The PharmaBrands Podcast
The Canadian healthcare marketing industry is full of personal, impactful, and fascinating stories. The PharmaBrands Podcast is proud to celebrate these stories from people, brands, organizations and businesses who are making a difference.
For more PharmaBrands content and experiences visit PharmaBrands.ca
The PharmaBrands Podcast
Karim Vassanji, Head of Digital Strategy at Bayer on Frameworks, Consensus Building and Impact.
There is an old saying that, “When all you have is a hammer, everything looks like a nail.” Today that could be, “If you have AI, everything looks like it can be fixed with AI.” In this episode of the PharmaBrands podcast, Karim Vassanji, discusses how discipline, curiosity and consensus building are fundamental to the success of any digital transformation effort.
Links mentioned on this episode: Super Human AI Newsletter, The AI Daily Podcast
Our host is Neil Follett, Co-Founder of PharmaBrands and our Producer is Darryl Webster with Chess Originals.
Karim, thank you for joining me on this very sunny summer afternoon.
Speaker 2:My pleasure to be here.
Speaker 1:We've got introduced because you were on stage at the recent Age of AI conference, but, unlike a lot of the guests, this is the first time that we'll be talking, so I will be learning about you and your ideas in real time, as our guests do, so I'm really excited to have this conversation.
Speaker 2:I'm really excited to have this conversation. I'm really excited to talk to you. It's always interesting to hear about you before actually getting a chance to talk to you, so I think this will be an interesting one.
Speaker 1:You know what I'll start with. The one of these things is not like the other one game. What rule on your LinkedIn page, do you think, jumped out at me? That felt like a little bit of an outlier.
Speaker 2:Maybe my education.
Speaker 1:Oh, could be. Well, this is probably tied together, but it was your associate dentist role. Yeah, you started out in a very different spot, so maybe just kind of talk about that a little bit and then we'll jump into all the digital and data stuff that you've done.
Speaker 2:Of course, yeah. So as a student I was always fascinated by healthcare and my dream was to be a doctor for a very long time and luck had it that I didn't get into med school in Portugal, but I did get into dentistry and the program in Portugal at the time without dating myself too too hard was basically the same for the first three of the six years. So dentistry and medicine were the same program. And I thought you know, let me, let me learn the basics and then maybe on the third year I'll consider switching. Well, things didn't pan out that way and I continue with dentistry.
Speaker 2:I found some passion in what I was doing and it wasn't until after graduating, getting a job. I actually got a job in London, uk. So I got to experience dentistry from a very different perspective than the one I had in Portugal. And that's when I discovered that, while I loved seeing patients and talking to people and helping them, that the business side of healthcare was really what was driving me. And it wasn't until I started looking at the books for the clinic I had in London I was associate there and starting to see what else could we do? You know, do we have a website that allows people to book their appointments, like, do they have to call us all the time? And even at that time I didn't connect the dots. So I thought maybe this is just me being curious, that's all.
Speaker 2:But then I decided to leave the UK, as great as it is for many, many people. I left a very sunny place warm and sunny to a place where it rains a lot, and I just couldn't handle it. Fair enough, I got a shock. Okay, it was shock therapy. I landed in London just a few days before the 2008 financial meltdown took place and it gave me a very different taste of what the UK is today. So I ended up returning to Portugal after about a year, or just under a year, and then I decided to educate myself on the business side of healthcare. And so when you look at my LinkedIn profile and you see associate dentist, that was the beginning of a very non-traditional journey into healthcare.
Speaker 1:It looks like you switched from being a practitioner to a series of roles that had data in there somewhere, be it in the title or in the description of what you did. Is that fair? Did you end up sort of going into the analytics side of the business, kind of post-dentistry?
Speaker 2:Yeah, when I was looking into switching my career, it was around the same time as I moved to Canada, and at the time as a newcomer. There are some options to consider, but as a healthcare professional, the number of options are perhaps not as wide. And I was trying to look at what do I know how to do, what did I study coming into here? And if I had to mix and match the two, what could I do? And while my mind wasn't thinking, data data became a presence in my career.
