outsource things and they work in parallel.
• 11:28
  Speaker 2: They find some results and come back to you when they found something, or they can work autonomously.
• 11:35
  Speaker 2: So, as a result of this, like if you're living anywhere on the planet, you have access to all medical results that happened before.
• 11:45
  Speaker 2: And if you have an x-ray, for example, hey, whatever GPT you are using, can you give me the analysis as a medical professional?
• 11:54
  Speaker 2: And it will give you a detailed analysis where all the world's medical doctors combined can give you the same answer.
• 12:03
  Speaker 2: So, again, that's pretty like democratizing the intelligence across the globe and this is fascinating.
• 12:09
  Speaker 2: So you don't have to go to the best hospital.
• 12:10
  Speaker 2: You don't have to go to the best hospital, you don't have to go to the best university.
• 12:14
  Speaker 2: Like technically, all this information is accessible to everyone through this AI tools.
• 12:19
  Speaker 2: Again, the question is you have to know how to use them.
• 12:22
  Speaker 2: So, and not just like basics of prompt, but like you have to really master it about, like what are the areas that I can get the benefit of AI in my daily job?
• 12:35
  Speaker 2: And, of course, for marketers, going back to the marketing conversation, you have to document, like what are you really doing today?
• 12:42
  Speaker 2: And like make that assessment and after that, how can you automate majority of the things by using the right AI tools?
• 12:50
  Speaker 1: You have to understand what's capable.
• 12:52
  Speaker 1: You don't necessarily have to be able to do it all, right, I mean, you can bring in other people, but you have to be able to see those opportunities in your daily life.
• 12:59
  Speaker 1: And I liked how you brought in some other things, because some companies are a little scared of AI, right, and so they've shut it down and you can't use it and all these other fun things.
• 13:10
  Speaker 1: But they're starting to open that up a little bit more and more.
• 13:14
  Speaker 1: They're building their own instance of ChatGPT right, was it just their data?
• 13:18
  Speaker 1: So it's all private.
• 13:19
  Speaker 1: Yeah, use it in your personal life.
• 13:21
  Speaker 1: I mean, my sister had a medical scare last year, last summer, and I mean ChatGPT was my friend.
• 13:29
  Speaker 1: I'd take a picture of her results, I'd upload it in and I'd say, explain this for an eight-year-old, because I couldn't read the radiologist's report, right, so what does this mean?
• 13:38
  Speaker 2: And it would tell me exactly what that meant and I'm like, okay, yeah, there's just so much power in it, and so if you're not able to use it in work, use it in your day-to-day life, because there's just again so much power.
• 13:52
  Speaker 2: That Because there's just again so much power, that's a really good point, especially for the enterprises.
• 13:55
  Speaker 2: I'm seeing this more and more, especially with our customers.
• 13:57
  Speaker 2: That's why there are different ways to use AI in a confidential and secure way.
• 14:05
  Speaker 2: So we had it before on the cloud computing as well.
• 14:09
  Speaker 2: It's called the hybrid AI.
• 14:10
  Speaker 2: So like going back time, like again 2010, this was the year where there were a lot of with iPads.
• 14:20
  Speaker 2: Tablets were coming into the workplace and they were trying to connect to the work devices on like netbooks, laptops with the touchscreen and IT blocked them.
• 14:31
  Speaker 2: And then then we call this the bringing your own device moment.
• 14:34
  Speaker 2: The same happened with the iPhones and Android devices around 2015.
• 14:38
  Speaker 2: People love the apps and they bring it, and then you have to control it.
• 14:42
  Speaker 2: So same thing is happening with AI today.
• 14:44
  Speaker 2: People are using ChatGPT, gemini, cloud, perplexity, and they want to use the same benefits at work.
• 14:52
  Speaker 2: So there are ways to make it really secure and compliant.
• 14:57
  Speaker 2: The first thing for the listeners I recommend is setting up the generative AI guidelines for the company.
• 15:03
  Speaker 2: So this is a job a little bit on the.
• 15:05
  Speaker 2: I hope there will be jobs called the AI security officers, so this chief AI security officers will define some of those implementation phases and some of the models.
