Nobody's job is going to be taken entirely by generative AI, in my view, at least in the very near future. But what will happen is that people who use generative AI will take the jobs of people who don't. I am Alex Kahn, Global Head of Content at Publicis Sapient, happy to be joined today by our Chief Product Officer, Sheldon Montero.
Hey, Alex. Pleasure to be here.
So Sheldon, you are even busier than you normally are, it sounds like, because you essentially put down what you were doing to focus almost entirely on this question of how are we as a company going to incorporate generative AI and how are we going to, what's our perspective on how we use it in our work with clients? AI has been around for a while. So I'm curious to hear what makes this moment different.
It's a great question, Alex. When I think about, you know, fundamentally what the role of product is at PS, and frankly, the way it should be in any organization, its product is about really realizing value for customers and the business. And so we look right now at generative AI as the thing that is going to transform how we work and deliver value to our clients and our customers, and also how our clients can create value for their customers. And to do so, you know, with some pretty exponential equations in terms of the value that can be delivered. So when I think about the role of product as accelerating the flow of value, right now, this is an enabler to really accelerate flow of value. So it's very, very compatible with my core job.
Talk to me more about the role because, you know, Chief Product Officer is a role that a lot of times exists at our clients as well. But what separates what a Chief Product Officer does, what you do for Publicis Sapient versus what a Chief Product Officer at a bank, auto company, retail company does?
So product fundamentally is a shift from outputs to outcomes. It's all about how do you orient what teams of people working together do in service of creating valuable outcomes. That is it at its core. When I think about Chief Product Officers at a digital native, at a large bank, or frankly, any institution, it's really about figuring out where is their value to be had? And then how can you mobilize teams of people to be able to get at that value, often in uncertain environments? We are really the people that help our clients in order to realize that value, work with their teams, alongside their teams, both in some cases being their arms and legs of the product talent, and in some cases actually playing the role of product managers and product owners, where we tie our results and the way we measure success to how they measure success. And we are very much tied at the hip. But it's this relationship of helping clients to get at value. And then there's the dual part of my role is also doing that for our own company. And in our case, a lot of what that means to us, if you think about us as a service provider, is very much around our most important product is our people, it's our talent. And so I spend a lot of time really making sure that our talent is the best that exists in the marketplace.
It's very interesting to hear from you that you view one of the main roles as a chief product officer is developing our people and helping make sure that our people are as empowered as possible. So what's your perspective when people say generative AI is dangerous in that it will displace people? What's your view on that?
Now, where the current state of the technology is, Alex, is tremendously exciting because every study that you see out there, and I watch these really closely, what it shows is that generative AI is being used in a way to fuel additional creativity, additional productivity. What is turning out in reality is that it's actually reducing inequality. So for instance, people that have a hard time initially putting pen down to paper and coming up with an initial set of thoughts, you get a starting point from which you can achieve a state of flow and get to a better product. It's changing the ratio between the time for that initial ideation, iteration, and polishing up. And it's these kinds of effects that are yet to become evident. But what is clear is that people who use generative AI are going to be fundamentally more effective than people who don't. Look, nobody's job is going to be taken entirely by generative AI, in my view, at least in the very near future. But what will happen is that people who use generative AI will take the jobs of people who don't. And so as long as we orient ourselves in a way that realizes that this is a really, really powerful tool that enables human beings, I think that's where the opportunity lies. Of course, we've got a lot of issues to solve with regards to the things that are being spoken about today, bias, hallucination. Look, but I think that all of those things are, in many ways, at least the bias pieces, are more a reflection of where humanity is versus where the technology is.
You know, thinking about how technologies sometimes have impacted society in the past, like even with the beginnings of AI and other technologies, we've often seen, unfortunately, when humanity does not proactively take that decision to say that the benefits of this will be equitably distributed, all it does is exacerbate, just more goes to the top, to the people who already had, to the people who can already do, and it just worsens inequality. But it sounds like your perspective on generative AI is that it can actually do the opposite. I'd love to hear a little bit more from you and what we as people can do to ensure that that outcome actually happens.
