On the Front Lines of AI Game Dev

[Music] Welcome to the Navit Gaming Podcast, where it is our mission to explore the business and future of video games. We bring together the industry's brightest builders, investors, and thinkers to keep a pulse on current events, dissect emerging trends and games, share lessons learned, and have a great time. This podcast is also part of Navik's growing ecosystem which ranges from free and premium research to consulting and advisory services. For more information, visit www.navic.co. [Music] This episode is brought to you by Leveler, the Discord community intelligence platform helping game studios cut through the noise. With powerful social listening and sentiment analysis, Leveler tracks millions of Discord messages to tell you exactly what your players care about. No more guesswork, just realtime insights into what's working, what's not, and what

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to neonpay.com or check out the link in the show notes. And with that, let's jump into the episode. Hello everyone. I'm your host Devon Becker and today I'm delighted to be joined by a fellow Novik member here, Francois Corset, a senior games industry consultant, Novak. Francois joined Navic recently and is providing some additional consulting expertise and experience in using AI for game development. So today we're going to dive deep into the current and near future state of using AI for game development, touching on some of the stuff uh in an article I recently had done as well on the state and then some stuff from Francois and his experience. So just to start things out, why don't you go over your background and experience around AI by itself as well as with gamedev?
Cool. Thanks, Devin. And happy to be to be here. Thanks for for having me. Um yeah so I've I've been working in in gaming across research and strategy roles um for the past the past eight years um companies like Neielson Ubisoft

and most recently at NIS as part of the the global strategy team um where I was in charge of like monitoring identifying and assessing um any kind of new AI powered tools that could be leveraged to improve our production pipelines or directly serve some of our gameplay play for positions um with this idea of like a sort of open innovation establishing strategic partnerships and collaborations with external to providers and understanding um where the value was um in all those new kind of kind of AI related innovations. One of the things we worked on was uh supporting team me, one of the first studios to implement in world AI technology um in a consumer uh facing product which was Sinus Enterprises. Um, and so throughout throughout this time at at Netis, I kind of saw firsthand like the the the lack of general present focus in the way we approach AI, kind of

looking at at u the hype without necessarily having reliable sources of information of like what AI can actually do right now uh in in games with all also the the multiple internal roadblocks to actually adopt and deploy AI solutions um within within kind gaming gaming companies uh and even on the tool provider side like struggling to kind of to kind of enter those gaming companies, find the right point of contact to actually engage and and suggest those those innovations. And so kind of took all those those learnings and figured that they there might be some some some potential to to support the the broader the broader gaming industry. And I recently joined Navic to help uh uh studios um and any kind of kind of gaming companies looking into AI and and and and gaming as part of like a new AI consulting service that that we've recently announced at at Navic and more broadly supporting all consulting

needs.
Well, excellent. I mean, as you've put it, like a lot of people are still figuring things out, so you're not hearing necessarily a lot of even learnings from a lot of these companies. It's definitely let's let's figure out what we can and can't do and we're probably not going to announce anything unless it works and we're happy with it. So, it's even the the failure learnings, right, where it's like definitely difficult. Uh but like just kind of on a personal level based off your experience, based off what you've seen and just based off what you think, what's your kind of highlevel take on AI in general and and then specifically in game development?
Yep. Um so in general I think like um any hot topics or or sectors there's um um a need to kind of cut through through the noise. We tend to kind of underestimate the future potential of it because it's going to be extremely transformative but at the same time the current potential tends to be um overestimated which leads to all sorts of of of issues when actually deploying solutions. There was an interesting

piece of research um published recently by by DMIT where there was this flashy headline of of like 5% of test specific pilot AI projects are are actually uh reaching production and gener generating benefits. regardless of like the exact number of methodology, it kind of tells you that like there there's a real struggle in in kind of getting to those actual benefits of AI, h how to actually impact um uh the the business, the efficiency. Um and so there's still a lot of work to to to be to to be done there in kind of the AI space in general. Um, and then more specifically, um, with with gaming, I think it's it's safe to say that that AI is already there in a way. Um, like I think 20% of the the the games released on Steam this year were were kind of including some sort of of of of AI were actually disclosing uh using some sort of of of of AI and developers are are

already leveraging all sorts of of um largely available tools like chat GPT or or coding supporting tools. Um so AI is there um in a way but still uh a lot of the the kind of lowhanging fruits haven't been fully captured yet. So people are still kind of dabbling with um those those AI tools and uh often not in a structured manner uh kind of integrated with it with within kind of a a clear um a clearer strategy and even besides this like the gaming industry itself has kind of a set of of specific challenges uh compared to to to other industries. the fact that gaming teams tend to be um a fragmented group of highly specialized teams uh that each use like very um specific sets of tools that could all need to be kind of kind of AI enabled in some way and kind of

limits the potential of like large scale um benefits of deploying uh tools within those those those teams. the gaming projects are long as well. Um, and it's it's often tricky to kind of change course uh in like a three to five year kind of kind of production pipeline. So, adopting new technologies mid- project can can sometime be an issue. And often in gaming, we also don't see a lot of uh change management teams that are really dedicated to um deploying and and identifying all those new technology innovations uh built externally that could be beneficial for for for the game production teams. And on top of that, you have also all the brand risk and consumer backlash that that kind of comes with um with dabbling with with with AI. So it creates an an additional layer of risk on top of um of of everything um listed here. So uh it makes it uh challenging for for the the