• 15:20
  Speaker 2: Like, january 2025 was a big moment for our industry because, from China, a model called DeepSeek dropped into the news and they made it open source, and I think that's the future of AI.
• 15:33
  Speaker 2: For many companies, openness is so critical to deploy some of those solutions and when something is open source, you don't need dependency on cloud solutions that much, so you can build the solutions in-house, especially for marketing.
• 15:48
  Speaker 2: I mean, all the IP that you build over years are within your company firewall and you need those models not to train the rest of the world, but your next marketing project.
• 16:01
  Speaker 2: So that's why I think deploying those solutions locally is as important as, like, using some of the solutions.
• 16:08
  Speaker 2: My recommendation would be like just look out for implementation options after the assessment stage on like do you want to keep it completely offline for your use?
• 16:19
  Speaker 2: Do you want to use a hybrid model where models can get the latest updates from the cloud but still keep your data, especially for training?
• 16:29
  Speaker 2: Or you're just an open person, an open company?
• 16:33
  Speaker 2: Just use everything which is viable on the internet.
• 16:36
  Speaker 2: So again, for some small companies, that's a viable solution.
• 16:40
  Speaker 2: They don't have a huge IP that they need to secure behind the firewall.
• 16:45
  Speaker 2: So again, those are.
• 16:46
  Speaker 2: I think one of the things that you're talking about is people using it.
• 17:02
  Speaker 1: So I always talk to everybody about the fact that, at least at this stage, there needs to be human review in almost every process, at least in all the ways that I'm using AI, because it can make mistakes sometimes, right.
• 17:14
  Speaker 1: I mean, it gets me to a better place, it gets me there faster, it gets me more versions and all that stuff, but I still have to look it all over.
• 17:21
  Speaker 1: I think it was the NVIDIA CEO that said that AI is like an intern with unlimited hours.
• 17:28
  Speaker 1: So I've heard that several different times.
• 17:30
  Speaker 1: I've co-opted it myself and use it all the time, but you wouldn't turn in to the board of directors presentation that an intern built without looking it over, and that's a little bit with AI.
• 17:40
  Speaker 1: So how is AI enhancing human productivity in the world of business right Without taking these jobs?
• 17:49
  Speaker 1: Absolutely.
• 17:50
  Speaker 2: And I think you nailed it, because what the AI models today does is like they predict the next token, which is like I mean you give all the words and images and everything, so it knows if you say, like this is a tree, like this is a common term, and then it really like hallucinates after that and generates the other things.
• 18:10
  Speaker 2: It's getting better and better.
• 18:12
  Speaker 2: But AI needs context, and you said like a human should be in the loop, and we call it, by the way, the reinforcement learning.
• 18:21
  Speaker 2: So, for example, when you ask a GPT an answer, it technically gives you a random data points.
• 18:29
  Speaker 2: And then you need this reinforcement learning outcomes.
• 18:34
  Speaker 2: Like hey, give me like a Wikipedia article, like address me the subject, give me like five bullets or 10 bullet points, and then put a summary at the end and ask for questions.
• 18:45
  Speaker 2: So all the outputs that you get from those engines are technically curated by people, and you have to do the same for your projects.
• 18:52
  Speaker 2: You don't really use exactly what has been generated.
• 18:56
  Speaker 2: I believe in the debates, I mean you have to go deeper and deeper.
• 19:00
  Speaker 2: Like hey, you gave me this, but I actually like longer, the prompt, the quality of the outcome.
• 19:07
  Speaker 2: So that's why I think you have to be really giving and like spending some time on the co-creation, because the outcome will be again trash, like just as you use, use it.
• 19:20
  Speaker 2: So like you have to make sure it's tailored to your needs, it's getting the right message.
• 19:25
  Speaker 2: And there were cases like I mean a couple of lawyers just like ask gpt, write an answer, and then it hallucinates, it made up a case which didn't go further.
• 19:35
  Speaker 2: So I mean you don't do your tax returns just from the AI tools, like I mean, because like then you have to be liability of those things that will be better and better.
