How Generative AI Changes Creativity

Most enterprise AI stalls at pilot stage. Publicis Sapien is already powering Fortune 100 companies today. Publicis sapient AI that's built to deliver. Learn more at Publicisapient.com Don, you are an artist based in Los Angeles. I'd love to hear you talk about that moment that you realized that, okay, wow, this generative AI is doing incredible things. And to what extent did you at least initially feel that existential dread?

Yeah, so, I mean, it really kicked in pretty, pretty fast. I would say, like, within the first couple of hours of playing with these tools, it started to sink in that this was going to fundamentally change what it meant for the value of my own work. In the past, I made a lot of money off of kind of how much time something used to take me. Whether that's an augmented reality filter for a client, a commissioned art piece, a 3D model, a 3D sculpture, a video edit, an animation. All these things used to take a lot of time. So if it took a week, I might be able to charge more, and if it took a day, I would probably charge less. So when I started playing with the earliest text to image editor generative AI tools, I was realizing that the iterations of ideas that I can get through and show to a client shrank the time to almost zero. You know what would have taken me a week to iterate and think of before having a sketch that I could show a client? Well, now that just takes a few seconds. And so that suddenly hit me hard because I had to really rethink what it meant for me to exist as an artist. It's going to really change what it means to do artwork professionally. It's going to change what the expectations are for artists as well as clients. And so the dread really came from this idea that, well, I'm going to have to change a lot of what I thought my future was going to be.

Welcome to How Generative AI Changes Everything, a special series of the HBR IdeaCast. From prehistoric paintings in caves to an inventor's Eureka moment, to the collaborative imagination behind breakthrough products, creativity has always been described as a particularly human trait. But something strange can happen with generative artificial intelligence. Sure, your ideas can take shape faster when you use these new tools, but you also get ideas that you might never have imagined on your own. So who is the creator here? What is creative work in the era of AI? What is innovation in this emerging world? This week, how Generative AI changes Creativity. I'm Adi Ignatius, editor in chief of Harvard Business Review, and your host for this Episode. In this special series, we'll be talking to experts to find out how this new technology changes workforce productivity and innovation. And we're asking how leaders should adopt generative AI in their organizations and what it means for their strategy. Later on in this episode, you're going to hear from Jackie Lane and David decramer, management professors who research innovation. And I'll ask them how generative AI can change the creative process within organizations. But right now, I'm talking to Don Allen Stevenson iii. He's a video artist and consultant based in Los Angeles, and he's worked at the animated film studio DreamWorks. He also collaborates with freelancers and independent artists, and he's been using generative AI in his work for clients. Don, thank you for coming on the show.

Thank you so much for having me. I'm very excited to be here.

So we talked about that first moment when you realized generative AIs potential in your world. So since then, you're learning it, you're playing with it, you're creating with it. What have you learned about the technology and how it affects the creative process?

Well, for me, it's actually helped me to experiment a lot more with riskier, more out there ideas in creativity. Because in the past, it would have taken too much time to experiment with the vast creative ideas I would like to do. And so now, because a lot of that iterative cycle is replaced with just kind of instant feedback, I'm actually allowed to explore and do larger scale projects, which has actually been really productive, really positive for me.

Can you talk about some of those projects?

Sure. So in the past, oftentimes I would like to tell more animated stories, but it takes a lot of time to create characters, 3D characters, to give them bones, give them the ability to move, to place them into worlds, to render them into the scenes, to relight them. All of these steps are normally pretty time consuming for someone who just wants to tell a short story. So all these things in my past I might have resisted, but now there's tools like Wonder Dynamics that came out that basically streamline this entire process of creating characters that are embedded in live action video. Now, instead of me having to go and animate characters manually one by one, I can just film with my phone camera somebody acting and performing in front of a camera. And when I process that footage, it comes back with a character replaced in the person's place. So if there was once an actor raising the right hand and waving, I would get that footage back and it would be my 3D character waving and the actor would be physically removed from the frame and all of the pixels cleaned up. And that would have taken me weeks. And now it could be done in like an hour.

So that is amazing. That's an amazing example. I mean, here you're talking about, like, we can all create Pixar. Yes. You know, sort of almost. Almost that level of quality.

It is that level of quality.

So does that mean you don't collaborate? You know that whereas in the past, not only would this have taken weeks, you might have been working with a team of people. Does this eliminate collaboration for you?