gaming industry, but it also means that there are like like very interesting opportunities to to to uncover and when properly executed um that can yield like significant benefits for for gaming components.
Yeah, I imagine a lot of the problems is just from having to find out the hard way what doesn't work. especially they just you know there's not even best practices yet right and like you said change management and coming in like people kind of dipping their toes in
they can't go all in right unless they're like a very small company willing to risk the whole thing and you know they usually those are the ones just trying to seek funding off of using AI you very similar in some ways to what we saw during web 3 where it's like this is a new tech we're trying to figure out how to integrate it might integrate it kind of naively and we're just hoping that will attract investor interest obviously investor interest in games is kind of at a bit of a low point in in some ways. So that could be a a big bo for them. But I'm kind of interested in like the the very down to earth practical aspects of this like what can we really do right now? And so like on that topic like are there some favorite

tools either that like work well now that you have like that you've tried and used or ones that like have shown enough potential where you're like maybe it isn't doing it right now but we should definitely be trying these and like building towards that.
Yeah. Um so obviously there are like tons of of of tools already available or being built uh either proprietary or or kind of external ones uh probably like close to 200 startups uh actively building around around um AI in gaming. Um, so like lots of of like specific kind of kind of areas are are being addressed on on my side. Like a few that I've really kind of kind of found like um deeply interesting in terms of like the potential behind it. Uh, one is is kind of pool day AI um, which is uh, an AI video editor um, centered around like ad creative uh, production. And I like it because it kind of has this this this principle of like being able to to do a time 100 on your kind of output

capacity. So the idea is that you can um create multiple iterations of um add creatives by simply inputting like content and uh like gameplay excerpts and and and and taglines and things like that. and the the the the tool will produce like hundreds of videos that you can then use for AB test AB testing. So I think this inter intersection of like uh AB testing with AI um and the the the potential of like yeah u uh increasing significantly the output of like one specific task is really where there are like tons of value to to be found. So that's one. Another one that I um liked um a lot is is Craftbench AI um which is like a a Minecraft uh asset production uh tool using generative AI um which supports like UGC studios in creating custom Minecraft uh assets that can then

be used um within the within their their servers or or um and and and and there like what's particular really interesting is that it really showcases how you can make the most of like a very in-depth data set in the first place. Like if you start training your AI with a very specific um um pool of data uh that is really geared around your your business objectives, uh you can really end up with something that is extremely um ready for for um uh being actually published and shown to to to consumers. And so Craftbench is really interesting in that in that aspect. Um, and then finally, one that that that I think has like a huge potential is uh model AI, which does uh automated QA testing. Um, they're basically able to deploy uh bots in game that will explore the game environment, find bugs, um, uh, optimize

pathing things like that. Um, and again you have here the idea that like uh you can potentially deploy like thousands of butts to to to kind of to kind of go through uh all the different the different pieces of your of your of your level and and find all all the the potential the potential bugs there. So once again, it's taking one small piece of um the the the production pipeline and then finding a way to really kind of kind of um address it in a in a significant way and scale significantly the amount of of of testing here that you can that you can do with with AI tools. Yeah, that seems really useful considering just man-hour for testing, especially when it comes to like testing something after a fix and all those kinds of things where you constantly have to test same content on a very tight schedule usually seems I mean especially if you're like running live ops or anything else where you're going to have to be pushing out updates and you need to be testing those and I can't

count how many updates come out partially broken in some way and just the you know testing coverage is very limited. So that seems like a really really useful one. I mean, the part that sounds like it might be more difficult is like the recognizing of bugs uh that aren't just straight up errors, you know, like recognizing uh odd behaviors and stuff like that. I'm c curious how it works when it comes to identifying those things.
Yeah, it's always like um so it's one of those cases where like the entire kind of game testing pipeline won't be kind of kind of addressed by by like a um a single tool. uh but rather it's about like uh finding those uh those like tests that can be uh supported by AI and improved by AI um and then uh kind of kind of leveraging that to let the team kind of focus on the other areas that that that can't be kind of fully addressed by AI now or uh hope oversee AI kind of kind of contribution because there's always an a

need for like for like human checks and and and and and like managing errors that can come out of of of AI models as well. So uh it's about yeah uh again finding those those little kind of areas that you can that you can that you can address and then expanding on that um progressively as like the technology evolves or motors are becoming available
right kind of that theme of like it's not about replacing people just yet because it doesn't do the same thing as people it's about augmenting enhancing what you can do right I mean I have heard you know obviously people uh at the programming level often are like uh you know AI programming is no good stuff like that but I have heard good things about it for like unit tests and that sort of thing, right? Where it's like getting that kind of coverage, something that's kind of a pain to keep up on and set up like those kinds of things where, you know, as we hear all the time, repetitive tasks and things that are a bit like manual work, those tend to be sometimes best suited. I mean, it makes sense, right? Something that logical and repetitive is good for a computer. Now, we just have a bit more flexibility in how we execute those with AI. I mean,

that sounds that sounds great. I am kind of surprised that the you mentioned the Minecraft one, and it's like Microsoft's been trying to put AI into just about everything. So it does surprise me that they're not pushing that, you know, considering they own Mojang. So M Minecraft is essentially a Microsoft project for the most part. So it kind of it kind of surprised me they don't showcase that sort of thing more even if they are involved in it. I'm not, you know, sure who's in charge of that, but it it does sound like a good use case similar to what we see in like Roblox and things like that. And UGC definitely seems like an interesting use case where it's like, well, if people are pushing back when game developers are using it, well then are people pushing back when average users for UGC are using it? And if not, then that's an angle where it makes sense because it's, you know, as they say, democratizing development as opposed to like firing people basically. That's the part that people don't want to see, right? So, I mean, speaking of like the different areas, you're talking about some of the different areas you could try to hit. Game development is like this big long multi-year thing. Lots of things to it like, you know, like making a movie, but maybe even more complicated in many ways. Lots of lots