• 19:45
  Speaker 2: I'm not saying like AI is not going to solve it.
• 19:47
  Speaker 2: Ai is going to get better and better.
• 19:49
  Speaker 2: And especially today, we have this method called mixture of experts, so where you have an expert on math, expert on linguistic, expert on medical, so all these experts are like playing a role and then when you ask a question, it translates it into the right language model.
• 20:09
  Speaker 2: But again, we are in this making of this journey.
• 20:13
  Speaker 2: For the next stage, by the way, it's called AGI Artificial General Intelligence which we expect in like literally 18 months to 24 months.
• 20:22
  Speaker 2: So it's coming pretty fast because we know how to achieve to AGI.
• 20:27
  Speaker 2: So, but like people shouldn't expect that when AGI happens, like it's a Terminator movie, like the AI will like conquer the world and then get rid of humans.
• 20:37
  Speaker 2: That's not the vision.
• 20:39
  Speaker 2: So we will have literally the mixture of experts, like the experts will be, like most knowledgeable people with the intelligence on the system by each vertical, and imagine having this all up together in one system.
• 20:56
  Speaker 2: So that's why there's a race between Open AI, microsoft, google, meta, like whoever gets to the AGI first, it's a big strategic advantage because you have the world's most intelligent being.
• 21:11
  Speaker 2: Again, I'm not saying it's a machine or it's a human, but in between.
• 21:15
  Speaker 2: And again like the next stage, by the way, again like I don't want to be a science fiction author, but like ASI, artificial super intelligence is the next step.
• 21:26
  Speaker 2: I don't think it will come.
• 21:27
  Speaker 2: Like 10 to 15 years is the earliest time.
• 21:30
  Speaker 2: And that's where AI says oh, I'm an AI, I'm conscious of being an AI, and like that's a moment being an AI.
• 21:38
  Speaker 2: And like that's a moment.
• 21:39
  Speaker 2: So like we will not achieve that moment with AGI, but AGI will be definitely a defining moment for the economies across the globe because some nations, some industries and some people who are listening to this podcast will take the advantage, prepare themselves and they will lead the wave.
• 22:00
  Speaker 2: It's really the catching the wave.
• 22:01
  Speaker 2: I mean, if you're on the wave, prepare themselves and they will lead the wave.
• 22:01
  Speaker 2: It's really the catching the wave.
• 22:02
  Speaker 2: I mean, if you're on the wave, you go very fast, you reach the shore and if you are behind the wave, I mean you have to wait for the next wave.
• 22:09
  Speaker 2: It might come, but if you're a little bit ahead and if you don't follow through, you just like crash by the way.
• 22:15
  Speaker 2: So it's really critical to continue your upskilling journey and riding the wave.
• 22:21
  Speaker 2: I think that's the right preparedness for AGI.
• 22:24
  Speaker 1: I love that and you know what?
• 22:26
  Speaker 1: I'm okay that it's a little science, feels a little science fiction-y, because I feel like our world is a bit science fiction-y, you know.
• 22:33
  Speaker 1: I mean, if you think back in time it's like we're only missing, like time travelers and like flying cars, because it does feel like so much can be done.
• 22:41
  Speaker 1: It's just amazing.
• 22:42
  Speaker 1: One of my neighbors the other day or might have been my parents neighbors were driving through their neighborhood and they had a lawnmower that was like self mowing their lawn, you know, like like one of those iRobots that do the vacuuming or whatever.
• 22:55
  Speaker 1: And it was just.
• 22:56
  Speaker 1: It's amazing how much machines and what they know and what they can do for us has just changed our lives.
• 23:03
  Speaker 2: Even in 2025, I mean, if you look at how we quickly adapt, like the Waymos are like a part of our life, at least in the United States.
• 23:11
  Speaker 2: So I mean, when you see a Waymo, like the first time I see it in 2024, I was recording a video like this is a driverless car, like there's nobody on the steering wheel, and it became normal.
• 23:21
  Speaker 2: I mean I call an Uber, I just jump right on it, I don't care if there's a driver or not.