So some of the tools eliminate collaboration and other ones actually encourage it. I've actually been collaborating more on short films since using Wonder Dynamics, because I need actors, I need someone who can operate the camera really well. That being said, I don't need the same visual, massive size of a team to produce a short film. So the number of people has reduced. Now that I can kind of spearhead and streamline the effects process, I kind of have more time and energy to bring on more people if I want to.

Yeah, that's really interesting. It's sort of counterintuitive, but I think I get that, that it enables you to think bigger. And what's also interesting to me is, you know, we're talking about a technology and we're marveling at its possibilities. We're just a few months into this thing, so it's going to get better. It's going to do more, I assume.

Oh, yeah.

Can you talk a little bit about how the technology has improved even in the months maybe it is since you've been playing around with it?

Sure. So I've been playing with the AI tools for about a year and a half now, which makes me, like, really old school because. Which is so weird. Like a year ago, where the state of the art of artificial intelligence and generative AI was. People don't even care about it anymore. In the same way, one of the biggest changes I've noticed from the creative industry is moving away from just being impressed with 2D images and moving into a world where we're now expecting and being impressed by video that's generated and 3D animation and 3D performances and 3D characters that are generated.

So, Don, I understand you have a relationship with OpenAI, which is the firm that developed Dall E and ChatGPT. You mentioned that you sometimes feel like a dinosaur just because the technology is moving so quickly. But, you know, given the conversations you've had and what you've seen, what does the future Hold. I mean, do we. Will Generative AI kind of hit its limit, or are we going to see dramatic improvements to come?

So I'll start off and say that I'm going to speak from my own personal experience of what I'm allowed to say and what I think is public and available open knowledge and assumptions that I can make. So on that, I would say that we've just scratched the surface of what generative AI can do. I'm already very impressed with what it's publicly able to do. But to be honest, this is not even close to what it's going to be like in even a year from now. Because imagine you're trying to learn a concept, and maybe you go today to ask ChatGPT, I want to learn about the moon. How far away is the moon? And ChatGPT would do a great job at explaining that number and writing it to you in text and giving you a nice little paragraph about some science about the moon. What I think is going to happen probably pretty soon is you'll ask the same question. And imagine you say, well, can you help explain it to me? I'm more of a visual learner. And so then chatgpt or a model like it that might come out, might actually share an animation with you, an animation that would help explain the concept of the distance of the moon. Visually, we'll be moving away from having it be just text output to having it be image output, video output, 3D model output, 3D environment output. First, it might be a 2D image, just shows a moon, Earth, and maybe a line between the two. Then it will probably eventually become a video so you actually see stuff moving around. It shows like maybe the distance is being drawn between the two. And then after it's drawn, it then puts in the distance. And then eventually it's going to be 3D. It'll actually just pop up like a 3D model of a moon that it generates. And 3D zoomed in, picture of Earth, and then showing that distance generate visuals that would help accommodate the learning.

Amazing. So from everything you say, I mean, it sounds like you know somebody like you, who is creative, who is not afraid of technology in the sense of you're willing to roll up your sleeves and try to master it. But there may be people who are several rungs below you in the experience chain who, because of these tools, can actually create what you create. Almost. Right. A sort of Good enough version.

100%, yeah.

So do you worry about your ability to get compensated and recognized as an artist when all of Us suddenly have these tools at our disposal as well.

So I've actually in this last year, have been transitioning away from being identified as an artist because of all these AI technologies. Instead, I've been moving more into basically doing consultations, doing inspirational videos, public speaking gigs. Those are actually where we're going to pay the bills now as an artist, not the art itself. Unless you're a very specific niche brand that people already love and care about, it's going to be really rough right now for people that are only identifying as artists, especially if their output is solely digital.

So that's interesting. So you're not self identifying as an artist now, but what does it mean to be an artist now in this era of generative AI, where suddenly we have amazing tools at our disposal?

Yeah. So the good news is, if you're creative, what it means right now is you're able to bridge domains that normally don't talk to each other and have them interact in new and innovative ways. But someone who's a specialist in one category or domain, they're the ones that I would say are in the most danger zone for generative AI. Because if you're a specialist and it's a very narrow field of tasks, these are exactly the kinds of things that AI systems would like to get training from. It's a very specific, narrow data set. They don't have to work as hard to generalize if you're a specialist, but they have to work very hard if you're a generalist at trying to clone and copy what you do. So if you're a creative, that's being a generalist, you're safe. If you're a creative that's being a specialist, you're not safe at all.