of different areas of development, lots of different people involved. What are some of the areas that you've seen uh AI be most useful for in game development like like consistently where like you mentioned a couple right with QA uh and maybe some EGC stuff. What are some other areas whether there's you know specific tools or not?
Yeah. Um so I I think one is um is asset repurposing. Um so the idea of like taking existing assets and and uh reusing them in a different uh in a different way. for example, like create a Christmas themed version of my game assets so that I can do like a Christmas event, for example. Um, so uh here it's it's more about like uh reusing existing stuff and iterating um rather than actually creating assets from scratch um which is uh really where where where I think we see the most potential in this this kind of repurposing um uh element. So it's especially helpful in live service content production, but it can be valid for SQL, DLC's, uh basically

any place where uh you can feed existing assets into your model to to kind of kind of iterate on to we come back to this idea of like iteration and and being able to to kind of multiply uh things where where really AI has like tons of of of potential. Um so yeah uh I think this area is is particularly interesting uh especially in 2D uh right now um because uh for 3D the tech still needs to to to kind of mature a little bit uh but most likely in the in the coming months or years this 3D assets will be will be um similarly impacted by by kind of this this idea of asset reversing. Um, another one, uh, obviously I mentioned at creatives, I mentioned, um, QA, so I'm not going to dive into this once again, but localization is very interesting as well. It's one area where AI has been used um, fairly widely for for a long time um, already, but but it's really

one of those those really uh, low hanging fruits again where um, the the the technology is is very mature. Obviously there's still need for for kind of kind of overseeing uh what what AI does uh because inherently has has like hallucinations, issues, errors, things like that that you still need to account for. Uh but there there is a huge potential there and with companies like alloci and um kind of building around around localization. Um, voice also uh has proven to be extremely mature already uh with 11 Labs obviously, but like all sorts of other kind of kind of startups helping um do text to speech or or speech to speech u um kind of kind of generation. So this uh this is also a very kind of mature area. We've seen it included in the finals from Embbox Studio as well. So it's already kind of reaching consumers to to to an extent and so they're

definitely another interesting area. And then the final one um the dialogues um dialogue production um is also one one place where AI can can already be fairly seamlessly integrated. You have the the ghost writer tool from Ubisoft that allows to uh produce box or secondary um NPC interactions. Um again uh taking like a a very uh time consuming uh parts of the of the process and using AI to to kind of deliver at scale uh on that specific uh task. So, so yeah, that could be some of the some of the obvious ones. And I think the idea behind this is like it follows a lot of like the u the type of of content that you're willing to produce like producing text content is already extremely mature. Voice content is very mature. And then as you go into um images or videos, you might you run into more uh challenging

with challenges when it comes to how ready uh the technology is, how um easily uh it can be integrated for actual uh production pipeline needs especially in a AAA context. So as you go into those those those kind of modalities it becomes uh increasingly uh uh difficult or uh there's still a need for for a few few more months or years of of development to reach like full uh full technology maturity.
Yeah, a lot of those sound like things that it would it's really important to have oversight on in terms of like quality checks and things like I mean, I've seen more than enough bad versions like especially like AI subtitling of things and I'm I'm sure that, you know, goes to localization as well. I mean, how many Japanese imports have we had over the last couple decades where just, you know, the memes from the bad translations. Uh, I mean, obviously like that takes a certain amount of effort to go through and do all that

double-checking, right? And I and I had my own experiences where it's like sometimes the amount of work to double check everything AI does, you get to the point where you're like, well, why didn't I just do it myself in the first place, right? Where sometimes, you know, you wonder what was the what was the cost savings? Are you seeing anything where there's some good ways to be efficient about that? Are is there AI double-checking other AI's work? Like, hey, go through and make sure that all that dialogue that you just, you know, translated from another language makes sense, right? Here's like the type of characters like does that those translations are they nonsensical? Stuff like that. that is there like some amount of automated oversight?
Um I I haven't heard about like actual kind of kind of yeah uh uh AI reviewing other AI but you can you can easily see how that that could kind of happen like especially if you you start having like QA oriented kind of kind of solutions stuff right?
Yeah. Yeah. and and and and and it all comes down to like internal governance and I'm being extremely intentional about what you want to do um with with

AI because uh as as as you said there's there's always this this kind of kind of uh uh need for for supervision review and things like that and you don't plan ahead properly uh there um you end up with processes that aren't generating any significant value or cost savings just because uh because you can't trust the the AI enough behind it. And so you need to really be conscious of like um model limitations, parent limitations and and how to to manage that risk internally um and how to to get reduce the potential impact as much as as as possible. And again, it come comes down to how you structure your your internal teams and product project management around these new tools to ensure that that can be properly deployed and it can be beneficial in terms of efficiency or or costsaving for for the studio.
It sounds like I mean the important thing then is not to rush it, right?

Like I think of the altars, right? What happened with that? uh and you know that was also a transparency issue and things like that and we're not going to get too much into that sort of topic because that it's a whole can of worms when it comes to ethical stuff transparency business models you know customer relations all that stuff it's uh it's it's tricky right this is more about the uh the potential in the tech but I I you know I feel like you know the number of times I've seen like localization or other dialogue attempts where you see like actual like parts of the prompt in there and other things like that that's just those things that slip through the cracks where it's giving enough time not just for the actual process and double checking, but like you said, for maybe setting up the proper governance for it or the proper structure so that there's like proper reviews for it, that it goes through a pipeline that if there's changes that that also goes through the same pipeline. So, it's like just don't just jump into it thinking, oh, we're going to rush into this and suddenly save our game company with
there's no magic. There's no magic there. like it you you still need to to do the work in a way and and and and

