AI FIRST EP 2 TRANSCRIPT
Brice Challamel: Every human employee, manager or leader should ask themselves, when do I need to find the needle in the haystack? When do I need to predict and anticipate things? When I need to create informed recommendations. And then depending on their role, they can build their own roadmap out of those building blocks. We will call them for now, the five superpowers of AI.
Andy Sack: This is AI first with Adam and Andy. The show that takes you straight to the front lines of AI innovation and business. Andy. I'm Andy Sack alongside with my co host Adam Brotman. Each episode we bring you candid conversations with business leaders who are transforming their businesses with AI. Straight talk, actionable use cases and insights for you. Welcome Brice and Adam.
Adam Brotman: Hey Brice. Yeah, we're really thrilled. We were really looking forward to having you here on this show because as you know, and many, many of our listeners may not know, uh, you know, we had an opportunity to spend some time with you and learning more about your background and, and Moderna's AI journey and transformation that you and the team that you work with have really pioneered. And um, for those, you know, obviously we spent time with you. We wrote a chapter in our book AI first. Uh, that really was sort of a hero chapter of our book because we were looking for case studies of companies and leaders that really understood the transformative power of Gen AI. Not just in, you know, uh, in a bull time kind of a way, but in a fundamental essential way. And uh, we had read a little bit about uh, what was out there about what Moderna had been doing. We were lucky enough that you, you allowed us to interview you and feature you in our book. And, and for those that haven't read the chapter, let me give you a quick one minute overview. So that kind of set the table and then uh, Andy and I would love to spend um, some time asking you some questions. So the thing that people need to understand is um, we, the, the chapter in the book and our conversations with Brice focused on the fact that Brice was brought into Moderna specifically to help lead an AI transformation effort of sorts. And um, in the book we outline and talk about how you got there and it wasn't like flip a switch and all of a sudden everyone could just have an AI transformation. In fact you got to um, Moderna, I think before ChatGPT was released publicly. And then as that came out you were, you had positioned yourself because you had done some um, really amazing things to sort of spot that the, the technology stack and the, some of the infrastructure, how the workers were able to use Technology needed to be shored up. Um, you already obviously had buy in from leadership to perform and implement and lead uh, an AI transformation. And then when ChatGPT came out, um, you've suddenly had a catalyst for a much easier to use platform to get everybody in the company sort of rallied around this idea of how Gen AI could really be a productivity lift, an innovation boost, um, et cetera. And so you talked us through that and um, talked about um, the fact that you, you you know, have this really innovative way of getting uh, everybody to try Gen AI internally by doing a kind of a prompt, a thon, type of a contest. And um, it really catalyzed and began the process uh, that you ended up with you know, thousands of people using Gen AI, uh, really embedding it into the culture and into the fabric of how Moderna, um, works every day across multiple functions and, and that you saw a lot of positive um, things that came from that. So that's the essence of what we talked to you about in a very, very high level and we'd love to just sort of um, you know, for, for the benefit of ourselves and everyone else kind of start asking you some questions about it. So one I'll start just because Andy and I probably have a list of things we'd love to talk to you about. One is you know you, we, we definitely hold you up, uh, and Moderna up as an example of a company that have the right mindset, that understood that you know, there wasn't a particular outcome in mind, um, that you understood that this was a transformative technology that should be infused into everything the company does. Almost like computers were back in the day or the Internet or um, those kinds of essential utilities. And um, flash forward to now and I'm going to, I'm going to start with sort of an end of the movie question like where, where have you
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Adam Brotman: found, generally speaking to see the most positive uh, results? Is uh, there a particular function or a particular type of use that either surprised you or didn't surprise you where you have found like that the company seems to be getting the most out of Gen AI? Uh, not, not. And I'm not denigrating other places that maybe aren't getting as much out of it, but could you kind of tell us and our listeners a little bit about where you're thinking? This is really popping for you guys.
Brice Challamel: So thank you, thank you for the recap on the great question. The one thing that strikes me is that generative AI uh, is a very powerful tool when you have an Important decision to make with a lot of data and short time. So uh, this is not functioning specific or role specific, but I'll give you a couple of examples. So we have a very popular benefit, GPT. And GPTs for everyone's reference, uh, are the names that we give to AI agents that are coded to do one thing and do it well. So in this case that agent has digested in its knowledge base 600 pages, uh, worth of content on the benefits that Moderna offers. And as I speak to you, we just close our open enrollment two weeks during which you have to choose your benefits. And that's very little time and a lot of data to digest in order to make informed uh, choices. And yet this is very material. At the end you're going to choose a healthcare plan, commuter benefits, a number of options are offered to you that can have a significant impact on your life. But then we famously also have uh, a dose ID GPT that supports our clinical development team to evaluate the qualities of different drug candidates in terms of dosage. Uh, in clinical trials as much as the decision still, uh, is the humans, there's uh, thousands of pages worth of data and you want to be as quick as you can in those clinical trials and especially there's our back to back trials to get from the inception of the first idea that you have of a new potential trial treatment towards something that you can put uh, on the market and that goes to patients. So I would have dozens of examples such as these ones to share in which, whether it is for hr, for legal and complex contracts with deadlines on clinical research, on um, finding patents, there's a clock ticking, there's a lot of information at play and you need to make important decisions. And up to now a lot of those were done with the best possible means available to humans, which is basically to read things and write hand notes and do the best you can. Um, and these were not very efficient processes, uh, before, and they were not also very safe processes. There's only so much reliability that you can expect of a human who has hundreds or thousands of pages of information to digest before making an important decision. So I know that some people hearing us will think, ooh, having AI that maybe hallucinates and maybe generates wrong information support you for something in the field of science. But you would be amazed how those decision processes in our company, as in everyone else, uh, really rely on human ability which is uh, itself constrained by what our mind can absorb and give back. So the combination of the experience, the wisdom, the ability to pinpoint Something that is uh, uh, unusual and uh, interesting. With the ability of AI to digest vast amounts of data, to categorize it instantly, to give it to you in a relatable narrative, and to anchor for you the things that seem the most important and insightful. The combination which we're going to call this augmented work, the AI augmentation shines in my opinion the best at the moment in the current state of the technology, in those, in those moments of decision making.
Andy Sack: Brice, I'm curious, like, given the two examples, one being, I guess, internal benefits and the other being clinical trials. And then you, you mentioned a bunch of others. If we were to ask the executives, not the employees, the executives at Moderna, uh, where they got the most return on their AI investment, what, what do you think they would say? Because I don't think, I doubt that they would give me the same answer that you just did, which is, your answer is excellent. This notion of short time frame and lots of data to make a decision that makes a lot of sense. Like AI is great at that.
Brice Challamel: I'm, I think. So we should break down what AI does in general and what Genai does in particular.