Speaker 2:So my first role in Canada was through a very small consulting firm where one of the partners was also a healthcare professional, but a Canadian physician who was doing EMR research, who was doing EMR research, so he would go into clinics all across Canada primary care predominantly and mine information to help improve patient outcomes. They'll help doctors better manage their patients and I at the time was looking at this from a consulting perspective in terms of practice improvement for the lack of a better word. I didn't focus on the data side of things. Data was just a means to an end, but absolutely, if I look back, data was sort of this constant that has always been there.
Speaker 1:Which is such an interesting to go from and we'll kind of step on the other stepping stones on the way to where you, to where you are now. But, like you know, to go from sort of being a practitioner and then, in a lot of ways, kind of pulling back the curtains on. You know how you know clinics operate and the the business of of healthcare, the business of healthcare, part of which is how do we reduce friction for patients and improve care and all that other stuff. But there's a lot of this is a business. That must have been a really interesting way to view two sides of the coin. And I have to imagine, but I will ask did those years of getting deeper into the insights of running a clinic, have there been moments that have carried on through your other roles where you feel like that gave you just an interesting perspective that others might not have? There's a level of insight there that I think not a ton of people have.
Speaker 2:It's interesting you ask that question. The answer is yes, a resounding yes, I think, that perspective on how to manage a clinic, irrespective of what type of clinic you're managing. It involves patient care. It involves communication, clear communication. It involves knowing how to run a P&L right. You have a business that needs to profit, but you have your ethics behind it that don't go away just because you changed the line of business. So that helped me to as I started my career in Canada, helped me to speak the language of healthcare professionals, while also speaking the language of those who are trying to help them improve on their business, and I was kind of the middleman in a lot of communication.
Speaker 1:It's interesting because I think that the day-to-day realities of, let's just say, a GP in Canada, there's a lot of friction in that practitioner's day and I think that, not for a lack of empathy but maybe just for a simple lack of insight, I think there are a lot of brands or brand managers who want to serve that practitioner or market to or sell to or engage with that practitioner in a certain way that is just fundamentally at odds with the day-to-day operational realities of that person's kind of like lived experience as a practitioner. And so if you can't connect, you're not going to be able to communicate it. So you know again, just sort of going back to how interesting that must be, to just sort of keep some of those aha moments that I'm sure you got in those days in the back of your head as you're thinking about data, digital, how that impacts practice, how it impacts marketing. There is a rubber, hits the road at some point, and that's often in a very busy clinic.
Speaker 2:Absolutely, clinic Absolutely. And I love that you bring in the sort of the clash between what some brand managers and product managers and sales reps, et cetera, et cetera what they want to do and what they have to do from a business perspective, and the dynamics of how physicians see their day and run their day, and that is something that I acquired over time. Right, my experience as a healthcare professional was similar in many ways to what other healthcare professionals in Canada go through, but there's a lot of nuance that I learned in my first interactions in my consulting days and that has served me well to also bring in perspective to my colleagues in the various roles that I've had over the years and helps to level set the things we need to do with the ways in which we may want to consider doing.
Speaker 1:That was one of my takeaways from your time on stage at Age of AI. Is this marriage between the vision and the practical reality like consensus building, and how do we get there? I'm going to dig into that in a sec. But why don't we sort of skip ahead and say lots of interesting stuff, roles that have data and multi-channel and digital innovation in them, and customer engagement, and you're now head of digital strategy at Bayer. I know what all of those words mean. I'm not certain that I know what they mean at Bayer. So what does the head of digital strategy do at Bayer?
Speaker 2:Well, it is an interesting and evolving definition. And evolving definition as I'm new-ish to Bayer. It's been about nine months since I joined and the first few months of my time at Bayer has been to understand what does this role need to achieve and help the company achieve in Canada? And part of what I do is to map out the path of least resistance to how we engage with customers. If you think of almost like what an omni-channel manager would do in most companies, but not think of only the operations. Think about the strategy when do we want the company to go and how do we set the foundation to get there? Want the company to go and how do we set the foundation to get there?