work alongside AI rather than kind of leaving everything uh to to ADA that that's that's where you run into into massive uh issues even backlash and and and those kind of of of yeah news that we see pop up here and there. I mean on on that vein too like you there you know there's a lot of these companies experimenting internally right and I think part of that's just like they they want to figure out what will work for them with their particular workflow and and their particular data and things like that but that's that takes time away from the working on the game right where it's like they've got a budget they're on that game's budget they're not usually unless it's a studio with a ton of leftover money where you know if it's like hey maybe like Valve or something like Rockstar where they've got money to burn to some extent they they kind of have to burn some of the game's budget on that are you seeing like where it's you know it's some of the developers just looking to see if they could improve their own personal productivity is it like independent teams kind of just experimenting kind of a prototype lab like you know Ubisoft for example has their uh they're the individual lab doing those sorts of things we see some of that what's kind

of your overall take on how people are approaching that internally in companies
yeah so I I think there like um so the the idea comes down to uh being intentional about what you want to achieve with with with with AI and keeping that that business focus um in mind. Uh you see different initiatives like you mentioned um AI labs being uh being built um all sorts of like internal R&D uh initiatives. All of these need to be like tied to uh actual uh business objectives like um if you end up kind of experimenting uh with like a team of of uh of AI researchers looking into anything that that's possible through AI that's that's that's that's a significant issue and and and we've seen kind of projects and and and pilots um that that that are more kind of showcasing what's visible rather than like what's can what can be actually

valuable um for for for for businesses. So I think uh what what studios need to to do is really balancing the the needs uh from for between like extremely um specialized um tools that that will that will yield like uh located benefits versus tools that uh claim to address like a massive part of your your um game production pipeline. Um I think it again there's no magic here. Uh like production pipelines in games are extremely complex involve like a lot of different different tools and teams. Um and so uh it's about like identifying those efficiencies reviewing strategically and systematically like all those innovations to see what can be fitted into uh into the the the various

um projects. So it's it's really about like saying alert uh finding the right um teams or external tools that can be that can be easily leveraged and plugged in to to address specific areas. Um and when relevant and mentioned like it's it's mostly for like broader kind of kind of organizations like really invest on building an edge in a in a specific area based on um internal data sources. uh for example that can't uh that that can't be accessed by external company and that allows you to actually polish a tool one step further and and and and really be able to to kind of kind of optimize your own internal processes with with those those kind of larger IPs or or or studios.
Yeah, it sounds like a a long process for a lot of these companies trying to figure that out. It's that's especially tricky too because like you know you have these business goals and things like that and most of those are going to be financial or times based and you

can't really show off the fruits of those results to the customers generally right because the players are not going to like to see that. You're not going to be showing off like hey look what we did with AI. Uh we saved ourselves money or we like
generated something that you guys thought was real. Those kinds of things you just you can't brag about. Uh and so it becomes kind of this weird thing where you you could kind of show it off internally a little bit to be like look we found some things that worked uh and kind of have the communication and some of that governance and sort of infrastructure inside. I imagine that a company culture then matters for that too cuz you know you get the internal revolts of developers like hey are you trying to get rid of me? Are you trying to take my job? Uh I don't want to see KPIs improved there because that means a threat to me or uh to the creativity of the game things like that. That seems like a really tricky process to navigate. Yeah. And and and really the the the teams that that that really kind of kind of manage to Yeah. uh progress. There are are companies that that have those established kind of strategy game

teams in a way that that really look at at those those tools um at that understand like all innovations coming up from the startup world but also look at the broader kind of AI innovations um and kind of the the the the broader business landscape and and and and trying to to really tie that to okay what are our internal processes and and where can we match those those kind of two pieces together,
right? Especially now too with it with with the KPI stuff and the spend that it takes to do that stuff. You have that whole like people talking about, oh, uh, the returns just aren't there for AI, that sort of thing where there's a little bit of like that sort of trying to bubble pop, I guess, at this point or deflate the excitement around AI is definitely like trying to set that realism in there of like this is not going to be like a magic thing. we need to actually figure out what's going to work for us from a business perspective. Uh or at least something that's going to like benefit us long term if we can afford to do that. Um and and like those are some of the obvious things you talked about like when it comes to

things you could generate, things you can actually translate, things like that. What are some of the more unobvious uses or some of the like the really interesting things that you see potential in that maybe like outside of the 3D, right? You mentioned 3D is one where it's like obviously like not quite there yet, but I think it's almost a given like what you said. what are some of the like the the obvious ones are the ones that people should be putting more time into or thinking about or uh just don't let it blindside them like investigate now kind of thing. So, I think um one that is that is extremely interesting more kind of on the the gameplay um side of things is is really this this this idea of like um adaptative difficulty um and like having a game world or an environment that that's um constantly kind of adapt uh based on the players input. can be like adding more enemies uh based on on um what what like you you you kind of like what the player does like if if it's a good player put more enemies to to keep

it uh interesting and engaging. So I think that's that's that's really an area where having um uh tools that are context aware and that can allow to to tweak uh parameters uh for the gameplay experience. Um be extremely extremely relevant been done to to a certain extent like all the older games like F4 Dead and things like that. pushing that further with the latest um AI innovation is definitely uh an interesting area to to look at for um I think there's also a an interesting angle for like brand engagement or IP engagement um and in kind of a consumerf facing uh way uh we see a lot of engagement like not necessarily AI related but with uh clip productions like with Roblox for example, Roblox clip it. Um, and so we see um consumers kind of going in

between different uh content formats like videos, game play, uh, text and so on. And AI um has really the potential to help blur those lines between content types um and um and could be used to to to really engage consumers in a different way uh to allow them to create viral clips, viral images, viral text, things like that to really supports the community buzz around specific IPs or aims. Um there are like specific initiatives there that kind of point in that direction like kinetics allows you to to kind of create uh custom emotes um by by scanning uh your your your body um which is which is kind of one way to do that. that you have Dorian AI that u um is is a platform where you you can um you can write uh aided by AI about your