The revenge of the generalist. I like this world already. So, Don, as this technology is starting to take shape and potentially reshaping your world, my world, everybody's world, how do you know? So let's say as a creative, how do you make sure you're part of what it does in the future rather than getting steamrolled by it? I mean, what's the best wisdom so far?

Yeah. So if you're a creative and you're trying to figure out how not to get left behind right now with all of this innovation in AI, the main thing that you can do is actively experiment with the tools, the ones that are too scared to even touch this stuff, there's like no space for them, unfortunately.

So Don, given all this, is the product that you are giving to your clients going to be different in this world.

Significantly different. The main way that it's going to be different is that now I have to show my work on how I got to the output for my clients so that they can actually see the human effort, the human fingerprints, the human touch that was put into whatever that output is. So if you're a video editor, your fingerprints are showing screenshots of what your sequencer window looks like. If you're an illustrator, then your work is showing a time lapse of how you actually made that piece. If you're a writer, it's showing all of your rough drafts and all the versions that you went through before you got to your final thing that you wrote. These are just a few examples of showing your work in a world where the output is not going to be enough to understand the value.

That's fascinating. Yeah. None of us has had to show their work since. Since school. Right.

It's like, oh, because the output was the most important thing.

Right.

And then now it's like, well, how did you get there? How do I know that you didn't just generate this whole entire podcast with AI using voice synthesis?

Interesting. So there'll be a whole parallel industry that's about trust. Yes, that's about trust and verification. And that is a really interesting observation.

And the reason why I feel like I need to show that is so that people know that it's me who made it. They're not going to believe me when I say I made this anymore because it could have very easily just been generative. But if I can, show me making that thing that someone bought, oh wow, there's a real human behind there. Oh, wow. It's a real human artist. They put a lot of effort. The value is clear.

Dunn, thank you for speaking with us. Thank you for sharing your experience.

Of course. So happy to be here.

Coming up after the break, I asked two experts on innovation. How does generative AI change the creative industry and the creative process at firms? Stay with us. Most AI delivers promises. Publicis Sapiens just delivers enterprise ready AI that works. Not pilots, not prototypes. Modernization up to 75% faster. Cost cut in half billions unlocked in new revenue trusted by Fortune 100 companies because quite simply, what they build works. Publessis sapient AI that is built to deliver. Learn more at Publicissapient.com. Welcome back to How Generative AI Changes Creativity. I'm Adi Ignatius. Joining me now to discuss how generative AI is changing creative processes and innovation within organizations is Jackie Lane, a professor at Harvard Business School, and David Decramer, a professor at the National University of Singapore Business School, David co wrote the recent HBR article How Generative AI Could Disrupt Creative Work. Jackie. David, thank you for joining me.

Super excited to be here.

Thank you, Adi. I'm really happy to be here.

Good. Well, Jackie, I want to start with you. You have studied innovation at NASA, at hospitals, at big digital firms. I know you're now looking closely at Generative AI at ChatGPT. You know, help us figure out what is unfolding now. What can generative AI do already today, let's say, for companies that want to innovate with it?

Yeah, so I study how we generate ideas and how we evaluate them. And so a lot of my research focuses on crowdsourcing. And so when I first heard of, you know, generative AI and the capabilities of ChatGPT, I thought, wow, there's just a lot more capabilities and possibilities that are available both from the idea generation side to diversify the kinds of ideas, you know, more innovative, more breakthrough ideas. And then also there's implications for how do we pick and select that. And so I think that's a super rich and exciting time for companies with crowdsourcing.

If you want to, you can sort of find the human fingerprints that are on ideas as they develop. With, you know, with generative AI, it's hard to tell where these ideas come from. I mean, you know, it's a sort of mashup of all knowledge. And I'm never sure if it's something lifted almost, you know, plagiaristically, or it's a trope that the bot has come up with. How do you deal with the quality and the reliability of what, what a chatgpt is generating?

Oh, that's a great, great question. I mean, we need human agency in this too. And so for example, if you're trying to think of how do you do the business model for a real estate startup, you could get ChatGPT to give you some ideas. The question, you're right there is the question of quality. I believe that there's also powers of using ChatGPT to help us with filtering these out. You know, in the beginning it could be filtering out the low quality ones, but going forward we can get better at training our models to come up with those better quality ideas as well.