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Brice Challamel: So AI in general does five things for you. And I've been living with that framework for more than a decade now. Was already framework I used at Google when I was uh, the global head of transformation there and still today at Moderna. And it's very stable. So first, uh, AI helps you with perception. Think about identifying a spelling error in your document or a tumor in an X ray or you know, like so finding the heat in the haystack, right? Like perceiving the signal in the noise. The second thing is very good at categorizing. Think about, uh, aggregating together customer, uh, segments, uh, or uh, organizing files in a folder or songs in a playlist. The third one is very good at prediction, right? Anticipating the consumption, uh, in terms of energy of the city, uh, uh, based on the past trends or even weather forecasts. The fourth thing it does recommendation. And of course each of the things I mentioned kind of includes the previous ones. So. But for instance, inviting uh, you to take one path rather than an hour in Google Maps to get from home to work because it's going to gain you three or five minutes. Uh, or if I go back to my paste example, recommending the next song in the paste out of thousands that you've never heard before. And the fifth one is good at generation. And this is not specific to Genai. Remember when we already had uh, autocomplete in emails and you would start your email with a few words, you would propose the next word. It's just that generative AI has put that feature of AI in general of machine learning under steroids. And now instead of the next two words, it does the whole email, uh, as a draft for you to think upon. So we have here five core pillars that every human employee, manager or leader should ask themselves. When do I need to find the needle in the haystack? When do I need to predict and anticipate things? When do I need to create informed recommendations? And then depending on their role, they can build their own roadmap out of those building blocks. We will call them for now, the five superpowers of AI. Now with all those superpowers combined, Genai does four things. Integrated things are really useful. The first one is a good assistant, right? It can help as your personal assistant to do something. The second one, it's a pretty good coach to give you feedback on, uh, ongoing work, a draft or something, or even something you plan to say, the words, the arguments, the way of working. The third, it's a great creative uh, partner, right? You can bounce ideas off of it. It will bounce them back to you and add some. And the fourth, it's a pretty good expert. It has huge knowledge and actually the hallucination topic only plays in that fourth bucket. AI doesn't hallucinate ideation doesn't hallucinate coaching doesn't hallucinate assistance. It only when it is required to give an answer and it doesn't have the data as most humans would do. By the way, how do sense the answer, which for humans we call uh, you know, gaslighting you or whatever. So there's one case in which you should be careful. It's when you're asking these generative AI models to be your expert, but you haven't given them the knowledge to be your experts and you're asking them tough questions. Ah, that's a, ah, point which you have to bake into your culture to not push too far. So if I go back to the leaders to your question. The leaders find fantastic assistance in generative AI when they have to summarize a 120 page deck to make a quick address to the whole company, uh, when they have to speak at a public conference and very soon it veers towards the creative partner and towards the coach. Is that the right tone for the right audience? Uh, what other idea could I think, uh, of what would be a great question with which to start a meeting that I have with this very important stakeholder. And then of course, the Last1, the knowledge1. Leaders are less expected to be subject matter experts of any given component of the company. It's the beauty of their role that they should understand and be able to have a conversation, but that the combination of all of this is what matters to their efficiency. Uh, it doesn't mean there's no expertise involved. It can be being expert at doing quarterly earnings results and having the conversation, being experts at, uh, handling government regulation authorities and how to discuss with them. So all those four Personas, if you will, of the combination of the five superpowers to create AI agents that are by your side, I think are still useful to our leaders. And those, uh, among our leaders who have embraced them the most, I can see already after 18 months, how their leadership has heightened to new levels and they've been recognized for it. We have two new EC members at Moderna that have been
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Brice Challamel: publicized, Ros Laughlin and Jackie Miller. And both of them are among the very early trailblazers of leveraging AI uh, for their organizations and are now the first inside promoted EC members in the history of Moderna. And it, it's absolutely not a coincidence.
Andy Sack: Let me nudge you a little bit on this because, like, we're, what we're really trying to do with this conversation and, and with the podcast is help the people that have it. I mean, you've been working on a, uh, digital transformation for four or five years at Moderna and that really you're, you're so far ahead of any other company that we've encountered. And so everybody want, like, the chapter speaks to it. It's why we did two sessions with you. So my question of, like, what would the executive say? Like, your structure's awesome. It's an awesome answer. And yet it's not simple enough. I don't think for someone who's. If you have, if I'm an executive and I haven't yet embarked on the journey and I have the opportunity, I really want to know, from Moderna's experience, in simple business language, where is the return? Like, what can I expect? How would you answer that for someone who's, who's considering going deep on an AI transformation experience?
Brice Challamel: Okay, well, I think I'll give you concrete examples. There's one of our executive leaders who had, um, a recording to make for a conference that was very important to our future and had an hour to prepare for it and deliver the recording, the timid recording. So they jotted down bullet points, ran them through chatgpt to have organized narrative and structure using their usual way of speaking and their language. Because we do Persona based GPTs that read things that you've said or that you've recorded before, learn your style and give it back in your style so that it's very fluid for you to express yourself. That's your own language.
Andy Sack: Yep.
Brice Challamel: And that executive just put it on the teleprompter, did their recording for 10 minutes, shot it at the conference and was done in 30 minutes. And something that they felt was challenging to accomplish in an hour. I have another concrete example recently of an executive who had had 17 quarterly evaluation meetings with their directs. So a very large team and had to document within a corporate application all of the components of those conversations. In their case, they had recorded them and had transcripts. So we created together, uh, a small tool which it took us 15 years to design, uh, that would help them break down the transcript, the recording into the eight categories of input that they need for the system and then read over those and change a few things that they think could be expressed differently and then have them published in the corporate application, which would probably have been something that would taken them a couple of hours before and have had a much lesser, uh, quality of outcome because how much time can you spend on those things when you have so many things to do? So in both those cases I see executives getting out of their way as you would expect. Things that need to be done thoughtfully because whether it is a recording that is going to be seen potentially by, in that case, millions of people in that very large audience and then staying online, or a very important moment in our corporate life, which is about performance evaluation and calibration and talent management, uh, in which you should never let the AI do the talent management, but have it support the way that you think about it and be your coach and your guide and bounce off idea and help you implement it efficiently. In both those cases, I think our leaders found the tool very useful for them. And those are examples from last week, both of them. Right. On any human beak. I, I would have come up, uh, to my field, 10 or 20 examples. But the truth is, and I want to highlight this, we have more than a million conversations a month on chat GBT Enterprise at Moderna. One million a month.
Andy Sack: I'm sorry, did you say one million?
Adam Brotman: One million conversations a month. More than one million a month.
Brice Challamel: That's, that's 50,000 a day out of 20 work days. So it's and how many.
Andy Sack: And roughly that's 6,000 person.