uh favorite u uh characters or or or things like that. So really kind of pushing this this text user generated content uh area as well. So this idea of like yeah using AI not only to uh strengthen ability to create content in UGC but also to um yeah uh enable u consumers to to dabble with different sorts of of content I think is is is a really interesting area to to look out for as well. You make me think of the some of the stuff that um that we've seen before where people try to experiment with trying to bring characters out of the game like even even like Left 4 Dead you bring up. I remember when there was like Twitter accounts for the um the different characters like I don't even remember if those were official but just like you know talking as them and like bantering and sort of thing and it's and it brings up that idea of like control of the experience when it comes to using AI that's reactive rather than like in the production process, right? there's this big separation between is this something we're using to produce content

in some way or produce a game or is this something that is real time to interacting with players in some way and we have seen some experiments with that like uh the Darth Vader in Fortnite was a good example
or any of the chat bots that have been online and and the big theme that I noticed with those is when they go out of control it becomes its own form of publicity good or bad right like and you could say maybe all press is good press and maybe uh a lot of people might not have heard about the Darth Vader character being in there that you could talk to it and wanted to go talk to it after and actually played Fortnite because they heard about that because of the bad press around that. It could have been that, but that was like two brands having to deal with the backlash that way. You've got the Star Wars side of things under Disney and then you've got the Fortnite side of things having to deal with that as well. Maybe even the AI tech side of things having to deal with where that might be loos. And it just makes me think like you you talk about like the Left 4 Dead style directors or any of the stuff that would normally be bit more procedural or algorithmic suddenly being like can we use these models to sort of like take a little bit of the rails off and allow for a lot more situations that we than

we could code for, but also in doing so the rails are off, right? And you end up with these situations where now I mean games are somewhat about controlling experience, right? you're building around an experience, but you don't necessarily control the way you do like with the movie or something like that, right? But do you think it's possible for us to kind of find that middle ground where where we allow players to really just kind of do whatever they want, maybe in a single player environment, uh maybe not as much as multiplayer or or even around that content creation stuff where they're not going to go, "Hey, I'm going to make Darth Vader drop the nword and then clip that and there's my social media content I created with it."
No. Yeah. It all comes down to um to this idea of of of like um where's the fun first in what you what you do uh with AI. you need to uh ensure that that whatever you're building it's going to add uh value to uh to the end player like is there um part of my player base that is actually interested in in

playing what I'm I'm I'm I'm building like the new gameplay uh proposition that I'm building using using AI because you can really see like AI easily allowing to do endless things right but is endless fun really um and How does that serve your game to have um infinite conversations with anyone's that anyone that you can meet in uh the game? So, I think it it game studios will need to balance like what's editorial and what's kind of artificial or what's generated by by by AI um within within those games. So um as you were mentioning there there's a lot of of um uh controlling to do on on on ensuring that AI is used like in places where it makes sense and in places where it can't be broken too easily uh by by by players. Um so so that's the first thing. There's another

thing that will likely be kind of cultural evolutions around the way we look at at AI generated content. Um uh you can see it um uh already in this in in in like consumers are already playing with AI tools and generating images uh um or content for fandoms and and and and online communities in general. Uh so it's already there and consumers are already kind of uh playing with your brands in ways that you haven't expected them to to to do. So there there will need to be some some um some wiggle room in a way to to to deal with this this kind of additional freedom um and and avoid like all the risks and and and backlash and navigating that will be uh will be tricky. But again it comes down to how um intentional you are with your strategy in the first place. what exactly um where exactly do you want to

uh uh implement AI and how do you do you kind of consider all the risks and limitation and mitigate that as you progress with the implement implementation process.
I'm kind of curious too about even like that freedom skewing the gameplay not just from a uh breaking the game in terms of what you could do with it perspective but it in terms of players then feeling the desire to purposely break it. So, I think of like, you know, when you have any kind of UGC element, whether that be like the Minecraft level or whatever, Legos, anything like that, you have the old uh time to a certain phallic symbol that that tends to happen, right? Where people have this innate desire to see where the limits are as soon as they're presented with something that is supposed to not have the same limits, right? So, you let's say you throw an NPC in and it's like, "Hey, now you can say whatever you want to it." Chances are they're going to completely break immersion themselves and not roleplay until they've thoroughly seen how far they can push it and then maybe once they're bored of that start role playing and actually

playing to the character and seeing what it does. I can see that being problematic to some extent versus like a more you know this dialogue tree system or these other ones where you might be able to allow a lot of flexibility but you don't necessarily have the same problem. I mean I even think back to like the old text adventure games with like noun and verb sort of thing, right? where everyone's just trying everything that you could possibly do, even if it's just kind of a joke, but that was more like in the the days when you didn't have viral social media or something to share those sorts of interactions. Uh, and they were all kind of hardcoded to some extent. And so it's it's a little bit of a different different world in that sense, but but I digress. It's it's it's going to be interesting to see how that that problem solved. Then maybe we just have like sort of an immature time period where people kind of have to get used to it before they actually take it seriously. and and and we do have also like um emerging kind of kind of moderation tools that also use AI. We were talking earlier about like AI kind of monitoring AI, but moderation is is also benefiting heavily from from uh progressing in

