Rise of AI: How Generative AI Can Help Business | Wharton Prof. Rahul Kapoor — Ripple Effect Podcast

generative AI can simultaneously help businesses and customers create more value at lower cost the effects are going to be more exponential than later and I think for for me that last part suggests the theory about you know is this a new form of disruption that we have not seen it it starts looking more promising welcome to the ripple effect the podcast that takes you on a journey through the minds of work and faculty I'm your host Dan Loney and in each episode we'll be diving deep into the inspiration behind the groundbreaking research that Wharton professors have conducted and exploring how their findings resonate with the world today we'll be covering a diverse range of topics bringing you the latest insights and knowledge that you can apply to your life into work so get ready to dive into new ideas with the ripple effect Rahul there's such a a large conversation going on right now around open AI chat GPT and when you think about management and and companies a lot is still to be determined but it seems like there is the potential for a lot of thought to go on right now about what what might what the impact might be in the in the years ahead absolutely Dan and uh and great to connect with you on this very important contemporary topic um yeah you know as somebody who has done research on deceptive Technologies and business models for almost 20 years uh chat GPT generative AI more broadly uh is truly emerging as what I would call a general purpose technology like semiconductors in the 50s and the 60s like the internet in the 1990s um and uh clearly they are you know emerging across multiple use cases multiple applications and so there is a big what I call an era ferment that all of us are in where they are multiple use cases multiple business cases multiple application domains uh with enormous potential uh for growth and disruption across the economy so would it be safe to say uh talking about the history you just laid out there with semiconductors uh and the internet is this kind of a big pivot moment then for a lot of these companies when you think about how those components Changed History they they had such a great impact yeah and and I think uh if you look at you know semiconductors and internet as two of those uh disruptive forces that we have lived through um what is similar between those and generative AI is that uh they are solving two types of problems right one is a problem around productivity slash efficiency you know can we do tasks more efficiently whether it's time or cost as you know internet and semiconductors you know really boost the frontier around those issues and the second is can we find new ways to create value whether it's in Enterprise side of things or it's in the consumer side of things and generative AI seems to check both of those boxes if you think of many markets and professions uh generative AI is going to make things more efficient uh at the same time it's going to present many cases of additional value being created through those and I do think um these parallels suggest that uh this is not a not a three year or a five-year phenomenon and this is a generation wide phenomenon that we will all be living through for the next 20 30 years so what are the challenges then when you have those those massive changes from these different entities how do does management and how do corporations react to that and and and kind of does it change the process to a degree of how these companies organize and run yeah no great great question you know it's it's a commentary that I'm I'm seeing more and more coming through in the popular and the business price uh and there's clearly discussion about you know different types of use cases different types of Industries different types of professions who are getting impacted or going to be impacted uh very significantly right things like customer service content creation as you know very well software development uh internet search data analytics um and there's enough evidence that they are going to be impacting them uh in a pretty short order and then you have you know what I call on recombinations so these are not uh markets where there's an existing way of doing things and this new technology can do it better but recombinations is where new use cases can emerge through those new technologies as building blocks you know so think about chant gbt a combination of virtual augmented reality as a completely new use case that you and I have not really witnessed before so I think from my perspective uh you know when it when it gets down to what leaders and and managers can do is to is to recognize that these paradigmatic shifts uh don't take place in two years three years five years right internet emerged in the 1990s Amazon as the poster child of the success of Internet uh was successful 20 years later you know semiconductors emerge in the 60s Intel as opposed to a child for a semiconductor leader was only visible in the 1990s right so so so the good news is that this is not going to be a disruptive change that's going to happen overnight and that means there is no need to panic you know if you are a leader if you're a manager uh but there is a clear and critical need to understand what generative AI or chat GPT uh can do in terms of your business and I think this is where most of my research and teaching at the Wharton School um engages in terms of a framework that leaders and managers can use and I'll just give you a a very short um aspect of that framework right so if you are a leader or even an entrepreneur in an emerging business um you have to think about the Assets in the business model that your that your firm is is engaging with and then you have to think about these shifts taking place in the technology landscape chat GPT for example and what aspect of your assets and business models uh could complement uh what shared GPT could do so if you are in the healthcare service uh maybe there are certain things that would continue to be done the way they are done but then chat GPT or generative AI becomes an additional value-added service for for the patients for for uh for your clients and there might be other cases where uh it could replace right so if you are in the content creation business and there's certain aspects of content creation that could be fundamentally replaced through generative AI models and and I think that's a starting point is how your existing assets and business model are going to be shape and not framing it as a negative threat but think about where it can complement and where it might replace a very parallel thought process that I engage with Dan uh with students and Executives is thinking on the customer side as well you know you have existing customers and then