Brice Challamel: Yeah, there is so much that I don't know. Right. It comes to my level of attention when the criticality of it, you know, implies that the leaders would want to have my team by their side to, to think about something creative tool, share it with their peers or things like this. So I, some of our leaders probably still also need to make this into their comfort zone and have not truly baked this in their ways of working. Because if we're honest at the moment, generative AI is useful to people who have a lot of mundane tasks, who do a lot of corrections, redlining, edits, uh, uh, so who are
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Brice Challamel: rather in the middle management layers or even as individual contributors if you're that kind of work and you have a lot of manual repetitive tasks. Basically if you spend more than five minutes doing something that you do more than twice a week, you should immediately have a green flag in your mind to use AI for it. And that's more going to be the case of someone who has a very assigned role than of someone who's a top leader and by definition is going to have a very moving uh, goalpost in what they should deliver and a lot of personal influence, very different each time on how they treat this and that's what they're expected to do. But still, I hope I give you a couple of concrete examples there.
Adam Brotman: No, those are great examples. I, I want to pull the thread on this a little bit because I think this is really interesting. 1. First of all, you mentioned there's going to be more of a, uh, not obvious but semi obvious opportunities for assigned roles that have more repetitive type tasks to allow AI to help them. And then you mentioned as opposed to say top leaders that are somewhat, have more of an amorphous decision making and leadership role. Although the irony is you said it's really good when you have to make big decisions quickly with a lot of data which a lot of big uh, top leaders have to do. But let me, let me go back to something you said and I want to ask you, Brice, I want to characterize your answer to Andy's question slightly in my own words and I want you to honestly tell me if this is how you feel as someone who's living it. All of your examples that I'm hearing are finding these variety uh, of opportunities for AI to augment and improve and speed up the things that you're supposed to be doing every day in your, in your job as a knowledge worker, as a, as a, as a worker and as a leader as a worker. And so in theory, if it's giving you a speed improvement, a throughput improvement and an equality improvement on some level. And it might vary from task to task from day to day, but if it's happening across the board, by definition, if you were to step back in the aggregate and say a company that really is properly trained and proficient and understands the power of AI and is using it as much as possible where it makes sense, that company across every function will have a step change improvement in its throughput capacity and productivity as well as quality of decision making. Partly because it is being augmented by AI, but also because when you're freed up with more time, that also likely will help you get to better qualitative outcomes as well. So you have this double, triple compounding effect if AI is being used at that aggregate level. Am I so far? Is that a. Is that sort of how you would describe the end result that you're trying to achieve? And it becomes this, the roi, if you will, or the return is in the aggregate of all these micro moments that are some important, some less important, but they all add up to the overall outcome. Am I on the right track?
Brice Challamel: Oh, thank you so much for asking it this way. I want to quickly highlight something. Most of the leaders have people reporting to them who are architects of choice, who present them options with recommendations and pros and cons, and then based on this architecture, they make decisions. But normally, if you're the leader of a company with the type of cloud that Moderna has, you don't go around making decisions on your own, regardless of the way that they've been architected for you by the teams who are in charge of the fit. So I say this because those are the teams who need AI. And then as a leader, you're going to receive the architecture of choice and you're going to be able to make informed decisions thanks to them. And that's a very complex dynamics in which we could discuss at length the place that AI takes at every step of that process. Um, and so that's why I think that even though it's useful for decision making in short amount of time, with huge amounts of data, I think it serves the architects of choice more than it serves the decision makers. Now, that being said, the question that Andy asked me was if I would ask your executives today, what would they say? And that's why I gave you the, uh, step one of change, where I think our executives today are firmly anchored, which is improving the things you do already. Uh, this is not at all the goalpost or the destination. This is just answering the exact question that was asked of me, because the next thing that happens is that you're going to change the things that you're doing instead of improving them. And by the way, in my example of the leader who has transcripts of their discussions for performance, this is already an enhanced way of working. Because, uh, I would posit here that if it wasn't for the ability of AI to ingest those transcripts and do something
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Brice Challamel: useful with them, they would not be having transcripts of the conversations. Right? They would probably just have conversations and jot down notes. So we're already seeing in that example how someone moved from adoption to proficiency to new way of working. Right. And the fourth step of this is rebuilding your business with an AI first principle to logic of your book and of our interview. It is redefining your roadmap in a post AI world, or we could even say probably at this point in a post AGI world, uh, anticipating that this kind of augmented intelligence is soon going to be able to generalize, which means technology in one field and applying in another. And that if you have artificial generalized intelligence you can't work the way you used to, just the way that if you have laptops you can't work the way you used to. You're not going to use a typewriter and do carbon copies and send them in tubes anymore because something else is going to happen. And um, we already see. I'll give you some things that I find very positive. One of them is, uh, the contribution in cross functional teams has exploded in capability and inefficiency in our environment because people are no longer constrained by the lack of knowledge or the lack of expertise on topics that are bordering theirs and that they need to collaborate with. They can leverage generative AI to ask a lot of questions, to create courses for themselves to deep dive into something that was something they knew of but they could not have led a much deeper conversation with. And now they're going to become much more at ease in those cross functional uh, workloads. And the sidle breaking capability of Genai here is huge. The second one is it improves the morale of people. Like it's good for their well being at work. We have measurable evidence now that people feel better when they have an agent which in privacy, without emitting any judgment will listen to any question they have and help them get out of uh, if you will, um, a state of being prisoner of your own lack of capability, knowledge or even sometimes being able to bounce off ideas with someone or in this case, uh, with the Model with the agent to pressure test a little bit your hypothesis before you present them to a larger audience or to your managers or to your peers. So the ability to understand each other better because we don't have this huge knowledge gap anymore, the ability to have some support by a friendly, private companion mode that is by our side is both helping already rewire entirely the processes of the company and make people feel better about it. And, um, those two things combined, they shouldn't be taken for granted because it's one thing to have access to new technology, and it's a whole different thing to feel not only comfortable but elated with it. And in this way, I think we're in for a huge productivity boost with or without the catalyst of transformation, because you can always count on humans to do in less time, something important to do a more pleasurable way, something that is hard, uh, and to be imaginative about the way this should go forward because a lot of people have a lot of ideas and want to be owners of their own future.
Andy Sack: I'm, um, I'm conscious that we only have Bryce for 20 or 30 more minutes and I have a slew of questions, so I will. I'm gonna let you go first, Adam.
Adam Brotman: Okay. I, well, so this is great, but let's, I'm gonna take the conversation in a slightly different direction and that's okay. Yeah, yeah. So, so what we've talked about is. And that was fascinating. You know, I, I have to say, speaking of working a different way, I can't wait to go back and re. Listen to this conversation. Brice, I always get this from you because you, you think about this topic in such a deep way.
Andy Sack: Have, ah, you talked about, have you talked about this topic with AI, with generative AI?