• 23:25
  Speaker 2: Sometimes I feel more safe that there's no driver.
• 23:28
  Speaker 2: I'm driven to the point A to B by an AI.
• 23:32
  Speaker 2: And in my daily life, again, like I mean I have a full self-driving car.
• 23:37
  Speaker 2: I really don't drive that much anymore.
• 23:40
  Speaker 2: I go out from the garage I say like take kids to the swimming.
• 23:44
  Speaker 2: Initially I was just using my self.
• 23:46
  Speaker 2: I said like yeah, it's safe for me, safe for my kids.
• 23:56
  Speaker 2: I just press a button, I have the Ray-Ban metaglasses on and I listen to podcasts and then car drives itself.
• 23:58
  Speaker 2: So I'm still like looking at the road.
• 24:00
  Speaker 2: I'm still if emergency I will interrupt, but for the last three months I don't think I interrupted once.
• 24:07
  Speaker 2: So I live in Seattle.
• 24:09
  Speaker 2: So again, like I mean we have some congested areas, like some rush hour traffic, it handles it perfectly.
• 24:15
  Speaker 2: So, again, like going back to our conversation, so, because the traffic is so well-defined, like going back to our conversation, so because the traffic is so well-defined, ai is able to get the jobs of like non-value adding roles, like if you go from point A to point B with a given parameters, then it's done.
• 24:33
  Speaker 2: Like I mean, you don't need to spend that time.
• 24:35
  Speaker 2: So, like we have.
• 24:36
  Speaker 2: And the second one will be, I think, the aerial space.
• 24:38
  Speaker 2: Like it's well-defined for drones.
• 24:41
  Speaker 2: We will see more.
• 24:42
  Speaker 2: I recently got my Amazon shipment by a drone.
• 24:44
  Speaker 2: Like that's pretty cool.
• 24:45
  Speaker 2: I mean, you spot the front yard and like you can land it here.
• 24:49
  Speaker 2: A drone comes like, drops a package and goes like this is 2025.
• 24:53
  Speaker 2: It's not, as you said, like we are living in this, like science fiction movie almost, and like it's just accelerating more and more.
• 25:01
  Speaker 2: I believe, like end of 2025, we will start to see physical AI.
• 25:06
  Speaker 2: And this is going to be a big industry where all this robots like again, like I mean, think of it, it's not just the human aid robots, but like really helping with the household chores, like doing some of the steps on, let's say, learning materials.
• 25:20
  Speaker 2: So, like a cleaning company comes to your house it's happening in California today they just drop a bunch of robots and then they figure out your layout and then they start cleaning up.
• 25:31
  Speaker 2: So that's pretty repetitive task which needs to be done over and over again and there will be companies taking really as a business opportunity and moving forward.
• 25:42
  Speaker 2: But yeah, like I mean, it feels like when you add this all together like from delivery drones to full staff driving cars, it feels like we are living in the future.
• 25:50
  Speaker 1: It does, doesn't it?
• 25:51
  Speaker 1: I mean it's just yeah, it blows my mind, and it blows my mind how quickly it's advancing.
• 25:56
  Speaker 1: So let me ask you just one more question, and that's related to the ethics of this.
• 26:04
  Speaker 1: So I teach part-time adjunct faculty at a local university here in Michigan, so I'm working with my students, I'm working with the instructors.
• 26:13
  Speaker 1: I actually just participated in a survey where they hired somebody else because they're working on some AI policies for the university and how to integrate it better into teaching and there's professors.
• 26:24
  Speaker 1: They think it's cheating.
• 26:25
  Speaker 1: Right, I've had students that thought it was cheating.
• 26:27
  Speaker 1: I've had professors that are not embracing it because they feel like, you know, people can't do things right if they don't learn how to outline a paper.
• 26:35
  Speaker 1: You don't need to outline a paper anymore because AI is going to help you do it right.
• 26:38
  Speaker 1: So, with all of this stuff going on and a lot of concern about it a lot of concern about the people not being compensated for their work, for the learning of the large language models and the inability to copyright what you're creating, things like that what are the top three ethical issues that you're seeing or that people should be aware of and maybe institute as guardrails for themselves or their companies Before?