Speaker 2:Luckily, I've joined a team of extremely competent people, but at a time of some pretty dramatic change. So I took advantage of that momentum and change to just help bring things together and help build the vision of how we engage. So that's one of the things that I do. It's not thinking about digital only I always wear the digital hat regardless but a lot of it is to determine what does good look like for a specific type of brand or for a specific type of customer or for a specific type of team, because not all things are created equally. The other part of what a digital strategist or head of digital strategy does at Bayer in Canada has a lot to do with the upskilling of digital competencies, which today always relate somehow to generative AI.
Speaker 2:And what I mean by this is not to say, oh, people don't know what they're doing and I'm going to show them the way.
Speaker 2:Not at all.
Speaker 2:In many cases, I don't know what I'm doing, but I'm surrounded myself by people who can help me figure it out. It just happens that that is my mandate, and so what I need to do is to educate myself, play with things, understand how things work, translate them to how does this benefit the business? So, if you look at the traditional way in which perhaps many companies have tried to implement technology is to say, oh, here's a new piece of technology, use it. And then you hear crickets because people don't know what to do with it. And my role and part of what I bring to this team is to understand the technology and understand the business and build the parallels where they exist and where I see them, but also talk to other people to see what their perspectives are and when things make sense for everyone, turn that into a framework, and I know these are a lot of buzzwords, but that's essentially what I do is to set the tone, set the ways to look at it, build guardrails with other partners I have at the company and empower people.
Speaker 1:Three things in what you just said jumped out at me. One is when things make sense for everyone. I'm going to ask a question about that. You mentioned part of what you do is educate yourself. I'm quite interested in how you do that. I'm going to ask a question about that. And then you started with. Digital is a lot about Gen AI right now. So I'm actually going to go backwards and I'm going to start with the make sense for everyone.
Speaker 1:Now I appreciate that it can't actually make sense for everyone.
Speaker 1:I feel like there's a serious kind of like Goldilocks situation happening when it comes to AI. There's, I think, folks or brands or situations that are demanding velocity because they can they see or they can sense or they can, you know, measure the impact of moving to higher AI adoption. I think on the other end of the scale, you've got individuals or brands or contexts where there's a real slowdown. It's not necessarily right for us right now, it's not right for the brand. There's, you know, maybe safety or data concerns or whatever. So how do you figure out when you've got a solution that makes enough sense for enough people to say, okay, this is something we're going to move forward with, because I imagine there's always going to be. There's going to be folks on the periphery who feel that it's maybe not fast enough or maybe too fast. Maybe I'm wrong. Like is do you, do you find that you know there's some things that there's just complete consensus around, or is there always a little bit of like people on the margins?
Speaker 2:There's never consensus in the general term of things. Consensus in the general term of things, but there is enough consensus, like you said, and when I said before, things make sense to everyone or there's a consensus.
Speaker 1:what I mean is depending on the stakeholder. I'm talking to.
Speaker 2:I can give you an example. Say, for example, I'm working with my medical affairs partners and I understand that parsing through large amount of scientific data on an ongoing basis is something that it takes time and it takes a lot of attention.
Speaker 2:What I mean by consensus is is this a problem that affects, or is this a challenge that affects, a large number of people? The answer is yes. Does everyone want to use Gen AI to solve it? The answer is no, many people don't.
Speaker 2:My job is to help show what the incremental gains are, where you can use it, how you can use it and build a framework. I'm going to use the word framework and I'm sorry for that, but it is a framework. At the end of the day is to say here's how, here's how you could do it. And you're going to have people who immediately see the value and say, oh my God, I've been waiting for this since I started my career. And you have people that say, well, I'm going to do it the old way.