Adam Brotman: Yeah, no kidding. Because like, I mean, I love the way that Brice, you just talked about, yes, it's about productivity and improvement, but it's actually a different way of working. And then that, that's a holistic statement that is very in line with how Andy and I think. But it's really, we, we spend most of our day just trying to explain to people that this is not just a, a slightly better Google and that this is actually fundamental. And then to be able to have a conversation with you where you're, you're so far beyond where we are even in terms of seeing it in action. We, we have little bits and pieces and so that was, it's really helpful when we try to go get you to talk about the, the uplift, the roi, the, the outcomes, like how, uh, where you go now let's switch gears for a second. That's about the end of the movie or not the end of the movie, but at least sort of the, the throughput and results if you will of uh, what, what comes if, if somebody's working this different way. Let's go back though. So you and we talk about this in the, in the, the book and for our, our listeners there's
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Adam Brotman: this notion of there was a time where you had, I'll call it 5000 or so, give or take, um, employees and workers and leaders at ah, Moderna who for the very first time were going to be exposed to this notion of working with Gen AI and incorporating it into their workflow. And you went through a, a process with a promptathon if you will and a uh, champions council that you established. Can you go back. Let's go back upstream and talk about now looking back, what would be your. If you're say someone's listening to this podcast and they're like, I want to be AI first and I know there's a lot of technical stuff I got to think about in terms of like an academy and onboarding and technical issues. But like from a cultural perspective, from a behavioral change perspective, what would be your advice to somebody to. That's just starting out about how they sort of do the. Do as much as they can to facilitate a uh, smooth transition to a company embracing this.
Brice Challamel: So I want to say this very basic but I think profound thing to begin with. It's very hard to think of people as solutions when you think of them as problems. It is inhuman to have both notions in your mind at the same time. So if you start in this problem, in, in this challenge thinking I have X thousands of employees and um, and they are problems to me because they are used to one way of working and I have to move them to another way of working. You're resetting yourself up for failure because the truth here is that you, if you have X thousand of employees, you have X thousand solutions that are just given to you. People who love change. We love change. We love a new book, a new movie, a new lover, a new president, a new dress, a new season of fashion, a new makeup brand, uh, a uh, new computer, a new software. We love novelty in every and all domains of our lives. We are neophytes, the humans, and we love them under certain conditions. Uh, three mostly the first one. They have to be handed to us in a progressive fashion. We don't like change that is falling in our garden as a meteorite we need to have a way to wrap our mind around it in time. The second, we have to have our word to say about it. We need to be part of the change. I, uh, will accept smartphones, but I want to choose the applications and the screen saver and the ringtone or things like this. I want to be a part of this change. I don't want just it to be entirely imposed to me. The third one, I don't want to be alone in change. This has to be something collective. I want and need people around me to be going through the change as well so that we can support each other and that we can move the norm together seamlessly and simultaneously. If those three things are done and you give people something that is progressive, that is proactive and that is collective in the way that you bring it to them, you have x thousand of solutions. And that's why we did what you call the promptflow, which was very simply, we acknowledged the fact that it was going to be probably shadow AI. So we got access to all the genai, uh, domains or agents out there. But in exchange we provided one which we thought was best of breed. We gave a client to everyone who had a Moderna email that they could use and um, that had an API to the latest engine by OpenAI which at the time was GPT4. And we made sure that their data was safe and that their conversations were private. Right. We installed a zero data retention policy. We made sure that we were SOC2 HIPAA compliant. Uh, we have a uh, OneTrust audit that we applied to this and at the end of those basically 12 weeks of work, we had something in place, uh, quick and efficient that anyone could try with and they were fairly safe with it. And at that point they need to be telling us how to drive the change there. Like how is this useful to you? What are you doing today that you couldn't do yesterday? Um, and as you know, because we discussed this for the book, we came out with 180 solid propositions of AI driven use cases. And we wrote these blog posts for the whole company on our in intranet, which came to the first page of the intranet while had a lot of visibility, titled the High things we learned from you on AI. And that set the tone that we were going to certainly not impose something, especially on a technology that is the fastest adopting technology in the history of mankind with like 100 million users in a matter of weeks. If I
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Brice Challamel: remember correctly, uh, in the very first days of OpenAI, when you see those rocket ship Technologies that everyone starts to embrace in huge numbers. Why would you force it on people? Right? Like, uh, if anything, you have to kind of channel their energy towards it and make them feel safe and make them feel elated, try things and share with each other what they found. Um, as you know, we had this prompt contest, had winners per EC reporting line. So we had, we were sure that we would have people from all over the company and you would win if you were upvoted by your peers in a public channel. So it was a popularity contest, which you might say is the wrong idea. But what we were looking for are champions, people who can embrace the technology and lead others to embrace this. And for this you need them to be popular. You can't have someone at the end of a corridor who's grumpy and negative and just had one efficient idea and make them into a champion. This is probably not going to be my first draft as a candidate. So, you know from seeing people who've had hundreds of people upload their idea out of both the quality of the idea and the quality of the relationship with the rest of the company, that they're going to be, uh, useful champions to promote what they found to be something super interesting and useful. And so that's my. It's a long answer to your question, but I wanted to explain why and give concrete examples piggybacking on your relation, uh, to the, the promptathon you need as a change leader to not want it more than your users, but just capture the energy that they have. Understand that you have populations of adopters, that some of them will be first adopters and some others will be inspired by them later on. But, uh, trust them, right? Like trust your people to want it for themselves, to want to use them and make them safe. And then for those who are successful, give them a megaphone.
Andy Sack: Brice, I just want to comment that you're like all your prior answer, but this one in particular struck me. It's a beautiful answer in the sense that you start by saying, I mean, if you had asked me before, I would be like, no, people don't like change. And you actually start by saying no, people love change when it's presented in the right way. Uh, and then you have your, the conditions with which, um, people like change. And that's, I mean it's really counter, particularly when talking about AI because there's a lot of fear. And then. And there's also, from a business perspective, there's a lot of, because of the speed of development of technology, there's Threats to, you know, there's fundamental threats to businesses, existence and obsolescence that arise as a result of the speed with which the technology is developing. And certainly there's the topic of layoffs, um, which is something that moderna did not do. And so it's just. Your answer was just a beautiful answer, so I applaud it.