I think one of the studies that can really bring this home, Alex, is a couple of researchers at MIT took a control group of people that were familiar with ChatGPT and others who had not, you know, even if they had heard of it, they hadn't actually used it. And they conducted a very statistically valid set of experiments that really revealed the effects of this technology on basic writing tasks, right? College-educated people on writing tasks. And they showed through the data, through the research, that folks that, you know, were previously less productive at actually producing output got better and faster. The quality of their output was better, and they were able to do it much faster, complete their tasks much faster. And those who are already really strong performers were able to complete their tasks much faster, even though their quality stayed roughly the same. It's changing what we can see with people who are not using these tools and people who are using these tools. And I think we need to do a lot more of that. Look, make no mistake, there is definitely a fear that, you know, this is going to further exacerbate the power dynamic between capital owners and labor, right? So the net effect of it is going to be that, you know, you're going to be able to do more work with fewer people. But I also believe that the amount of debt that we have as a society with knowledge work, the sheer amount of productivity that is actually needed in the system, take software development, for instance. We've talked about technical debt for decades. It's one of the things that really plagues industry. The reason why we are not able to evolve digital products and services faster isn't because we are short of ideas, it's because we have all of this legacy that is debt that we've got to deal with because we can't modify it quickly enough. And so I believe that all of these productivity improvements that we see can now be channeled into dealing with that debt and creating even more value for humankind. Now, you might look at that and say, hey, Sheldon, you're an optimist, and I am. I will freely admit that. But I do believe that we can harness technology as a force for good. And that's been the, if you look at the long arc of how technologies have played a role in the world, that's largely true.
How might the world look differently in a few years if and when that technical debt starts to be addressed?
So let me give you an example. So let's say in the future, I wanted to buy an insurance policy for my home. I could set a task for a system that is fueled by a technology like AutoGPT and say, go and find me this policy. Think of all the time that I as a consumer have saved by being able to just ask an AI that actually has the ability to go out into the world and do stuff for you, like in this case, just looking up websites and purchasing a policy to do. But as we connect AIs with capabilities to really interrogate the real world and to be able to do actions on our behalf, we start to see some real possibility of how work that is, frankly, busy work today can be automated. And that's going to have major benefits to consumers. It's also going to have some pretty major implications to companies and brands.
Yeah, I was going to ask you, I mean, the insurance example is a great example because there's instances where Publicis Sapient actually, if a client could be an insurance company and one of the things with the products that we're helping them develop and improve is their website. So what are the implications there?
So we've seen patterns of this before, right? The same thing happened when the internet came around, right? At that time, the conversation was around, hey, nobody's going to call up our insurance agents anymore. They're just going to be able to go onto a website and they're going to be able to look at, get a quote, or they're going to be able to go to an aggregator website and get a quote. So we've seen these patterns before. And what will fundamentally change is that brands and companies are going to have to figure out what does it look like to have AI engine optimization instead of search engineI would go to pick up my groceries. You know, I would see improvements in the way they were doing the picking and substitutions and the mechanics of that actual interaction I'd have as the, you know, the person bringing out my groceries would be dealing with their technology and dealing with substitutions and putting it into my vehicle. So it's all of those things combined that you look at and say, there is real value to be had in the things that we've brought from the physical world and from old line companies into today's future. And they are inherently easy problems to solve if you know how to solve them. And that's part of the joy of our work, of what we do.
What are some sort of natural conflicts, healthy conflicts, but places where, as a for instance, product will disagree with engineering or product will disagree with strategy? What are normally those points that there's healthy disagreement on? And how are those overcome in the course of a client engagement?