Speaker 2:My role is not to force people into doing things one way or the other. My role is to help show the way of what is possible, give people enough training, if that's what's required to get them up to speed, and also make sure that the legal hurdles, the compliance hurdles, etc. Those are taken care of so that people have safety nets on how they use these new types of technologies. So when I say consensus, it's not just for the end user but for the other stakeholders that need to be involved to be able to make that decision.
Speaker 1:So I think that that align on a challenge and then evaluate the impact or the gains that can be made leveraging a digital solution. In this case, as the head of digital strategy, I think is a really again sort of somewhat obvious when you say it out loud, but not quite as consistently implemented approach.
Speaker 2:And I would agree. I think as you work through your life, you start to realize that there's a lot of common sensical ways of doing things. It's just that we don't always opt for that route right. And I think as you mature and as you progress in your career, you start to think about what is the simplest way to do this. And it reminds me of when I was in primary school and you're doing a test and the question was so simple that you couldn't believe that that was the way to answer it and you found a way to make it complicated.
Speaker 2:I think if we take enough time to reflect on what is it that we're trying to do, often there is a simple pathway to begin. It doesn't mean that things will not get complex. They will, and what I described to you doesn't mean that this always works at the first attempt. There is a lot of negotiating and doing this, but I think the ability to formulate the problem is usually at least from my perspective is usually a good place to start, because the empathy is built, so people know that you see them for who they are and what they're going through in their day-to-day jobs, and that is something that comes with experience. So the roles that I've had the privilege to have over the years gave me perspective on how does medical operate, how does commercial operate, what does a marketer do. And it doesn't mean that AI is the answer to all problems. Maybe it is, but that's not my premise. To begin, it's not to say here's AI, all your problems are solved. Dot, dot, dot.
Speaker 1:I imagine that, just listening to you, that folks don't see you in-house specifically as, for example, a Gen AI evangelist who's just shouting about gen AI from the rooftops you're a. You're looking to try to find ways to help those team members, and that that's again two sides of the same coin, but a very different experience, right?
Speaker 2:Absolutely, and that is by design, right, because nobody likes change, even those who are responsible for change management. When change affects them, the first reaction is always a gut reaction and it's just human nature and what I do. It's not a secret formula and it doesn't always work.
Speaker 2:I think you have to be, you know, truthful here, and the reality is sometimes, even though you may have the best intention and you want to bring people along, there's a perception that this is bad or that this is a lot of work and how am I going to manage this on top of everything I do? So that is also a reality of what I go through in my role, but it's also an expectation that I'm able to navigate through that and bring people along. And that is the fundamental objective is I'm not an AI evangelist. I might be an AI curious. I don't say that I know it all, because I don't, but we all have to start somewhere and if we can identify where to begin, it makes things easier.
Speaker 1:You mentioned that you know you make an effort to educate yourself. I will say, even just from my own personal experience, I probably fall into the you know hard to teach an old dog new tricks kind of category, and so I am potentially a little bit more set in my ways and I am very, very much trying to change my behavior. Like I am trying to be very disciplined about you know things as basic as I just don't use Google search anymore. Like I just I'm like okay, let's go to AI platforms first and engage. I'm asking AI how AI can help me, because I don't know you know very well yet.
Speaker 1:But I find that understanding AI tools, understanding what the full capabilities of those tools are, understanding where this is going as it continues to evolve, understanding what platforms and tools can do what, like I asked Gemini to do something the other day that Gemini responded and said like I can't do that, like that's not even something that I do. This is a lot to absorb while people are also like doing their jobs right, how do you educate yourself? How have you found that you've been able to kind of change your ways of working and what advice would you give to folks who are there in a busy day going well, I've got to get my stuff done and also have to learn how to get my stuff done differently and and and like that's just a lot. I could have just said talk to me about how you educate yourself, but all of my questions are too long.