Brice Challamel: And I think on the topic of layoffs, I'm going to talk about a fundamental trait of humans again. Hey, let's do a little bit of, like, you know, some really basic things. We have left brain, right brain. These are common to every living creature, which has a spine, right? All the vertebrates have a left brain and a right brain. One of them is basically meant to understand what we can eat, and the other one to imagine what could eat us. It's to eat and not to be eaten. So the brain fight or flight is analytical. And in terms of peace, we'll say, is this safe or not safe for me? And we'll analyze things to make sure that the color, the shape, the sound, the taste, it's all good. I can eat this. The other one, though, the other brain, the imaginative brain, the right brain, jumps to conclusions, like, there's something moving in the woods. I'm going to run the other direction. Right? We are not very high in the food chain, naturally, speaking before the cognitive revolution. And so we tend to be fearful species, right, like the humans. And so that part of us, the imagination, is mostly here to inform us of predation and a very negative outcome of situations. That's why when you turn off the light in the bedroom of children, they see monsters in the closet that are out to eat them and not, you know, fairies or treasure chests or candy, right? Like, this is not what happens in the children's bedroom when the dark comes. And we are still those same humans who, when you turn off the light, we see monsters. So relying on imagination to produce positive ideas and optimistic perspectives is completely counterintuitive. Uh, and it's reckless if you don't know what you're doing. Of course, people will go straight to the darkest possible outcome of something new, which is, I'm going to lose my job and the whole society is going to just topple and we're going to be ruled by overlords of AI but there's a spectrum in this in which we need to use our reflective brain to pose, to breathe, to watch the birds in the sky, and to realize that, no, the world is still here, we're going to be just fine. And yes, there's going to be skill displacement. We, uh, already said this in this podcast. Some people who
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Brice Challamel: used to do a lot of manual M tasks are going to have less of them to do. It liberates some time to do other things. Some jobs were almost entirely manual tasks and those roles would need to be rotated and elevated. Uh, some others had much less reliance on them and would have a different outcome. Uh, but we all live with these concepts of a role. Let's say HR manager, let's say a lawyer in a company which are bundles of dynamic skills. Maybe a lawyer has 20 skills and five of them are not there five years ago and 10 of them won't be there in five years. Dynamic skills libraries. And, um, yes, there is an acceleration of the dynamic skills of every role. And maybe some of the roles will have to be reconceptualized, like there will no longer be enough dynamic skills in them to justify error. But I think this is an extreme outlier. Uh, I think for the most part, most people will find that their role has a rotation of skills, that some of the things that they needed to do was necessary for the role are no longer needed to do because they have a very smart companion by their side to support them and that they're beginning to acquire new skills, new capabilities, new understanding that are going to be very useful to their future and if anything, fun because full of change. Who wants to have the same workday every day for all your life? So it's very promising to have a different workday in a few months or in a few years and become kind of Tony Stark with Jarvis. For everyone who enjoys Iron man, he doesn't work alone. He doesn't have all those ideas like himself in the void, he has an AI assistant who dialogues with him all the time when he's trying to accomplish something. And that's a positive outcome. This is the fairy, the treasure chest, or the candy in the room at night. You see what I'm saying, right? And, uh, I want us to be able to balance those things because otherwise we're going to be prisoners of our night. Natural inclination for fear and for devastation. Our imaginative brain is meant to fight predation. Let's not let it take it over. We've been there before, right? Uh, no 3G antennas didn't fire rings, no trains didn't dissolve our internal organs, no electricity didn't kill our nervous systems. All those things didn't happen. And once again, we're going to find in a few years that, yes, change happened, but no catastrophe did not Happen.
Adam Brotman: Last question is in. Since you're kind of ahead of most, to say the least, most other companies in the space, you've had probably more experience in seeing when, when an employee needs some help sort of overcoming their fear, as you just said. And you, you gave some good examples just now verbally about the kinds of mindset orientations that might help somebody sort of understand uh, the positivities here and overcome their fear. Do you specifically, though tactically you have the Generative AI Championships team Champions team at Moderna. Is. Is that who you rely on mostly to help kind of evangelize and prop up those workers that aren't using it as much every day? Or can you give some tips and tricks about what you've learned about, you know, how do you get uh, like more, more fulsome adoption within an organization?
Brice Challamel: Of course. And you know, I want for everyone who listens to us to relate to something that they've lived already, which is the generalization of smartphones, let's say, right? There was a time when you hadn't seen them ever. And now we come to a time when someone doesn't have a smartphone. Uh, it becomes strange, like it's unusual, right? Like it can be whichever brand, whichever breed can be. And so. But there were eight years, somewhere between 2008 and maybe uh, 2016, I would say, in which we had this big S curve of adoption. And so what happened there first? Uh, um, people around you started using them. Like I think everyone. I often do this show of hand when I'm in public speaking situations where I say, who here remembers the first time they saw an iPhone? And usually I had the whole room raising their hand. Like there's this moment when you had the realization that, wow, you were holding in your hand something that was going to be a huge change in your life. And I would say that most people remember the first time they interacted with Generative AI and got out of it. Uh, one of those results which now we're starting to get used to. But let's not be jaded. It's pretty extraordinary to have a natural price icon.
Andy Sack: The holy shit moments with the software, right?
Brice Challamel: So there's this momentum that kind of kicks the whole chain reaction. And then, uh, what's going to happen is that you need to trust the population dynamics. You need to trust that some people are just more comfortable with change and will adopt this heads on and just experiment with it, try it. They will have less fear, uh, be more affirmed in their past or in their experience with trying new Things, it's part of what they do or how they're perceived by their environments. And they will explore the field and they will show the others
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Brice Challamel: the rewards and the risks of trying it. And so that's why I want to say these things don't happen overnight either. From the moment that I saw the first iPhone in my life to the moment that I only saw smartphones all around me, it was, uh, almost a decade. Even though smartphones are such fantastic tools, they were not an overnight adoption. It wasn't like two months and then we're done. It was more like 10 years and then we're done. And so, uh, you have to give it time. Uh, transformation is more a catalyst to accelerate this chain reaction than it is an overpowering effort to make it happen. It's going to happen anyways. It's more a matter of how fast can you get there, how safely can you get there, and how much quality of outcome can you get out of it, uh, in this amount of time? So trust, uh, the chain reaction. Trust the people who want to get there. And to do the most of technology, uh, give a megaphone to those who have found something interesting. Don't speak for the change, let them speak for the change. And, um, it doesn't matter the scale, because if you have a million people, then start with 10,000, and if you have 1,000 people, then start with 100. Those mechanisms, they scale amazingly. They are very efficient for this. Um, and just keep listening and also keep listening to people who are not on board. Most often, if they are resistant to change, and I mean actively resistant to change, it's because they care. It's because they care about the company, they care about the outcome, they care about the job, and they've seen something, but it's not going to work from their perspective in using this technology for the job. And if they care, then I care, then I want to listen to them to understand why we need to get out by the way of this crazy Black or White 0 or 1 conversations in which we talk to each other instead of speaking with each other. And, uh, especially in the world of enterprise, this should not be an environment of opposition principles, but of tolerance and listening skills to people who have a very different perspective from yours because they hold a piece of truth and they would never be so active with it if they didn't profoundly care about the future of the company. They would just then go there. They'd be like, all right, sure, AI, uh, go, don't go. I don't care. They would be Careless, but they are not careless, right? And if they are not careless, then you should be attentive because this is how also you improve either the technology, which still has a lot of improvement ahead of it. Let's just by the way, acknowledge this is in the infancy of the technology right now. Improve, uh, the way that you bring it to people, the way that it's made available to them, the client, the agents and so on. Improve the learning programs and the way that you educate, make everyone aware and help them wrap their mind around it. So even the people who oppose the change, they are on your side. They are also solutions. They are the ones who would show you the little problem that you didn't perceive because you were into your own momentum through your own motion. And they are reality check to your desire. Right? You want change to happen fast. You want it to be fantastic and brilliant. And to find yourself on the podcast with Adam and Andy, pause there for a second. Listen to people who have a very different opinion, who are vocal about this because they hold the key to your future and to your common future. Once you've unlocked that key, those people will jump immediately from one end of the spectrum to the other end of the spectrum and become the biggest champions ever.