generative AI. And so um this can be like the missing block that that kind of allows to uh control uh a little bit more what's being produced or done around uh like uh old kind of AI applications deployed in games uh right now. Well, it's it's definitely going to be interesting to see like how that goes just because like there's a lot in motion right now, which is a good thing and a bad thing, right? It's a good thing that there's the possibilities haven't been set yet. There's lots of things that can be done. Some of it's dependent on the technology and the timing and money and the market and whole bunch of other factors which also kind of created the situation we're in right now. When it comes to game developers who are considering using this stuff, obviously like you know, we've talked about specific tools, things you've seen work and things like that. Should game companies in general be experimenting internally or should they look to outside expertise or you know tools or things that kind of solve problems already or thought about those things, figured out those things so

they're not burning internal time because especially now that you know we're running into like a lot of crunch time for games whether that be on time schedule or a money issue or any of those things or just you know manpower in general.
Uh yeah, I think so there's no one answer there. I think uh it's it's um often a case by case um analysis but uh what this reveals is just the need for having um uh teams uh that that kind of systematically review and assess uh cost opportunities associated with uh all the new AI innovations across um across the entire the entire ecosystem or the entire production um production pipeline. Um based on that like there are there are a couple things we can we can say there like the first thing is that AI tool providers like often benefit from significant platform effects uh especially when they're consumerf facing they they um can like um uh reinforce learning uh on their AI

models and improve the quality of the output and even sometime kind of access like private training data sets or or leverage some of their clients data. to further reinforce their their their model. So there are like clear benefits uh on the kind of AI tool provider sides when working across like a a large variety of of of of clients. Then I think the other angle is is really assessing like the modes from those companies like uh is it just a wrapper around a model that is that is widely available and that I could probably replicate uh internally. Do I have like unique data sources internally? Uh we we've mentioned that previously, but that can allow me to to build something that others won't be able to to to build to the same level of of of kind of refinement. Um or that would be specifically tailored to uh my own kind of kind of internal need uh within

within that studio. So that's that's kind of another angle like if you if you do have this this kind of ability to have that edge or you have those those those kind of uh yeah data sources internally that can be huge uh huge benefits. Um um then AI is AI talent is extremely expensive as well. um especially for lower size teams. Uh not every studio can afford like an AI lab with uh with like a few researchers kind of experimenting with um with AI. So um for like the majority of of of gaming companies and studios, publishers like there's a need on reliance on external uh partners to some extent. Uh in any case, um it can help move faster because you kind of leverage tools that have already been produced, but we need to be conscious of the fact that we're still quite early um

in uh those tools kind of maturity and there are a lot of things that still need to be narrowed out in terms of like u production pipelines, processes and how it really fits within um actual kind of kind of game companies. So any kind of AI initiatives uh need to expect some level of customization or kind of working hand inhand with with with external partners to make sure that um what you're deploying kind of really works um for you. Um and then finally it's about like uh keeping focus um is is your company uh building games or building AI models in a way and and what brings the most value to um to your company? And so yeah, the leveraging external kind of kind of uh providers can can definitely help kind of alleviate a lot of the of the distraction associated with with kind of looking into into AI and there's tons of

applications that can already be explored with the solutions that are that are widely um available. Um, so building kind of um internal AI solutions or replicating them is really something where um it makes sense if you're trying to build a competitive edge uh in a specific area. If you want to move faster than competitors and that this kind of justifies the um significant investment that you're going to put be behind like actually developing this this new tool or this new kind of application area. So yeah uh there is value to both. It depends on on on uh the company's size and and priorities. Um but yeah, generally speaking, uh to kind of assess this uh studios need to to really look into uh all those solutions and and really have this case by case by case approach of is it mature enough? Is it bringing uh valuable kind

of efficiency um to to our company? Um and if so moving forward with with uh with this are internally oxol you bring up interesting stuff about the the data right being a big part of that decision uh you know are we sharing data with partners do do partners have data that we don't do we need to like try and build this moat ourselves to have a a competitive moat against competitors especially like a publisher or big studio level where you're like hey we're doing this because we want to be ahead for our you know games under our big umbrella and those sorts of things so we can help partner partners do that sort of thing. You know, it makes me think of um some of the um the studios that will help like uh Voodoo and stuff like that sort of groom and and help these these studios underneath them uh build up what they're doing. And having expertise like that could be helpful. But it also makes me think of like stuff where Roblox for example was touting, hey, we're the only ones who could make this sort of 3D model generative stuff because we have this massive data set of games using like 3D modeling within our sort of

sandbox and we can use that data set to then build a tool that would be very difficult for anyone else to replicate internally or or otherwise. So it is an interesting consideration there like that might be like on a topic by topic case by case basis as you said. uh it makes a lot of sense to kind of evaluate that carefully before making that decision.
Yeah. And and and it inso at like broader changes that will uh likely to happen within within organizations around like how to systematically collect the data that will be helpful to uh fine-tune models or build models because AI models are just as good as the data that you uh feed them um with initially. Um so um companies will also need to to kind of uh like uh think um uh like before even deploying AI like how can we um properly collect data that's going to be that's going to be helpful like if I did like thousands of concepts over the past few years like how can I take the learnings from this

and and actually um make something that that that's valuable how to take value and strike value out of all those learnings and unstructured learnings and data that that that studios can can collect over time. So that's another part where uh again being intentional about the way uh the company structure, the teams are structured, the team kind of work with each others um can can really help enable um longerterm gains and and and opportunities uh for studios when it comes to AI.
Definitely. I mean, it makes me think like that studios especially that do a lot of games in the same genre or like have a lot of like historical data from their own games and they're making those kinds of games going forward can especially benefit uh because they can train off that data. It reminds me what you're saying about um the live ops sort of thing where you're like doing the seasonal content like the remixing kind of thing. if you were making games and then like whether those be sequels or games within a certain genre or uh theme or whatever that you can utilize that