Speaker 2:And that's fine, because I really enjoy having a more detailed question, because it helps me think about really what. What do I do? I think a part of educating myself is a very conscious effort and it's irrespective of my job. I make time to acquire new skills, to acquire new competencies, to get perspective. So, whether that's listening to a podcast or a number of podcasts about all things AI, whether that's the technology, business cases, et cetera, when I'm driving, if I'm commuting to or from work or whatever, and I'm alone in the car, I could be listening to music, which I do too or I could split my time between pleasure ie music and education ie a podcast. So that's where I get a lot of good short form insights that start to build up as like a puzzle in my mind. And then when I get home and I have some time and I hear about what this new tool can do or an existing tool has new capabilities I don't, but I try to find myself learning about new tools, whether or not they have an immediate use for me today, and that starts to paint the picture of where things are going. So I'm happy to pay for subscriptions to test things out, learn a little bit more. And if it doesn't make sense for me to carry on with that, I won't learn a little bit more, and if it doesn't make sense for me to carry on with that, I won't. So part of it is listening, part of it is trying. Part of it is newsletters. I subscribe to a number of newsletters, some more detailed than others, some more technical, and I find the short form. Reading helps me. I'm not the type of person that wants to read for a long period of time. Give me short and simple, and if it's interesting I'll go deeper.
Speaker 2:I tend to follow people on LinkedIn that are either very outspoken about their views on AI, and whether they're right or wrong, it doesn't matter. It's I want to hear their perspective, get curious and get my own perspective, following people who I know for a fact do this every day, all the time, and they go through the hurdles of figuring things out that I don't have to go through and I can just reap the benefits of their effort, and I think that's also very valuable. And the last thing is I use AI to discover about AI, especially now that the tools can search the web and do all these fun things. I'll ask you know ChatGPT and Perplexity and Gemini, and I'll probably ask the same question to everyone all of these tools and see what they come up with, and I think that gives me enough on a regular basis.
Speaker 2:This is almost like a daily effort or multiple times a day type of effort, but it's not a full-time job Not mine, for example but that helps me to build a lot of perspective and stay up to date. But the foundationals when Jenny and I started to become a think, I did a lot of those small short courses on Coursera, on LinkedIn Learning, just to get the foundations, because there were people that were already thinking about change management and I knew that that was going to be where the painful days were going to be is. It doesn't matter how much you know about the tools. Can you effectively help people navigate through this?
Speaker 1:So you said podcast, newsletters, linkedin. You ask AI how to use AI, which I do that too. It's as silly as it sounds, like a light went on at some point. I'm like, why am I trying to figure this out Like AI? Just tell me how to do this. But is it possible to, off the top of your head, name one podcast that you think that you know listeners might get a lot out of, one newsletter and like one person on LinkedIn that they should follow?
Speaker 2:So, newsletter I subscribed to superhuman. Okay, I find that the summary is very, very good. Uh, podcast the AI daily brief is my go-to. Okay, um sorry, and you asked something else. I think.
Speaker 1:Is there someone on LinkedIn that you follow that you find is particularly helpful?
Speaker 2:Yes, I find Simon Smith to be and this is a super biased answer, but it's true, it's his full-time job, I assume he posts a lot and he saves me a lot of time, so I have to give credit where credit is due, and so that's my go-to.
Speaker 1:Simon's my go-to too. I try to see if I can actually grab a coffee with him every once in a while and I come away smarter and amazed and also slightly terrified sometimes. It's a lot and, yes, he is in a really interesting position to have this be his full-time job and he's very smart to begin with and has a really interesting vantage point of being where he is. So I'm going to put those in the show notes so people can find those. So I'm appreciating that you're not going to go through the brand by brand specifics of what you guys are doing and reveal any kind of state secrets here on the show, but can you give a sense of, maybe, where you are finding some of that consensus around kind of AI use cases within Bayer and where you're starting to see early impact and what you're excited about early impact?
Speaker 2:and what you're excited about.
Speaker 2:There are some very low key use cases, and what I mean by low key is they don't require a lot of learning to get some benefit out of it, and that's the simple task of creating custom agents for a particular brand to help validate assumptions about how to position your brand.