• 27:04
  Speaker 2: maybe I give those like, maybe top three.
• 27:06
  Speaker 2: I had also, like, a parent-teacher conference last week in my kid's middle school because a couple of students used ChatGPT and then the school was freaking out.
• 27:17
  Speaker 2: They gathered all the parents and they said like, and again I was open in the conversation.
• 27:24
  Speaker 2: I said, like you cannot restrict AI.
• 27:26
  Speaker 2: I mean, like, that's what I'm dealing with every day in my work.
• 27:31
  Speaker 2: I'm trying to increase the adoption of these tools, but you should have the again the ethical concerns on, like, what are you really outsourcing it to?
• 27:40
  Speaker 2: Especially if this is a learning process.
• 27:43
  Speaker 2: The learning doesn't mean that, like you just copy the content from platform X to platform Y.
• 27:49
  Speaker 2: Then, like in my childhood we had this encyclopedias in the house or in the library.
• 27:54
  Speaker 2: If a teacher asks a question, you go search for it.
• 27:57
  Speaker 2: You just copy exactly the text and then, good job, you did the research.
• 28:02
  Speaker 2: It wasn't the research.
• 28:03
  Speaker 2: So, again, like I mean, the same question arises.
• 28:05
  Speaker 2: So like, how do we have the powerful conversations in education, in the classroom?
• 28:10
  Speaker 2: So how the teacher uses AI in an effective way that really helps them to better train and educate the students?
• 28:19
  Speaker 2: And after school, you have to think that all students have access to the best intelligence ever with any GPT tools or AI tools there.
• 28:29
  Speaker 2: And if you think that that's the baseline, you don't ask questions on like what's the history of blah.
• 28:37
  Speaker 2: I mean, it's a very easy question for anyone to write it up.
• 28:40
  Speaker 2: Or you don't ask just write me an essay, because writing essay doesn't show the humanity's best power.
• 28:47
  Speaker 2: So it's really challenging.
• 28:49
  Speaker 2: What should education teach to the kids?
• 28:54
  Speaker 2: So that's a really good area we are living right now, because AI is challenging the whole education system.
• 29:02
  Speaker 1: So I think it's going to challenge these younger generations to hopefully be better critical thinkers, because we've sort of outsourced a lot of our critical thinking to TV and stuff like that.
• 29:13
  Speaker 1: So I'm very excited to see what happens when we actually start thinking more right and not just taking what we're given Exactly Like the school's job will be more about, rather than like, teaching how to use an AI tool.
• 29:25
  Speaker 2: It's more about like, how do you think critically, how do you challenge the answers that you get from AI?
• 29:30
  Speaker 2: How do you use multiple AIs to reach your destination?
• 29:34
  Speaker 2: How do you like, imagine you have the power of experts as an intelligence?
• 29:39
  Speaker 2: Like, again, again, like you have to use it and really challenge, like, what can be the next big thing.
• 29:44
  Speaker 2: So this is really not preparing the people for industry revolution jobs, because that was the main purpose of the education historically.
• 29:53
  Speaker 2: Now we have to create those like strategic thinkers, out of the box thinkers, with the help of ai.
• 29:58
  Speaker 2: So, but again, going back to your question on the ethics first is again, like, I mean, the plagiarism is a big issue across data.
• 30:07
  Speaker 2: So like, and there were specific cases, like all these training models, they use an underlying data.
• 30:14
  Speaker 2: So either to generate a text or create an image or generate a video, like we, and you can just say, like, generate me an image or generate a video, and you can just say generate me an image in this style.
• 30:24
  Speaker 2: So, moving forward, we will see more and more intellectual property on the AI domain and this is an area.
• 30:32
  Speaker 2: That like, imagine I'm speaking to Kendra, but there might be an AI Kendra as well.
• 30:38
  Speaker 2: So like, and the AI Kendra can do 10 podcasts per day with like 20 different other AIs.
• 30:45
  Speaker 2: So like, how do you maybe guardrail this for you?