Adam Brotman: Great.
Andy Sack: It's a really wonderful sentiment, uh, particularly in our day and age in our world, not just applicable to AI, but to other areas of life, uh, particularly following really contentious election in the United States. So with that, Brice, I want to tell the leaders that this conversation was just a smattering of what, um, I think we've now spent four hours together, um, talking and we did our best to summarize our prior conversations in the book. So I encourage everyone to check out AI first, the book, and particularly, uh, the chapter on Moderna, uh, because there's a lot of gems in there about how to proceed, uh, with AI first Digital transformation. I want to thank you, Brice, for the four hours of time and really educating Adam and Aya, uh, because you really are a business leader who's thought about change generally and digital transformation specifically as it relates to AI and being AI first, uh, more specifically, more than anyone that we had met. So thank you for your time, um, and for everyone. Thanks for listening to AI first with Adam and Andy and in this case, Brice. Uh, to stay updated on the latest in AI and access exclusive content, check out Form 3, subscribe to our email list and follow us on LinkedIn. We truly believe you can't overinvest in in your AI learning,
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Andy Sack: everyone. Onward, Adam. We just got done with that session with Brice Chalamel from Moderna. Uh, let's do our, let's do our.
Adam Brotman: Debrief, our post game wrap up. Brice is awesome. I mean you can see for any of you who just listen to it, uh, he's probably the leading expert on AI transformation in, in corporate setting in the world. Like he, he literally was working on that before there was even chatgpt. He was plucked out of Google for that purpose by Moderna. And as you could just hear like he just gives these incredibly thoughtful answers, deep, thoughtful answers to why they're doing it, how it's transforming work. It's much deeper than you and I are ever allowed to go in most of our days because we, we're usually trying to like get to the brass tax of like, should they do this, what systems do they use? How does this even work? And so to hear him at that like, level, it's almost like talking to someone from the future. And he's explaining uh, how this goes. And I, I, I thought it would be worth maybe starting out, you and I by saying that there was a stat he mentioned and it kind of went by and we both talked about it, but it was, he talked about how they're at ah, Moderna, uh, with 5,000 employees, they just crossed the 1 million chats per month mark amongst their employees. That's a remarkable implementation success of a whole workforce using AI every day. And when you and I both pressed them for like what's the outcome? Give us examples, you gave some examples of some bots and whatever. But you know, man, you know what I think it is? I think it's a million different little uplifts that happen every month at that company. And they compound and they aggregate to just a tremendous amount of qualitative and quantitative throughput and productivity improvements for the company. And you know, it's almost like self evident if you have a million of them a month that it, that that's going to be giving you tremendous uplift. And he almost talks about it that way like as in, well there's a million of these things and it's transforming the way we work and we're obviously so much better for it and it gives us back so much time to do these other things and we're sitting here going, you know, how do you, how do you quantify that? You know, but the truth is, I.
Andy Sack: Mean pretty self evident our job and our this whole podcast is about really about translating AI into real world business use cases. The uh, successes and failures of business leaders trying to transform their businesses with AI. And then along comes Brice, who's really, I agree with you, like totally a leader, incredibly smart and intelligent. M. There's a lot more about this than you and I, uh, and is more nuanced and articulate and academic. And so when pressed on, can you, you know, what would your, what your would your other executive. He can't. He doesn't answer any question straight with a 1, 2, 3. We have a translation job between Brice and, and our listeners. And I think you, you zeroed in on really the one segment which was the most substantive that I think struck both of us, which was a million messages per month.
Brice Challamel: Yeah.
Andy Sack: The fact it was 1 million messages a month and he told us that just as we were ending that it's growing at 20% per month. Uh, which is a staggering growth rate for any digital product. Yeah. So it's really, it's 6,000 employees generating a million a month. Going to a million two per month next month.
Adam Brotman: Yeah. I think it's interesting because we were like, well, where are you getting the biggest bang for your buck or where, you know, what functions are getting the most out of it?
Andy Sack: And yeah, we wanted to, we wanted a clear success story or failure story. And he basically said, oh, it's where the, there's data and there's a need to process that data quickly, which is a good answer for a success. But didn't really give us like, didn't give.
Adam Brotman: Yeah, he, he, because he was coming, you're right, he was coming from the perspective of, hey, it's happening all over the company. It's almost like peanut buttered across the company. And at that point you're like asking me to tell you who's getting the most out of their computers, you know, like, I don't know, like, uh, you know, everybody and not everybody.
Andy Sack: Yeah.
Adam Brotman: And there's some people that are better at, you know, spreadsheets and emails and using, using the Internet than others, but everybody's using it on some level, right?
Andy Sack: Yeah, you're right. And for his answer to be the number one use case was, um, employee benefit, which I totally believe that the employee benefits program, which is a short term decision that needs to be made in a couple of weeks and it's incredibly family to
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Andy Sack: family. Like, it's a great example of where AI could be useful. I'd be willing to bet that the executives would not pick that same ex use case as the one that provided the biggest roi.
Adam Brotman: Yeah, that's right. That's right.
Andy Sack: Anything else stand, Anything else stand out that you'd really, that you'd want to translate for our listeners.
Adam Brotman: He said something about the transformation of the way you work. It's not just, it's not just the tactical examples that we were eager to get. He was saying if you're using it all the time and really understanding, I like to use some of the words that we use, maybe you feel good about us. He talked about if you're proficient, if you've been educated, trained and are proficient and you're bringing it to AI to the table all the time. He's like, you can't help but change the way you work. He mentioned the example of a transcript of a call and a transcript of a performance review or those kind of things. He said just the act of trying to record it and then feeding it to AI You've already transformed the way you work. Like regardless of what comes out of the other end, that AI summarizes and gives you these pockets of things to think about and then you go in and you edit it and you give a great performance review. You've, you've just up leveled and transformed the way you work is what his point was. And I, and if that's happening across the entire organization, I think that's something you and I probably should hover over more. Which is a, uh, true AI first organization sort of transcends just in improvement in processes, in a speed and productivity lift. And it becomes a different company, it becomes a different workforce. Your leg just went off again. And um, and so I don't know, that struck me as something that um, because you and I keep trying to visualize like what does a truly AI first company look like? And we talk about it and he's actually living in that right now, I think.
Andy Sack: Well, I mean the thing that, I mean I'll just add the thing that he already said that, you know, he, yes, he said that. And he also stated that he felt like he was in the first inning, maybe in maybe the end of the first inning of digital transformation at Moderna and that really, that that's, you know, they still have executives that aren't using it as much as other people and they like, yes, it's broad based usage and yes it's growing 20% a month. But, and, and yes the 6,000 people are performing at a higher productivity and it's early even at Moderna. And so that's what he expects to come, let's just say in the next year to two at Moderna, both as the technology continues to advance, but also the way in which they work changes.