Speaker 2:So, if you give an AI enough information about your product and your competitors, who they are we're talking publicly available information and just use the AI as your on-the-spot consultant or marketing strategist, is starting to show some benefits in terms of rapid thinking, of rapid thinking, so it's shortening the time we need to formulate some hypothesis about what makes sense for our brand and where is the brand going, et cetera, et cetera. So that to me, not being brand specific, many products can do that. I find to be an easy. Then there's other use cases where you can combine information, whether that's for market research or proprietary data, and use that to create personas, for example, and that also helps us to refine our messaging, refine perspectives, which data points to highlight and how to highlight those are. If you think about it, this is all very operational, almost to an extent, but those are easy to do and the ROI is very big.
Speaker 1:What does the infrastructure look like? And again, appreciating that you probably only want to talk about it to a certain degree of specificity, but what does the infrastructure look like at Bayer either sort of people on your team or tech stack, Because in July of 2025, building agents for a specific brand is not a Herculean task, but it's also not something where you're going to turn to a brand manager and say, hey, you go and stand up an agent for a brand. Someone's going to need help doing that. Is that your team that helps them? Do you have partners that do that? Who's helping to bring these things to life, some of these early but very impactful wins?
Speaker 2:We'll talk about the tech stack first. We have an internal tool called MyGenAssist, which is basically a user interface that in many aspects resembles what ChatGPT Plus looks like and, in the backend, has the ability to select a variety of LLMs whether those are from OpenAI, from Anthropic, from Google and that gives us the flexibility to pick the LLM that is most appropriate for the task. Back end, the tech stack that we have that also gives us the ability to use our own data and have those concerns of copyright and safety and security of our data privacy. Those are taken care of and this was developed by global teams much before my time at Bayer. It's been a tool that continues to be optimized with new functionality, perhaps a few steps behind the best in class of those in the public domain, from OpenAI, etc. But still very good.
Speaker 1:And that sets up the framework and their entire business model is just to release new Gen AI models is not a terrible place to be if the tool that is a couple of steps behind is, like, highly utilized and robust and is adding value. Because I've seen lots of I've been doing this for a really long time and I've seen lots of globally mandated digital tools that are more than a few steps behind and that don't get the kind of uptake that I think that my genesis is getting Like. I think that that's a pretty well-utilized tool.
Speaker 2:I think it's one of those things that I think everyone at Bayer is proud of. Yeah that's amazing. Is it perfect? No, yeah, but is it really good?
Speaker 1:Yeah, it is.
Speaker 2:And especially at this stage of maturity from an adoption perspective, from the type of use cases we have, it does things pretty well. So that gives me as an individual and as someone who's part of the mandate is to help the company progress in its adoption of Gen AI, so it gives me a really good place to start, so very privileged to be in this position. Now, on top of that, in terms of, you know, building those agents, that's where me as the individual also come into the conversation, because a lot of what I do is to figure out how things work, whether that's in my personal life or in my professional life. I'm at that stage where I can help teams do this by doing it with them. So I don't keep the secret sauce there is no secret sauce but I show them exactly how, step by step. Here let's build an agent. Let's start from scratch here's the documents that you might want to consider let's upload them, let's tell the AI what we want the model to do with these documents and, step by step, we go from a zero phase agent so there's literally a title to a fully functional agent. We know it takes a few minutes to get something that is good enough. Then we talk about refining, and that can be a joint effort, so we can assign more than one owner to the agent and say hey, if you feel that something's not quite there, here's how you could refine it. And we do that even as part of setting up the agent. So people know what does refining an agent even mean. So we show them, and I do that with them. My, my partners in it and I will work very closely in figuring out how to squeeze the maximum amount of juice from the tools that we have.