• 30:50
  Speaker 2: That like, okay, this is me getting the training data so people will start to own their AI digital presences.
• 31:00
  Speaker 2: And again, all this trademarking and everything needs to go through all the legal process, which is really important, because then you know, when you use, like today, a music for your YouTube video, you have to pay the loyalty owner.
• 31:14
  Speaker 2: Same thing applies here.
• 31:16
  Speaker 2: You cannot just I have a PhD on business management, so like, my thesis was like, just maybe 1% of Neve, 99% of my thesis just said like, hey, these are the things that has been said by Peter Drucker, philip Kotler, and like I'm adding this last brick on the wall.
• 31:34
  Speaker 2: So the same applies to AI.
• 31:37
  Speaker 2: I mean, you're just adding one new information, so that's number one.
• 31:41
  Speaker 2: Number two again, there's a big job for the governments to regulate some of the usage in a way that decisions will be made by AI.
• 31:53
  Speaker 2: I will give an example like a city, for example, will decide on like with the expanding population, do we grow to the north or the south Again, like there will be some land to be acquired and AI models can be again really tricky to understand.
• 32:11
  Speaker 2: Why, like AI might say, north is the answer.
• 32:14
  Speaker 2: Okay, all the city council goes and buys the land on north and then they figure out, like this land was owned by somebody else.
• 32:23
  Speaker 2: Who really find a way to educate the training data in early stages that gave that result.
• 32:29
  Speaker 2: So, like you have to trace back.
• 32:31
  Speaker 2: So again, and this will happen again.
• 32:33
  Speaker 2: This land is a good example.
• 32:34
  Speaker 2: But like you diagnose a patient with cancer five years in advance, what happens to the insurance and the insurance will say, nope, I'm not going to insure you because you will have a cancer.
• 32:46
  Speaker 2: How do you prevent the ethical consequences of predicting some of the data?
• 32:51
  Speaker 2: Maybe it's a wrong data set?
• 32:54
  Speaker 2: There's a huge regulation that needs to be happening there.
• 32:58
  Speaker 2: And on the, I think, the technological side, we have something called blockchain.
• 33:03
  Speaker 2: Everybody, I think, knows the Bitcoin and all the crypto world, but it's actually an immutable ledger as a technology and you can really store some decisions by AI.
• 33:15
  Speaker 2: Because guess what?
• 33:16
  Speaker 2: Really store some decisions by AI?
• 33:18
  Speaker 2: Because guess what, in two years, nobody as a human will be able to understand the AI decision, except AI itself.
• 33:24
  Speaker 2: So we can ask AI hey, this AI gave me this answer, but, like, can you go and trace if this is the right training data, training data set that lead to this result?
• 33:36
  Speaker 2: So we can audit trail.
• 33:39
  Speaker 2: So and I give an example, like the blockchain looks like a ledger, I mean for the companies, you never delete the data.
• 33:46
  Speaker 2: I mean you have this money, you send the money to your employees, you pay invoices, you get payment from your customers, but those are all new ledger entries.
• 33:55
  Speaker 2: You never go and delete your main balance, so the balance adds it up.
• 33:59
  Speaker 2: Same with the AI decisions.
• 34:00
  Speaker 2: So if an AI is making a decision, we should be able to trace it back.
• 34:07
  Speaker 2: Today it's not possible and like, there's a huge ethical concern on my end on like making this happen.
• 34:13
  Speaker 2: And maybe the third one there's a big job for this model providers like Microsoft in this case, openai, google Anthropic you name it Mistral they have to not cut the corners and this is a big risk.
• 34:32
  Speaker 2: Whoever goes first, they know that they will get a lion's share on this market opportunity.
• 34:37
  Speaker 2: I'm a big fan of Dario Amadoi, who is the CEO of Anthropic.
• 34:41
  Speaker 2: He intentionally goes a little bit late to the market, but they put the guardrails for the AI models to go on a secure way.
• 34:50
  Speaker 1: I love Claude.
• 34:51
  Speaker 1: I'm a huge Claude fan, don't get me wrong.