Adam Brotman: Yeah, yeah. You know, he made a comment at the end about like, hey, here comes AGI. And by the way, it doesn't mean it's coming in six months. It could be in 18 or 28 months. But he's like, it's in the nearest Horizon. It's not 10 years away. It's, you know, three years away or four years away or whatever. And, and meaning, like, you know, infinite memory, text to action, agentic systems that haven't even, like, landed yet. And think about with a million chats a month, when those capabilities start to come.
Andy Sack: I mean, it's the thing, you know, the thing that struck. I mean, this is me just reacting to the, the, you know, he's, um, he's really what you want in the, in the type of person to assist in, in leading change. Like, his answer to your question. Like, you tried to summarize and package up what he was saying in language that our list. That was more succinct that our listeners could understand. And he, he thanked you for positioning your question the way in which you did. And he also was like, you know, at the end, he, like, made the comment about, like, the people that are naysayers are saying that because they care. He's just a very thoughtful, respectful, inclusive, yeah. Human being. Which, you know, which makes him a good, uh, a good change agent. And my sense is he's, he's getting a lot of credit, but he's not, he doesn't, it doesn't seem like he's out for the credit.
Adam Brotman: He definitely seems like somebody who's, you know, he's living the thing that we're, we're trying to visualize and, and encourage and facilitate companies to start a journey on. He's like, in that journey, and you can, you can just hear it, you know, like, he, like, remember, I think I may have mentioned either on the podcast or after I said, oh, yeah, when he talked about, like, I remember when we were at 2,000 chats a month and 5,000 chats a month, and he's like, yeah, a million. And I reminded me of Starbucks mobile order on pay. Like, at some point the thing just blossoms and it's just alive and it's just happening. And, you know, he definitely talks like someone who's in the middle of that. And that's what's so great for you and I and, um, our readers and our listeners is like, I think we picked a good case study. I think
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Adam Brotman: Brice is awesome, and you can tell from our conversations with him, but I just feel like there was a re. We were drawn to the moderna story. We didn't even know about Brice really, other than like his name was in this one thing. And, and then when we got to talk to him we're like, oh my God. This wasn't like some bolt on initiative shiny object. This was like an incredibly multi year thought through thing. They brought the team in and they did all stuff before even chatgpt came out. He's an inspiration and I do think you have to translate it a little bit because it's like, wait a minute, like, like for example, he said at the end, he said he used words again. If I was listening to it or watching a transcript of it, I would have highlighted where he said. I asked what, what does it take to get people that aren't using it enough to sort of get encouraged to use it. And he said, oh, it's like the iPhone. And you know, you just gotta like give it time and like eventually there'll be this chain reaction and all of a sudden it's everybody. But it could take eight years and some people go fast. I was like, yeah. And um, by the way, without revealing anything confidentially, I don't think he, he was telling us that like you know, basically 80% of their workforce, I mean it's been, it was in our, it was in our case study in our book. You know, he's talked about it before. Like, he's talking about like 80% of people using a lot. That's how you get to the million. So he's like, I'm not worried about the 20%. They'll get there on their own schedule. You know, whereas we're trying to get to, we're trying to get companies to get leadership to buy into this and you know, get kind of get a visual of it. So I'm hoping people listen to this and are inspired.
Andy Sack: Yeah, I mean I think that like I said, he's the type of person that you want to lead change and you can, if you, when listening to that episode, even though it's academic, he sounds, he is and sounds academic. He's incredibly insightful and incredible and definitely has the right Persona to uh, initiate and foster change. It's like a gardener who, who plants seeds and you know, very methodically waters it, makes sure sunlight comes, but doesn't, but also knows that you can't rush it. Right. Like you have to do it. And I kind, and I balance that with really many, like uh, some of what we're trying to do, which is like we really do see the kind of change that he's talking about. Like we're, we're very interested in what that new way of working and what does it mean to be AI first and really how much, but how much ROI gain can you get to out of being AI first. And we believe that it's going to, that, that results in really economic EBITDA growth is what we're. And we know that executives will push for that and need to see that in order, some executives will need to push for that at UM and need to see that in order to make the kind of time investment, economic investment and technology investment to get people to change. And we're looking to shine a light on that, on that playbook, uh, that roadmap.
Adam Brotman: So it's almost like we're going to look back in a year or two and it was right there in front of us all along, even with Moderna. In other words, even he's not going to say it because they're a public company and he's got to be careful what he says and he's really responsible that way. But on the records, Stefan Bonsell, their CEO, went on the record and said because of these initiatives they're doing, you know, five, six thousand people, that company are doing the work of 100,000 people, he said. And they talked about 3 to 5xing their throughput of um, ability to get innovative new products out the door and support them. So it's funny, I'm realizing like it was right there in front of us. He's, he has to be careful with, he has say to us and I respect him for that but like it really is what we've always thought which.
Andy Sack: Is like give me those numbers again Al.
Adam Brotman: So Stefan Bonel said they're doing the work of a hundred thousand people. He believes with uh, only five or six thousand people. I, I, to be honest, I'm not, they might, they might not like me pointing out that he said that. But it's, you can go along the way he said it, he said it. And then you know, maybe there's a little bit of hyperbole in there. So fine, maybe it's 50,000 people, it's still 10x. Right. And then there's another part where they talked about supporting, I want to say three to five times more products over a five year plan than they would have originally been able to support. And so those are pretty good numbers. I mean, by the way, just to put it into perspective, when you and I talked to Professor Ethan Molik, for the conclusion of our book, we were like pointing out the, the Harvard Business School BCG study that he led. And even though he's at Wharton, but he led this HBS BCG thing.
Andy Sack: Yeah, yeah.
Adam Brotman: And he was just like, oh yeah, that just proves that AI can do the work of a BCG consultant. And yes, even before 4.0, that was with ChatGPT4. You were seeing what, 40% quality uplifts, 25% productivity uplifts. Like, just stop right there. That's on a prior model, not even, uh, at the advanced system level we're at today.
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Adam Brotman: And molik's like, yeah, 25 to 40%. Quantitative and qualitative lifts across every function is what you're talking about. If you, if you do what Brice and the team at Moderna did, which is like fully ingrain it into the way they work, you know, like it's, and we're sitting here going like, what's the ROI on that? And I think everybody that really is in the thick of it is saying, guys, it's kind of obvious. It's, you know, it. Massive productivity lift.
Andy Sack: Let's double click on the ROI thing. I mean, I think this is not the first time or the last time that we'll double click on roi. And I continue to be on the fence because on one hand I see the common mistake and change efforts as on focusing on ROI too quickly. And if you listen to Brice, his, you know, his use cases are not driven by business function or department. They're not focused on roi. They're focused on increased productivity. And gave us a few examples that's on the one hand of roi, but on the other hand, like, you know, businesses and leaders run off of roi and they, they really want to be able to make the case internally, whether it's a hundred person organization, a thousand person organization, they want to be convinced that they're making good business judgments and, and measuring that in terms of impact on business and EBITDA growth or net income growth. Profit growth is something that leaders are going to want to do. Where do you come down on that?