Speaker 2:But a lot of this is knowledge transfer, because the intent here is not I do it, it for everyone, or myself and my IT partners will do it for everyone. That's not scalable. We want everyone to do it for everyone. So for those who are in that stage of adoption where they're curious enough to get started, we start there, path of least resistance. You want to do this, I got time, let's do it. And for those who are perhaps a little bit more cautious or not convinced yet, we'll use the use cases of those who are a bit more advanced to say here's what your colleagues are doing. If you'd like to test, I can do it for you, because what I find is that people don't do certain things because they think they have to do it by themselves and they don't know where to start. But that's where I come in with my immediate team, my cross-functional team members, to build these things for people.
Speaker 1:Well, and I imagine that it starts to become a bit of a flywheel, in the sense that if you have a handful of brands using the agents and that's impactful and they're continuing to train their agents, one, they're kind of up and running and you can turn your attention to others, but you also then have this kind of installed base of advocates and installed base of folks who know how to do it and they can be helping their peers. It ends up proliferating, probably in a very positive way.
Speaker 2:It does absolutely. And the interesting part is that there are other curious people in the organization, I bet, and they've done their own agents. It's just perhaps they haven't had a platform to share those and through this sort of change management piece, I sometimes find that, oh, so-and-so has done this agent. It's really cool, great, show me what you've done so I can learn from you. So this is a two-way street.
Speaker 1:How do you feel that agencies can be providing the most value to brands right now and I appreciate that different brands have different needs and all that but if you can generalize it like where and how can agencies be providing the best value right now, in this time of change and sort of like a little bit of like decoupling from ownership over some of these things?
Speaker 2:That's an interesting question and it's one that, as a as someone who's spent some time in the agency world not a lot, but enough to see how it works and spent a lot more time on the client side I think it's the value proposition, and that goes for agencies, it goes for everyone. What value do you bring to the equation now that certain tools do some of the things that you used to do, assuming that your client actually uses those tools to their own benefit? Yeah, that's probably the very first asterisk I see is do your clients do use those tools? And if they don't, there you can still maintain your business model. If they do, then try to figure out where in the supply chain do you bring the most differentiation? And what I find is, for that very high level strategy where you just want to talk the basics of a brand, maybe your client can do that on their own. But when you go to things about you know want to do things related to creative development, storyboarding, maybe your client can do the first few steps of the journey. But what you bring as an expert, or as an expert with AI, is a new way to differentiate yourself. So my short answer to your question is.
Speaker 2:I think the expectations of an agency, of what an agency do, what an agency can do, will change and are changing, but at the same time the same tools that the client uses, with the client view on it, are different from what an agency could do it with the same tool.
Speaker 2:So I think the two can coexist.
Speaker 2:I think that if one of those equations where things move from the left side of the equation to the right side of the equation but the totality is the same, I think it's the dynamic between can an agency really charge to write a brief these days versus a marketer using a Gen AI tool to turn an idea that is unstructured into a structured brief tool to turn an idea that is unstructured into a structured brief, yeah, maybe the marketer could do that and save some time and money, but that gives the agency also the advantage of having a very clear picture of what the client wants.
Speaker 2:So I think that dynamic is changing. Different companies I mean different pharma companies might be at different stages of ability and maturity to expect different things from their agencies, but what I've found over the last few years is that many agencies are able to give their clients more for the same amount of cost or investment. So I think it's a good place to be, but it's not one of those where you can just set it in cruise control and life is good. I don't think that's the case anymore.
Speaker 1:One of the things that I think has actually caused a lot of frustration and friction between agencies and clients is this sort of notion of I am not capable of doing X Y Z because all of the designers reside in my agency or they have all of the brand assets, and so I'm sort of and this is maybe a bit of an extreme, but I'm held hostage a little bit because when I need something, the only way I can get it is the agency right, and that I think that is one.
Speaker 1:I think that that's been problematic. I think that that causes undue burden on a relationship. I think sometimes the executional stuff gets in the way and I think that that's very dramatically shifting right. Like these platforms in many ways are a little mini delivery team that's sitting on every client's desktop, but what's not baked into those platforms is perspective right, absolutely. And that agency perspective and like the deep insight when agencies have worked with brands over multiple brand managers for years, are able to look at the data in a really unique way and they can add that well-informed perspective and be part of the dialogue with a client versus. You know, they're the ones that hold the keys to the door behind which, you know there's a bunch of writers and designers that hold the keys to the door, behind which there's a bunch of writers and designers.