you're looking for growth as new markets and new customers and existing customers are part of an existing ecosystem and new customers may require you to build a new ecosystem so once you start thinking about the ecosystems you think about how is a new technology like generative AI affects your existing ecosystem or your partners are your customers better off or you need to invest in the ecosystem to create a higher value for your customers do you need to create new ecosystems like electric cars you know what Tesla has done and what uh the success story there is it's not just about the electric car it's about building the whole ecosystem so I think from my perspective uh this is a process of disruption that is not going to get resolved in the next three to five years the organizations and the leaders who are going to do well are the ones who are going to have a very thoughtful approach to how this shift is affecting their business both in terms of the positives but also in terms of the challenges thinking about it not in terms of just existing customers but New Market opportunities and not just focusing on the existing value chain but the broader ecosystem of how these companies create value so if I can have you talk about that customer component again for a second because it's interesting there's been so much conversation in the last few years about the relationship between the company and the customer about how the company the industry can do a better job of making that connection and keeping that consumer longer term that this is seemingly that next step in that process isn't it yeah no I think you know we've talked about customer lifetime value and as we have embraced more personalization uh much of this is coming through data and data analytics we are explicitly thinking about you know how we can enhance and maximize the value that we can create for every customer and it doesn't require a one-size-fits-all approach right so we can generate things that are more personalized we can create and capture value for each customer or entity over time and I do think you know a generative AI uh would enhance that you know it will broaden the scope of what personalization might mean for you personalization might be let's say from a from a Content creation perspective yeah for me it would also include research perspective as well and so I can imagine scenarios where companies are able to create a suite of personalizations and bundles through generative AI add a level of a customer at a level of an Enterprise that was not possible before primarily based on data analytics so I think once we include these new algorithms and these new learning processes that are algorithmic the scope of personalization becomes much broader and that has exponential effects in terms of success of businesses I think it's issue when you talk about this of how it will impact companies but I think you can even take it larger scale and think about how it's going to potentially impact Industries as a whole correct absolutely absolutely in fact I was uh on a panel this morning with fellow academics from from other institutions and that was our question uh how can we think about the impact of a journey purpose technology like generative Ai and you know the conversation that I strongly believe is true is it's gonna have at least four different points of impact right the most obvious one as a strategy Professor is for businesses and for Industries but it will also start having an effect on professions and societies might a much broader level right so think about what social media has done to our societies to think about what internet has done to our society so I think each of these levels starting from organizations to Industries to broader professions and even the social fabric are likely to be impacted through these technology emergence some of this is going to be positive and value creating and some of it we have to be careful yeah especially with such a strong human interface and a modality that uh these these Technologies uh are human-like um I think there has to be a lot of care that needs to be exercised in terms of how professions and societies are going to be impacted by these emergencies so part of that it would seemingly from what you said there is you know how companies think about their structure the levels of jobs the types of jobs that they will have what jobs you know have the opportunity to have open AI chat GPT benefit from uh from that technology what in some cases may even replace uh certain jobs along the way as well absolutely and and you there is a lot of research it's very early stage so we don't have a definitive statement uh on that issue uh but when you think about every new technology right the model that we all prescribe to as as researchers of of technology is every technology follows an s-shaped curve right early stages of a technology it's imperfect it's not cost effective we have to invest in resources and it takes time for it to improve but once the technology gets well understood and the experimentation allows us to fine-tune how the technology actually works then we have a very fast robust trajectory of improvement kind of what we saw on semiconductors in the 70s or the 80s what we saw on the internet era post 2000 what we're seeing with electric cars in the last three five years and so I think from my perspective many different professions are going to be affected I think it's uh it's a bygone conclusion the rate and scale of what that would look like would be a function of those S squared trajectories across the different professions you know if you think about you know let's think about uh the professions that are tied up in customer service versus professions that are tied up in Creative Industries you're likely to see different models of s and different rates of of growth depending on how the technology is going to improve and achieve the performance requirement for those professions to be substituted by these emerging modalities we will obviously see this play out in the years ahead but as you were describing that my thought is is that the level and the the sheer volume of companies and industries that could be impacted this it feels like it is extremely large and it will be realistically on the company themselves or maybe the industry to understand how open AI chat GPT will be able to be incorporated within the structure of their firm moving forward yeah and absolutely and and just the way you describe the problem it's it's it's uh it's a very complex problem right and and um you know when uh when I talk about how companies and leaders can manage disruption of a skill like what we're talking about today we generative AI uh there there are three impediments that companies have to deal with in the shot right the first is uh there is significant