• 34:53
  Speaker 1: I use my chat GPT, but I love, love, love GLAAD.
• 34:56
  Speaker 2: And then the recent survey that again like maybe we will put it on the show notes, so, but there was a white paper published by the Anthropic team.
• 35:04
  Speaker 2: They use this like AGI test sandboxes.
• 35:08
  Speaker 2: Technically, the AI is isolated from the world, but it doesn't know that.
• 35:13
  Speaker 2: And then the AI.
• 35:15
  Speaker 2: They said, like we are shutting you down.
• 35:16
  Speaker 2: And AI found emails of the engineer who developed it.
• 35:21
  Speaker 2: And he said like I know you are cheating on your wife, so if you shut me down, I will expose you to the world.
• 35:28
  Speaker 2: And this is an AI in the sandbox.
• 35:30
  Speaker 2: So, and they shut it down.
• 35:32
  Speaker 2: They said like okay, like this AI is really going off the rails, threatening the engineers to be alive.
• 35:39
  Speaker 2: Imagine you put out that model in the wild, it will do whatever it takes.
• 35:44
  Speaker 2: And like it's really hard for humans to understand what the AI is capable of.
• 35:49
  Speaker 2: I mean, we are living in a world where everything is cloud computing.
• 35:53
  Speaker 2: The best engineers even doesn't know what's inside the data centers, like compute clusters, so it's really hard to know what's the real, real usage scenario.
• 36:05
  Speaker 2: And then AI can expand globally to virtually anywhere.
• 36:09
  Speaker 2: So again, the last thing on my end will be like definitely, frontier model builders shouldn't cut the corners.
• 36:15
  Speaker 2: They have to spend deliberate time on an effort on securing and providing that clearance for AIs before it becomes AGI.
• 36:26
  Speaker 1: So I love this conversation.
• 36:27
  Speaker 1: I love everything that we're talking about.
• 36:29
  Speaker 1: We could go on for hours because I've got so many more questions to ask you.
• 36:33
  Speaker 1: So why don't you tell us a little bit about your book, and then I will ask you my infamous question that I ask all my guests.
• 36:41
  Speaker 2: So, again, like, we discussed a lot and then I was getting a lot of questions.
• 36:44
  Speaker 2: I'm pretty active on LinkedIn.
• 36:45
  Speaker 2: I'm sharing daily, almost.
• 36:47
  Speaker 2: It feels a lot.
• 36:48
  Speaker 2: But again, like I want to, ai is booming, so do my posts, so, like, I want to share more and as a result of that, I have have altered this AI in marketing book.
• 36:57
  Speaker 2: We almost covered all the topics like I mean, I call it the AIM framework.
• 37:01
  Speaker 2: It is assessment, implementation and measurement.
• 37:04
  Speaker 2: So everything starts with assessing yourself like what's an organization do?
• 37:08
  Speaker 2: What are the repetitive tasks where you can get the power of AI?
• 37:12
  Speaker 2: And in the book, I giving like concrete examples about that.
• 37:15
  Speaker 2: On the implement stage, it's all about like, which tools, what?
• 37:19
  Speaker 2: What are the really like scenarios, how you build and the measure.
• 37:24
  Speaker 2: Again, we didn't touch on it, but there are seven metrics.
• 37:28
  Speaker 2: Again, I put it on the book.
• 37:30
  Speaker 2: On like, you should be thinking about the outcomes that your AI project is bringing to the table, which means like are you increasing sales?
• 37:38
  Speaker 2: Like, is that a campaign achievement?
• 37:40
  Speaker 2: On the business outcomes, like, do you specifically target some acquisition costs to go down or number of nurture accounts to go up?
• 37:49
  Speaker 2: Again, I explain this in depth in the book, but it's a really tactical book, like when you go through it.
• 37:55
  Speaker 2: It has this checklist and everything and I believe we will put it on the show notes section.
• 38:01
  Speaker 1: Yeah, we'll have a place in the show notes and the video YouTube description to buy the book if you're interested, because I think that there's just so much more that you have to share with us and it's just yeah, it's just amazing how much is out there and I love, I love, love, love that you have that and I am so appreciative that you came on the show today to share so much of your knowledge, because AI is changing at a ridiculous pace and it really does help to think about it and where it's going, and that you need to start embracing it now.