And when I think of, of how companies innovate, how they experiment, you know, you think of sort of design thinking approach, rapid experimentation, you think of brainstorming, rapid prototyping, all of that. What's the role of generative AI in some of these processes, do you think?

Yeah, for sure. I mean, there's a famous study that was done by Hargadon and Sutton on the design consulting firm ido. And the competitive advantage for those designers was to be able to take and understand knowledge from one domain in one technology or industry and apply it into another one where it wasn't known. And that's. I think one of those beautiful things that ChatGPT can help us with is to give us those kinds of recombinations from different industries and domains in ways that we might not necessarily think of them ourselves. It's not like everyone has this kind of experience or this exposure that the IDEO designers had. But ChatGPT can enable people who don't sit in those cross boundary positions to be able to come up with those types of recombinations.

So David, I want to ask you, I mean, one of the interesting things about this new technology, it's not like a supercomputer that churns out information faster than we've ever seen. It's capable of doing things far more interesting than that. And there are examples of architecture firms using generative AI to churn out new designs to share with their clients, drug companies who use it to conjure up candidates for therapies to study, companies creating imaginary customers to interrogate as part of product development. It was really amazing uses. Reflecting on all this, can this help make firms better at creating new markets?

Creating markets at the moment I'm not too sure about it because not only for generative AI, but AI in general. If you look at how do they create value for companies, usually it's promoting efficiency, making sure that people work better. But I hardly see that AI is really capable or even being used to create new markets. I think that's something that's not really happening yet. So that kind of value I don't see being created that easily. I still believe it's an augmenting tool, but humans are in charge. And the reason why I'm saying this is because I look at creativity in the following way. Creativity or a creative solution for me is something that is new. It's a novel idea, but it needs to be useful. It needs to be useful to solve something that humans care about. And this is where AI in general is lacking. It doesn't have that sensitivity. So AI can do the first part. It's new, I generate as many ideas as possible. But then we need to verify, we need to edit and we need to see is this something that's useful? Is this useful to Solve a problem that we care about.

Yeah, yeah, well, those are good questions. And then there's the whole kind of ethical concern, and I guess I'm interested, David, to what extent are you thinking about ethical considerations when you're using generative AI in the creative process?

Well, I mean, first of all, let me say, like, with any new technology, if you look in the past, of course, if we didn't take the risks, many of the things that we know today, we wouldn't have if we would shut it down right away. Having said that, I'm not someone who likes to see, hey, let's see what happens. And then when it goes bad, when it goes wrong, okay, then react. So we can anticipate already, and some of the things we can anticipate, I think you've referred to already, is it has such access to the World Wide Web, it scrapes everything, it knows everything. It has all these data sets available. Obviously, one of the things that comes to mind is that IP rights, the intellectual property rights. So that's one ethical issue. The second is what I see. ChatGPT is being used in terms of its applications a lot. And one of the more recent ones you can see in the US is like, can it replace doctors, for example? Let's say you're sick, you're developing a flu, you don't know exactly what it is. So the first point of contact will be chatgpt to see, like, okay, what will be the diagnosis that AI brings forward? And then if it's severe enough, you may be transferred to a human doctor. I don't want to end up in a world like that where insurance companies are going to decide, these are the decisions about your health. So we really have to think about again, how will we use it?

So, Jackie, are there now early good practices that are emerging in implementing this technology into workflows, into corporate creative processes?

Yeah, no, I think that's a great question. I mean, right now, everything is in its infancies, but a lot of, like, the way that work gets done in companies is at the group level. People work in teams, multiple teams, like in different groups. And I think the question is, how does ChatGPT or generative AI fit into that workflow? And so if we go back to the basics of idea or group brainstorming, I think there's a lot of evidence from studies that have shown that, you know, group groups tend to come up with better ideas when you do it alone first, and then you share your ideas with one another. So you can imagine a world where that process still exists, but you could insert generative AI into that individual aspect. Right. And so instead of you coming up or an individual worker coming up with some ideas and then sharing them with the group, you use Chat GPT as your co pilot or as your assistant to help you think of some other ideas, some maybe more wacky ones, maybe some that wouldn't have necessarily come to you and it encourages serendipity. And then you come into your group and discuss the ones that may make the most sense. And so that's, you know, I think maybe thinking about it more in terms of, you know, how it fits into our workflow can help us disentangle, you know, what it means to have these tools at our fingertips.

Yeah, I agree with Bot as my copilot.