Speaker 2:That perspective feels like something that you're saying is a really key area that agencies can provide value. Absolutely. I think what you mentioned the example you gave on holding the client hostage when I use the words cruise control, that was sort of the dynamic of power if that's the right way to look at it is the agencies, the various agencies would have some level of control and over their clients, because they knew that it was the only way to get things done. That has changed, so it's not a bad thing. It just means that what we consider low value or low complexity tasks can now be either done in-house through the variety of tools. But as they do that, they also free up a lot of bandwidth for the agencies to shine on what they're really really good at, and I think that's good. It's a win-win.
Speaker 1:I think in some ways it creates like a really unique opportunity, but it kind of raises the stakes a bit right To say, all right, how can we be smarter? Because getting this sort of functional list of assets done isn't really considered and it really probably never was, but like it's not really considered success anymore.
Speaker 2:Yeah, I mean I'm not saying that this is a great story for everyone at the same time. For a client, I think this has shifted the wind to allow us to do more with the same amount of investment and resources. Allow us to test, because there's perhaps some savings elsewhere. Like you said, for an agency it comes down to being able to work with the client. To say now that you've saved X, y and Z based on our previous year's spend. Well, how about we do this, and what an agency would have to do in the olden days, if that's a way to look at it.
Speaker 1:That was like six months ago, but yeah, I know right, maybe last week.
Speaker 2:But you know, get a team of highly skilled, extremely knowledgeable people and look at their billable hours just to come up with what should we do, what should we propose to this client to take them from stage one to stage two. The amount of money, the internal cost of doing that, has also been reduced. Right, because now you can have those experts collaborate with an AI tool, come up with a few scenarios, prototype it. We're talking a few hours worth of investment from only a few of those stakeholders and being able to give the client not one, but like three or four scenarios and say, hey, you have another hundred dollars to spend. Here's four different ways that we could do this. Yeah, and I think that's that's what agencies can try and and do more. It's. You still have the same resources, but your clients now may have more latitude because they're able to save elsewhere. So again, I'm looking at the positive. I'm not saying this is good for everyone all the time. For agencies that really don't want to evolve their business model, it will be challenging. There is no question.
Speaker 1:But, to your point, the ones who do.
Speaker 1:It's not an overnight, it's not an overnight switch and it's not simple.
Speaker 1:But you know there's lots of agencies out there who have really really smart, talented people who, like that earlier conversation that we had about you know, metafares, where you've got really smart people at MetaFares who are spending a portion of their day, whatever portion that is, on what might be considered kind of low value or repetitive tasks. If you can remove those and level those people up and they can spend more of their day on high value tasks, that's a good thing, right. And I think that the analog is there's really smart senior people at agencies who are often doing things that are sort of below their pay grade, as it were. And if they could be spending more of their time and not more of the client's dollars, right, but just deploying that scarce resource which is their effort and their kind of intellectual capacity, if they can be deploying that more effectively for clients, one, those people stay busy and two, the clients get better value. And, to your point, that in those scenarios I think is a good thing.
Speaker 2:Yeah, I think this is very cliche what I'm about to say, but I think everyone at some point in their life has thought of work smarter, not harder. I think Gen AI has now unlocked the very real possibility of working smarter, so I think it's shaping out to be a good thing.
Speaker 1:Kareem, that was an excellent quote and I'm going to use that as an opportunity to say thank you. This has been a really awesome conversation. We covered a lot of ground and you were very game for every one of my really long questions, so I really, really appreciate it. I really love both the insight and the approach that you bring to this. I know that the Bayer team members are lucky to have you as part of the mix, so thanks for the time today.
Speaker 2:No, thank you, Neil, and thank you for the opportunity to participate in your podcast. This is very interesting.