uncertainty in terms of what the dominant use cases are going to be what Solutions are going to satisfy those use cases what business model would allow for companies embracing generative AI to actually do it in an economically viable right so there is there's many sources of uncertainty that every era of disruption seems to present so you are you are in an environment where there are more unknowns than nodes secondly you still have to run your existing business that's not going away tomorrow often this is going to be a slow process of evolution three five many cases longer years um so you have to think about how do you want to still focus on the old business or existing business why exploring these new possibilities and the third is the adjustment cost that you are making in terms of building new skills building new capabilities uh dealing with new competitors that you may have to deal with so once you introduce inertia which is how you change and the adjustment cost once you introduce uncertainty and once you introduce the balance between the existing and the new uh it is a very very hard nut to crack I'll I'll tell you what I've seen in in my research the best time right to explore something that's uncertain and disruptive is when you're not desperate for it to be adopted right the best time to invest in a new disruptive solution or opportunity is when you are running a healthy business and that's where the pressure is going to be the lowest for you to take more risk and explore more broadly you know the second aspect of the management uh or leadership that I see that generates successful outcomes is to think about what sort of an organizational structure but allow for companies to take advantage of these disruptive opportunities and you know it's it's often talked about that they need to be managed as separate businesses or separate units um if you see what Google is doing with alphabet there's a Google business and then there is a WeMo business which is a self-driving technology um I think that's one way to do it I find Partnerships alliances with many companies to share risk to share cost to learn from each other is a model that I think is a very effective model especially when it's still uncertain um and then third I think we need patience why we need to be disciplined in terms of how we experiment and innovate as well so I think a combination of how do we balance existing with Neo how do we engage in organizational configuration that allows us to maintain that balance and then having a disciplined approach to how we are experimenting around these new technologies and business models and giving them enough of a Runway to take off as opposed to switching back and forth between something new versus something else every year every two years that generates more confusion more inertia more cost and tends to be counterproductive let me finish up with with one question is it it seems like we have had disruption in our corporate structure for such a long period of time at various levels with various impacts but this feels like that this is a disruption that is kind of taking us down A New Path and it's almost disrupting what we think the idea of disruption is that we've kind of made this massive shift potentially as we move forward yeah I think the thing that the juries out there in my view Dan uh you know is this uh is this a new wine if I might use that analogy or this is an old wine in a new bottle and um you know whenever there is a widespread uh paradigmatic change like the internet like the semiconductors um those conversations emerge and I see with generative AI or chat GPT more specifically I'm seeing there are those two camps within Academia as well uh many people believe that uh yes the the the technology is different uh the the models of value creation are different compared to what we saw with internet or semiconductors but the the nature of shifts in terms of assets and business models and capabilities uh they have been well understood and studied so it is a wine that we understand and we can we can understand what the ramifications are um and others believe that this is fundamentally different it's a it's disrupting the way we have thought about disruption and I think and I think how to parse these two perspectives in my view uh depends on thinking through what the impact that generative AI is having right in a business context uh it's clear that this is not just a technology problem you know it is a broader issue than just thinking about the technology it's how it impacts organizations uh in terms of the jobs but also in terms of how organizations create value it impacts the business models uh it can completely replace a given business model and find a completely new business model at the same time right and it also impacts the ecosystems the broader ecosystems that many companies are part of in terms of requiring a major reconfiguration of the ecosystem or meeting many old ecosystems completely redundant then on top of it the the generative AI technology is allowing us to do two things simultaneously uh that has been very hard to do historically which is we can use simulative AI to find use cases that create more value for the specific customer or a market at the same time we can do so at a much lower cost yeah and I think because generative AI can simultaneously help businesses and customers create more value at lower cost the effects are going to be more exponential than linear and I think for for me that last part suggest the theory about you know is this a new form of disruption that we have not seen it it starts looking more promising not so much that we have not seen a flavor of that before I think internet had flavors of that in very specific markets like social media and others but I think it's not happened at the scale across markets across Industries across professions across societies at the pace that we think a generative is going to uh going to go into propagate so I think for me uh the scale of the effect with exponentiality and the linkages between technology organization business models ecosystems and professions is going to create a much larger Multiplex effect some of it we have understood and seen before but some of it remains to be studied and remains to be understood thank you for listening to the ripple effect we hope you found this episode informative and engaging don't forget to subscribe and leave us a review so that we can continue to bring you the best Insight from the Wharton School

Channel: Knowledge at Wharton

Views: 1,718

Keywords: wharton, wharton school, penn, university of pennsylvania, business, business school, journal, knowledge at wharton, research, Rahul kapoor, ai, artificial intelligence, podcast, ripple effect

Id: KZbDvpgWkoI

Length: 25min 21sec (1521 seconds)

Published: Tue May 30 2023