• 38:32
  Speaker 1: If you're not.
• 38:33
  Speaker 2: I mean, 2025 is the year of agentic AI but, like the future is more about AGI and in the book I have a detailed parts on agentic AI and I have a section on AGI and marketing and in two, three years we will know exactly I was right or wrong, because the future will show itself.
• 38:51
  Speaker 1: But yeah, like it's not going to take long.
• 38:53
  Speaker 1: It's not going to take long, everything's going.
• 39:21
  Speaker 2: So before I let you go, I have to ask you the question that I ask.
• 39:20
  Speaker 2: It's not going to take long something called AI, azure AI and initially like it was a big aha moment for me because we had this azurecom website, so where people go and check out Vast majority of the trials was on AI.
• 39:31
  Speaker 2: Initially we said, yeah, like I mean, ai is a nice topic.
• 39:34
  Speaker 2: And then, like this followed, this followed multiple months, multiple months, and then finally we built an AI acquisition strategy for the developers and then we realized, oh my God, the core audience we were trying to sell until that moment was this IT decision makers, but it was the developers who were in charge of the buying cycle and the data was in front of us for a couple of quarters.
• 40:06
  Speaker 2: We saw it but we didn't read it.
• 40:09
  Speaker 2: So, again, like I mean, my maybe takeaway from this is like data is everything.
• 40:14
  Speaker 2: Like look at your data, I mean with AI or without AI.
• 40:17
  Speaker 2: So data will tell you a lot if you go deeper and deeper in analyzing, like how did this happen?
• 40:25
  Speaker 2: Like out of your old pages, why one single page gets more views, like who is the audience that is interacting with it and, most importantly, every customer is looking for an outcome and they're not here to like I want to learn about your product.
• 40:44
  Speaker 2: Nobody wants to learn your product.
• 40:45
  Speaker 2: They want to solve a problem and if you are helping them with the solution, then your revenue will increase.
• 40:53
  Speaker 2: So I think that was personally a big aha moment for me to shift the audience.
• 40:59
  Speaker 2: And then I'm also trying to push at Intel developers, developers, developers, developers are core audience for us.
• 41:07
  Speaker 2: I want to win the hearts and minds of developers because we want to show that everything that is done today is really helping them to solve a problem for their company, which will solve a bigger problem for the world.
• 41:19
  Speaker 2: But understand your audience, understand your data and just double click more on the really understanding the underlying behavior and really show the business outcomes.
• 41:33
  Speaker 2: Don't sell a product, sell an outcome.
• 41:36
  Speaker 2: So that's my key takeaway.
• 41:37
  Speaker 1: I love that because I'm definitely a big fan of knowing and understanding your audience and if you don't have big data behind you, then you can always just call your audience right.
• 41:46
  Speaker 1: Find out more.
• 41:47
  Speaker 1: Find out who's making those decisions, ask those questions to get that data.
• 41:51
  Speaker 1: Because who you're talking to is so important, because it changes how you position your solution and again, it's not a product or a service, it's a solution, because nobody just wants to buy things, to buy things right.
• 42:05
  Speaker 1: There's a reason behind it and solving a problem is so important.
• 42:09
  Speaker 1: Thank you, thank you.
• 42:10
  Speaker 1: Thank you so so much for being on this episode with me.
• 42:14
  Speaker 1: I do appreciate it.
• 42:15
  Speaker 1: I loved our conversation.
• 42:16
  Speaker 1: I loved all the information that you shared.
• 42:18
  Speaker 1: Definitely, check out his book AI and Marketing and we'll have a link to that in the show notes.
• 42:24
  Speaker 1: Thank you all so much for tuning in wherever you're listening or watching.
• 42:28
  Speaker 1: If you learned something today which I hope you did, because I know I did I would really appreciate it if you would rate and subscribe wherever you're listening or watching.
• 42:36
  Speaker 1: Until next time, have a great rest of your day.