sort of thing to train the models. Obviously training models is kind of a weird thing that's not always accessible and depends on the model and stuff like that. That's a whole technical thing we won't even get into. But I think the big question like h having discussed a lot of this stuff like sort of the the more nitty-gritty with the the details of how studios think about this. The big question is is should most game studios and and you feel free to break this down into individual silos and and categories or whatever be experimenting, looking into toying with or considering AI right now or in the near future or should it be uh most studio should just be like hey let's wait till this stuff's mature we're already like taking enough risk even just making a game right now that sort of thing. What do you think overall on that?
Yeah. Um so I think I think there we we need to to come back to the broader picture of gaming right now uh with um like this need for production cost optimization especially when it comes to AAA kind of projects that have like that

are reaching new heights budget sizes um as well as also the competition from emerging kind of kind of markets that are delivering similar level of of of quality at at a fraction of the cost as well. So um there are like strong external incentives and and pressure for studios to um optimize production costs um for games in general. So that's that's the first thing. The second thing is as I mentioned like AI is already there. Your competitors are using AI already. So um you should probably look uh into it in some ways uh to to see how that could translate to your own needs. And we've mentioned that previously as well. There are already like several careers that are mature enough um to to yield like uh efficiency gains uh within studios already. So uh it's not that much about the maturity anymore. It's

about the ability to um identify those opportunities and then uh manage change internally uh as you kind of integrate those uh those those solutions and then also your developers are already using uh AI. So there needs to be um some level of intentionality there as well in the way you allow uh AI tools to be used and where and um tracking um the potential issues that might come with um with using those those AI tools. So in a lot of ways like you can't really like studios studios will need to um adapt to this this new wave of like AI innovations uh that is that is that is coming. Uh again it's kind of already there. The the one part where um it's it's le less of an obvious kind

of kind of area to focus on would be uh adding gameplay benefits. uh like some studios are kind of experimenting with finding new gameplay propositions using uh using AI uh directly. Um and there are a lot of kind of issues to be narrowed out there like uh what can be enabled by AI, how fun is it? um uh how to navigate consumer adoption, who is actually interested in AI within my my my consumer base and and most importantly even like how um do I monetize this because token usage can become like a huge cost center as well. So how do I deal with that? So all of this this this area really depends on whether you're trying to find the the the the next new shiny thing or or the the the new kind of kind of genre. That's that's going to be um a breakthrough which is definitely something that as an industry

we need to experiment with and and and some companies will find success getting there but it doesn't have to be um a business priority for all studios or all publishers. Um uh there are no like obvious indications right now that uh in 3 years uh consumers will only play games with AI mechanics. Uh we still haven't really proven that AI mechanics can actually be fun and and and bring like like significant added value to um to to players. So I think on the tool side of things definitely they're like pretty much um all studios and and publishers need to stay on top of what's going on there um and understand those designation and and where they fit within their their production pipeline. On the content side, it really depends on on your company strategy. Uh but it is far from from being like a a must have to kind of build AI features in in your cake.

Yeah, I mean there's a lot to consider there, but uh I knew it wouldn't be an easy yes or no answer, which is which is good here. So, it depends is always the answer, right? But, uh but you brought up an interesting point in there of even if the answer is no, that doesn't necessarily mean that employees within your company uh or external partners, contractors, things like that won't necessarily be doing that. And I think of like uh this comes up a lot in Marvel Snap, for example, where they contract out a lot of artwork and it's not a hidden thing, right? like they have the indicator of who the studio is that does the artwork or the particular artist or things like that and there's these sort of witch hunt accusations sometimes around is that AI generated art and you see that sort of thing and and that's obviously going to get crazier and crazier right where everyone's going to be accusing everything potentially of being AI art but it does bring down that sort of idea of like governance that you mentioned before but not not just in the organizational level of where you're like hey here's how we're using AI it's also are you using AI and not telling us because that can be a huge brand risk if

you if you're unaware, right? If you just oh, we have no idea that someone did that. Like, so uh the the the controversy that came up with um Marathon, for example, wasn't around AI, but it was around uh plagiarism, right? Where it was like, oh, someone that worked at the studio but no longer works here plagiarized from that potentially and therefore like well, we have to do this huge purge now. But you could see the same thing happening with the AI generated art. It's like, oh, that particular person within our company was using a whole bunch of generative art and our customer base is not interested in that. Now, we've got to go through purge and redo all that. So it seems like in itself regardless of whether you'd like to bury your head in the sand and be like uh we're not interested in AI we're focused to what we're doing you're still going to have to be like but is anyone within the company doing that that we need to know about or our contractors who maybe these and I can see that even more in contractors looking to cut corners looking to shave costs or keep costs down in bids things like that just being like I mean localization in general I feel like if you're if they're not super clear with you there's a good chance they're using AI without telling you like just because

they're going to be looking for an edge and able to keep costs down. So definitely something to consider. Uh but I think you mentioned three years ahead. So I I'm kind of curious the next two years. What do you think that looks like? Put on your little nest hat here.
You can you can feel free to be a little bit, you know, optimistic, but this is the the no hype version of what do you think the next maybe six months to two years looks like uh in game development in regards to AI and sort of the industry in general and games.
Yeah. So yeah, um like as as I mentioned, I think um we're overestimating a lot of like what what um AI can do. Um right now um and and in the next two years, we're uh going to need to kind of face uh like the harsh realities that comes with um AI, which is that we still need to do part of the work. You need to deal with governance. you need to uh deal with um how to