So let's start with a little bit of, you know, walking back and talking about, you know, how do things get done or how have things gotten done in most companies to date? So it used to be that, you know, there'd be a group of people that would do corporate strategy and they would figure out, here's where the firm is going to go. And then they would come up with, you know, essentially a roadmap, typically, you know, three to five year roadmap. So this is where we see our capabilities evolving, et cetera. And then you would have, you know, essentially this would be distributed to different departments in the organization. You know, if it is in the case of IT, you know, there'd be an IT project portfolio. And the CIO would preside over that portfolio and there'd be an annual budgeting cycle at which, you know, all the projects would be defined. They'd be scoped out in terms of, here's exactly what we are going to build and here's how much it's going to cost. And they would determine which ones go to the top of that list and then it would get into development. Similarly, the same things would happen in operations and customer service, what have you. And then there'd be further kind of a waterfall process where somebody would define the requirements in detail and then somebody would design things and somebody would build things and then somebody would put it into production. And by the time it actually gets to production, it may or may not be what the plan envisaged. Now, in times when change was slower, right, this was a system that somewhat worked. You know, if you're building a bridge, you can actually, you know, follow that process because we've been building bridges for thousands of years. We know how they, you know, the physical parameters and the engineering that is involved with them. But when you think about the speed at which, you know, the world is moving today, businesses and competitors are moving, and frankly, human expectations are changing. This process of, you know, essentially separation of functions and responsibilities is actually crippling. It's one of the things that digital natives know how to do very well is actually compress those timeframes. But the only way to compress those timeframes is bringing those different disciplines into the same room and starting to work together as a team. This doesn't mean that the ratio of those people are always the same. But the fact that you've got strategy in a conversation during implementation to see the implications to the long-range plan are as important as having an engineer in the room when a strategy is initially being conceived to say, hey, I can think of three other possibilities that you haven't considered. And guess what? I think that this one that you're talking about is going to be super hard to implement given the current state of technology. And you could say the same for data and product. And that's why we fundamentally believe that speed, the strategy, product, experience, engineering, data, that speed themes are really the key to unlock things.
What are some of the roadblocks to making that inclusion happen? And how do we overcome them in the course of a client project? Because it's easy to say this, right? And easy to say, hey, fingers off the hand, et cetera. But we also have to recognize that culture matters. And the backgrounds of people in these professions, there's quite a bit of variance, right? So if you take, for instance, people that went to design school and people that went to engineering school and people that went to business school, the ways in which they were evaluated in those programs were vastly different. What was valued in terms of the polish of a presentation is going to be different for an engineer, a strategist, and an experienced person. These things make a real difference and have to be reconciled because what gets listened to, what gets heard, where you turn your attention, because we tell stories and we tell stories in the way we've been taught to tell stories, you got to reconcile all of those things. And I think we've done some pretty awesome job in getting those perspectives together. It's not just sufficient having the diversity, you also got to have the inclusion. And inclusion means finding the space to listen to stories that are told in different ways and to actually suss out the stories that are not being told when you've got a quieter person in the room. So they go hand in hand. And part of what we are really cracking with speed and what makes PS special isn't just the fact that we've got these capabilities or even that they are working together, but also that we figured out the human systems that enable that collaboration to truly be collaboration and inclusive collaboration.
It's interesting to hear you talk about patience and trust because technology is at the core of what we do, but it sounds like the magic, the core DNA of what makes us special as a company and what makes us different in our delivery of work and our culture are actually very human attributes, patience and trust. Can't get more human than that.
100% agree. I mean, at the end, it all comes down when you're talking about changing the world, it's with all of the technology that we have, it's fundamentally been about humankind working together in order to figure out how to create a different future. That's what we are about. And it's no wonder that we rely upon colleagues that come from all of these different backgrounds and perspectives in order to enable that. But at the center of that is our humanity.
Sheldon Montero, Chief Product Officer at Publicis Sapient, thank you so much for your time.
Thanks for having me, Alex. Talk to you.