Adam Brotman: I think that, oh, uh, by the.
Andy Sack: Way, we struggle with this as a business.
Adam Brotman: I actually think that we, I think that we're on the verge of overthinking it. And what I mean by that is, I mean, I think it's, we're talking about it because it, it comes up. So we're not overthinking it, but the reason we're on the verge of it is, remember you and I were on the phone with private, uh, equity guy the other day and he was, yeah, he was like, I was a skeptic of the Internet. I was a skeptic of the Starbucks card. He's like, yeah, he's like, I'm not skeptical. Yeah, he goes, I'm not skeptical about it because I think about dozens of use cases every day. And he, and he actually said, as a skeptic, I actually think that not enough CEOs are using this enough. And by the way, we've seen that from other private equity folks and other venture folks. Meaning, like, I mean we talked to multiple, right? They're all like, hey, portfolio company CEOs, wake up. This is like the Internet. This is like computers. So I think that's the answer. I think maybe it's because we're a little bit older and longer.
Andy Sack: Yeah, no, I think that's right. And by the way, I think oftentimes executives tend to be a little bit older and so. But if you talk to the younger generation, you know, my guess is all the first year associates right out of college, they're all bought in, hook, line and sinker into, into using the tool. So.
Adam Brotman: But here's the thing though. It's been, I mean it doesn't seem like that long to us because we're middle aged guys, but like, you know, it's been, it's been a moment since there's been a general purpose technology like the Internet. I mean it's been at least, you know, 30 years, 40 years depending on how you want to look at it, that you've, I mean the Internet came along, let's call it in 95 when the Berber came out, right? So like 94, 95, whatever it was. So we're, that's 30 years, right? So like, and then computers were 40 years ago. So for us we're like, oh, this just the last wave. But like it's been an, it's been an entire, you know, young workers lifetime since they were born that there's been a moment where you're like, yeah, you don't need to like overthink the ROI on this. This is this the holy moment that you had. And like the level of productivity times a million chats and modern is seeing like it's, you can put it in the bank that like it's, you know, they'd be crippled without it at this point. And it gives them a competitive advantage over those that don't get it.
Andy Sack: Uh, you know, you're, you're reminding me of the one other thing that we Talked about just briefly, ever so briefly after the. The interview, which we have not talked about here, which I think absolutely bears comment, which is your, Your whole thing about demand, the demand for services as being the driver of the business versus the productivity gain. Can you. You said it so well earlier. You were making the point that that productivity gain gives you of a. Across a million messages a month. You talked about it being like peanut butter and it's being spread, being used widely. And in our prior interview with Hugh at the Sounders, he talked about basically going into the annual planning and having an extra three hours per person, per employee, per day or per week, whatever the exact number was. But extra time that suddenly can be used for additional stuff. But the additional stuff is like. Is totally. Productivity gain is totally dependent really on the use of that.
Adam Brotman: There's demand. Yeah, that they're. Yeah. What I was saying is that it doesn't. So I'll give you a good example. This
01:10:00
Adam Brotman: is an easy analogy. So go. So I'll talk about Starbucks. That is, you know, one of the few things in life. I know. So at Starbucks there's a certain amount of throughput and capacity that, that production line from the. Whether you mobile ordered or not, like from the POS to all the way through to them making your drinks and warming your food and gathering it up and putting it on the end. Okay. So when there's. You uh, get to a certain point a number of orders per hour where like being able to be more productive and have more throughput and capacity really matters. Because every single bit of improvement in throughput and capacity you can get more people through. But throughput and capacity, meaning, I. E. Productivity doesn't matter if there's not a line.
Andy Sack: Right.
Adam Brotman: Like you can be.
Andy Sack: That's right. There's not a long line.
Adam Brotman: That's right. So like I, I lived through that notion like it's top of mind for me to. So if you go now extrapolate that out, uh, to the business level. If there's. If you're a growing business and there's demand for your services and there's like. Because you're. You've got product market fit or you've got a great brand or there's some secular change. Allah. Nvidia, where like everybody wants your product. Well, like productivity matters a lot at Nvidia right now. Like literally like they can up their sales by billions of dollars with more productivity right now in throughput. And that's because there's more demand than there is capacity. And. But if you. That can Go the other way. Right. And all of a sudden it's like, it doesn't matter how much more productivity you have if the demand's not there. So that, that has to do with productivity and throughput. There's also like, the ability to use AI to generate demand by doing segmentation and insights and personalization.
Andy Sack: Well, no, but your, Your point is super valid in the case of Moderna because they've, they've got increased productivity, as you say, increased supply, and suddenly RFK Jr is in charge of the. Maybe in charge of the health and Human Services and, you know, and if he has his wig. The Moderna stock has suffered because there's a lot of skepticism about the political.
Adam Brotman: Yeah, yeah, yeah.
Andy Sack: I thought that was a really, I thought that was a really good point that, you know, it. The productivity matters and demand still matters a lot for a business.
Adam Brotman: Yeah, it's interesting, right? There's a whole, like, elasticity of demand and throughput and all that stuff that you gotta, like, think about. And so, I mean, you even said it not to go to the dark side, but you're like, well, this all lead to layoffs. And I said to you, if you're in the customer service group, you're gonna want to be, like, managing AI agents and be in the level two customer service side of it, because level one customer service is probably going to all become automated through AI. However, outside of that, I think it depends. I think whether AI is going to take your job or not totally depends on the circumstances of the company too. Because like I said, like, if, if they just. If there's like so much demand, then AI is going to just augment what you're doing and you can take all those little hours they save up and they can redeploy them into these other things they wouldn't otherwise have been able to get to. So, you know, I mean, it's an.
Andy Sack: Interesting, you know, given Bryce's talk about the, about invertebrates and left brain and right brain, which I thought was really well stated of, you know.
Adam Brotman: Yeah.
Andy Sack: When you're relaxed and comfortable, you're excited for change, but when you're fearful, you're not, um, you know, the, the application of this broadly, there's going to be increased media attention for sure, on layoffs, and there will be some layoffs because the nature of work is going to, for sure change. And that's going to make, I, um, think that's going to make employees skeptical and fearful, um, which makes change harder. So I think navigating that to a calmer place, uh, to be able to capture the genuine great things about generative AI.
Adam Brotman: Uh, harder, 100%.
Andy Sack: And one last thing. We put together a PDF case study based on Bryce's insights from today on our show. It covers the five superpowers of AI and so much more in a really nice, concise way that allows you to share the knowledge with the rest of your leadership team. You can get it by going to forum3.com podcast. That's forum3.com podcast. And there you can download it totally for free because we're nice guys, we care. So that that's our gift to you. Thanks and have a great rest of the day. Onward.
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