Yeah, exactly. So I think there's that. And then the second thing is it's clear that, you know, uptake of ChatGPT is not universal. Right. And even in our small pilot study that we were running, we can see that there's differences by, you know, where you live, your age. That's an important aspect because if Everybody that's using ChatGPT is of, of a certain, a demographic group, then in order for this to really democratize the workplace and help us come up with ideas, there needs to be training, training on how to use ChatGPT and how to use it with prompt engineering to help people understand the capabilities and the potential and also, you know, maybe the challenges and the drawbacks as well.

Yeah, it seems to me, I mean, look, I think most of us were introduced to this technology in November when suddenly it was available on a mass scale. And what you're getting at, Jackie, it seems, is that there will be new job descriptions that we don't quite know what they are yet. Right. I mean, it's about the prompting and then it's about the analyzing what comes out. But those aren't small things. And if you were advising people who are entering the workforce and want to succeed in a world where generative AI is dominant and not get switched, swept away by it, what should they study about mastering this new skill and being ready for this new era?

Yeah, I mean, I think a couple things. The first one is, I mean, don't be afraid of it. You know, I've talked to people who have said, oh, like, I'm nervous about, like, you know, what it is, but, you know, a little bit of encouragement and then, you know, people start using it and the best way is really to practice. And then the second thing is because the output is so dependent on, you know, what us as humans put in. And I go back to the prompts here. Take a prompt engineering course. I mean, there's free ones online. Andrew Ng has an amazing one on Coursera. And then also think about, say, like, templates that can help you. And I think just, you know, those kind of two things. And the iterative process of using Gen AI can really help train and, and help people who are just entering the workforce.

David, I want to come back to you. You talked about the tension between technology and the human in the creative process. Traditionally, certainly, we've thought of creativity almost without fail as something that is uniquely human. It is what we do that a machine can't do. And now we're in a somewhat different world. Do you think that generative AI will essentially make us all innovators? Obviously, with caveats. We have to figure out what we've got. But doesn't it. There are those of us who say, I'm pretty good at putting stuff into practice. I'm not a great innovator. Aren't we all great innovators now with this tool at our fingertips?

Well, yes and no, but that depends on the economic model. In my view, if you look at the output of AI as basically the output of a job, then, yes, we're all innovators because we're all prompters now and we let AI work for us. Basically, it's cheaper, it's more efficient, makes you efficient. So your job will be a prompter. If we live in that economy, yeah, everyone will be an innovator, but a restricted one, and I would call it okay, then we lock up humanity in the data of the past, because everything that's new now is generated by AI. We just need to prompt it. We're not innovators. If we have an economic model where I do believe people will value authenticity still. So is it a human that created the end game, the end product, the end idea, the solution? Right now, studies, and our own studies show this as well. People still see authenticity in their mind as something human, but not related to AI. So they don't see AI as authentic in terms of moral ways, in terms of creative ways it can generate. But the real authenticity still lies with the human being. So it will still be important from an economic point of view that customer stakeholders see that the final product is one, that it's handpicked to say so almost by the individual, by the human being. So in that sense, of course, the collaborative model, machine, human, and how they work together, that's the One to develop. And again, like I said earlier, we need to find the exact place that AI plays in it and the place that humans take in it. It's still up to us to make that choice. And just one quick example to illustrate this is, yes, we can see AI as promoting efficiency across the board. There's no discussion about that. They are a superior tool and they make us more efficient. But if we only adapt that point of view, you can also think in terms of work. Are we then looking at human beings as an employee, only as a task completer? Because then, yeah, great, generative AI is the way to go and the only way to go because it will allow us to complete our tasks more easily. But from the other point of view, you could also say, what does it mean to being a worker, an employee in an organization? Today, with Gen AI around, it may be that some of these tasks we truly enjoy as a human being. So do we really want to outsource this to machine? Do we really want to delegate it to machine because it may have impact on work satisfaction and in turn on the creativity of people in general? So these are questions that are still unexplored. And I find this from a humanistic point of view, a very important one, because it's still about creating the right work culture, which is motivating, inspiring for humans. So again, that collaboration between machines and humans is really going to dictate how we're going to build our jobs in the future and how we're going to do our business and what we can promise to society and our stakeholders. In terms of innovation, one of the.

Things that we write about in Harvard Business Review sometimes is how difficult it is for large established companies to innovate or that they need to rethink how they go about their business in order to be as innovative as, say, startups. I'm curious, Jackie, let me ask you, I mean, does generative AI change this equation? Where big dinosaurs that haven't felt very innovative and maybe really aren't very innovative suddenly can be, because everyone can be, potentially.

But I think this is where leadership really matters, right? So there's many reasons why I guess you call these old dinosaurs or the established firms failed to innovate. One of those is just like, you know, organizational routines, the way you're set up, the technologies that you're built on, you know, legacy technologies, it's really hard to change those kind of things. And so figuring out how you can incorporate generative AI into those workflows, into your routines, change the mindset of how people go about their tasks, that requires organizational change and cultural change, you know, and also feeling like the company is empowered to do that. And so I think we'll see. We'll see. And I think this is where leadership really matters.

Well, so let's end on this. I'd like to ask both of you. Jackie, let's start with you. I mean, what is it that senior leaders need to know about this technology and innovation, its capacity to assist in the process of innovation?

It's here and it's in its infancy, but my personal belief is it's here to stay and it's going to change the way that we come up with ideas within the workplace. And I would think of it as an opportunity and the potential. Just like how organizations started to use crowdsourcing in the last couple decades, Generative AI has similar feels to it. I think it's something that leaders should embrace. And then there's a question that we need to figure out, which is how the heck do we evaluate these ideas? There's so many of them. I mean, people have studied the fact that even when we had crowdsourcing with just humans, there were so many ideas that we ended up not picking the ones that were the most novel. Right. And this is a study that was done by Henning Piazunka and Linus Dallander back in 2015. Like we, we just, it's beyond our human capacities. So the question is, what do we do with that now? And what are the things that we can do within firms for leaders to start thinking about, you know, how we select those ideas that are not only novel but also useful and feasible that we can actually action on.

So, David, same question to you. What do senior leaders need to know about this technology and about its capacity to assist in the process of innovation?

Well, first of all, I like what Jackie said earlier. Don't be afraid. Just use it. Get to know it. Actually, we need our business experts much more involved today in any digital transformation. Because there's so many ideas then. Well, don't create chaos either. We still need to know which ideas are worthwhile pursuing. And this is where business experts are extremely valuable. Why are you in business? What is the purpose of your business? What is it that you want to achieve? You need to keep asking these questions because that's going to help the implementation and adoption of Gen AI in creating better solutions for the questions that you want to address. So purpose driven leaders are more needed than ever to know what their business is about because it's going to help the tech guys to make sure, okay, this is what we want to use Genai for. These are the questions that we want to see addressed and in the big range of ideas that we're going to generate that we know at least how to select what matters to us. There is great potential there. And I think it's Winston Churchill who said, we're not even at the beginning of the revolution. It hasn't even started. We're in the phase before the revolution starts. Well, at the, I think when it comes down to generative AI for a business leader, just be clear on why are you in business? What are you trying to achieve? Which questions do you want to ask? Keep asking questions. That's going to be your big contribution.

All right, David and Jackie, I want to thank you both for sharing your thoughts and being part of the show. This is. Yeah, the revolution is happening and it'll be fascinating to see where it goes. But thank you very much for being here today.

Thank you.

Thank you so much for me having having us.

That's Jackie Lane, a professor at Harvard Business School, and David Ducramer, a professor at the National University of Singapore Business School and co founder there of the center on AI Technology for Humankind. Before that, I spoke with Don Allen Stevenson iii, a video artist and consultant in Los Angeles. You can find his work on instagram @don alleniii. The next episode will be how generative AI changes organizational culture. HBR editor Amy Bernstein will host a conversation about adopting generative AI in your organization with the emerging best practices for how to do that effectively and ethically. That's next Thursday, right here in the HBR IdeaCast feed after the regular Tuesday episode. Now we talked about ethical considerations today. For more on ethics in the age of AI, check out HBR's Big Idea on implementing the new technology responsibly. That's@hbr.org Techethics this episode was produced by Kurt Nickish. We get technical help from Rob Eckhart. Our audio product manager is Ian Fox. And Hannah Bates is our audio production assistant. Special thanks to Maureen Hope. Thank you for listening to How Generative AI Changes Everything, a special series of the HBR IdeaCast. I'm Adi Ignatius. Most AI delivers promises. Publicis Sapience just delivers enterprise ready AI that works. Not pilots, not prototypes. Modernization up to 75% faster. Cost cut in half billions unlocked in new revenue trusted by Fortune 100 companies because quite simply, what they build works. Publicis sapient AI that is built to deliver. Learn more@publicissapient.com.