properly implement um manage change, measure success, train your teams on using those um AI tools and this will naturally uh take time. So I think in the next two years we are really going to get into that phase where um AI companies not only double with AI but adopt AI widely. So AI tools will yeah become fairly standard practice across uh multiple processes with uh others that will likely be uh unlocked as uh technology gains some maturity like 3D assets, animation, even coding. Um so these areas will will kind of increasingly be addressed as well on top of the ones that are that we've already kind of kind of um covered. Um so yeah, that's that's that's kind of the first the first thing. Um there there are tons of um needs that that that come with

fully adopting AI. Um especially when it comes to your own teams and and and talents um and uh regardless of like u specific processes, there will be um like a need to progressively adapt to also how those how to think about those tools as well. like we still haven't like um conceptualized fully how uh like a promptbased uh tool uh can be like uh fully leveraged in a way. Um so there will need to be like lots of experimentations and training around how to to deal with those with those uh changes. And I think one of the most concrete change that we're going to see in the next two years kind of aligns with uh broader dynamics within the industry of like increasingly relying on exteral teams uh to to support like very

um narrowed kind of kind of core uh development teams. I think we we're going to see this more and more like small teams that are leveraging external partners or tools to really kind of support their production capacity. um and and helped them kind of reach um um a higher level of of of like ambition.
Obscure, right? Where that was kind of an example of them leveraging a lot of outsource partners to be able to do what they could at that the budget they had.
Yes. Like and and yeah, kind of keeping like a a very kind of kind of focused uh team. And so yes, we're going to see this more and more um uh small teams that are somehow kind of AI enabled um and yeah working externally more more and more uh so it won't be like like a radical transformation like studios will most likely work in a fairly similar way to in two years than

they are they are right now. I like it's not like a um a fundamental reshuffle of everything um we're doing but rather it will be a range of like multiple located pipeline optimizations that will yield like significant costs and um agility benefits. Um so so yeah, I think that's that's really kind of the the the angle people should should should should kind of stick to is is this this idea of like Yeah. it won't like change everything and like it won't be magical and and kind of address um address all my my needs. Uh there are like a lot of of kind of implementation work um to be done. Uh but and at um but at the same time like besides the the kind of shiny things that AI could potentially do, there are like lots of less sexy areas that that can actually be addressed by AI right now. And those should be the ones that

that uh companies kind of kind of uh focus focus on. Uh and then in the next two years as well um we're likely going to see the first generation of like fully AI enabled games uh with new gameplay proposition uh coming to market uh with with these kind of radical kind of gameplay uh innovations and that will inform whether Gen AI can actually provide significant uh gameplay value and benefits to to players. Uh, and so we're likely going to see the first kind of confirmation um there and potentially like the first few um games that that reach like a significant scale while relying heavily on on AI uh game play um AI enabled gameplay. Well, it sounds like at the very least you think AI in some form or another is probably here to stay and that definely it will deliver something and it's just a question of where we can find where it sticks which I think is the most pragmatic way to

look at it, right? Just
we'll we'll do something with it. We spent enough money developing all these tools and figuring stuff out and experimenting that we we'll find some use for it at the very least. It's just a question of how much we could integrate it and whether or not someone could fight. I imagine if someone comes up with a big huge hit that uses AI, then there'll be a million clones all clamoring to do that and investment money and things like that. That's tends to be how it happens. As soon as there's big success, you'll see more of it, but
we'll see, right? But now is the time for some some quick rapid fire ones. So, this is short answers only, potential hot takes if if you got them, but just firing off the hip. So, just just three quick questions before we go. So, first off, the the worst AI decision you've seen? Well, uh not ne necessarily like naming names, but uh like we've seen multiple cases of of um AI being used for key arts. Um and and I think that's that's taking AI uh the wrong way. Like you shouldn't start with your most important assets. You should start with what can be um uh easily uh automated

without like being too visible to um to your your consumers and and and and audiences. So that just shows kind of kind of a lack of internal governance as was as we mentioned and and and in the way you kind of look at at uh at at AI views.
Don't use it for stuff you're just kicking out the door, I guess. Well, what what is the coolest or most exciting use of AI you've seen, even if it didn't always work out the way you'd hoped?
Yeah. Uh yeah, I think so. I haven't like talked too much about like very forwardlooking uh areas, but one that I like a lot are warp models. um like seeing uh applications like Decart uh Osis where you could basically play generate uh Minecraft gameplay in in real time. um there are like multiple uh issues or roadblocks or like it doesn't have like concrete kind of business

applications right now but it's one of those areas where you get a glimpse of something that is radically different and then really change the way you even think about how to build games, what building games mean. So, that's one of those areas where where it kind of opens up like a a really long-term perspective of like how transformative AI can be in the next 5 to 10 years.
Cool. Well, then lastly, the favorite game using AI and that could be in the production process, but even better if it's in a more obvious use. Well, I I think an area where where we see um like AI being ex very very interesting is when AI is put at the center of of fun as I was saying and one game like that is Best Buy AI um which which had some some some really big success um as well and it really kind of perfectly leverages AI chaos to support uh the game play. you you kind of basically engage with a

with an AI that kind of judges your your answers. Uh, and it's it's really fun. Uh, it's it's um really easy to adopt as well for consumer and one way to really engage with with AI from a from a consumer perspective and and yeah, they figured out the fun. Um, so so really interesting one.
Yeah, it sounds like keeping it loose might be a good way to integrate that way. This doesn't have to be a serious game because it probably won't work that way.
Makes a lot of sense. Well, cool. Well, I wanted to thank you first of all for coming on. I really appreciate it. A lot of expertise, a lot of actual practical hands-on use had uh as opposed to I think a lot of the people out there that have mostly just kind of talked about this. Um so really appreciate your insights and I look forward to a lot of uh interesting stuff to go forward. Both some of the stuff you're talking about as well as stuff hopefully you'll be involved in. But uh again, thanks for coming on. Hopefully you out there uh got some good useful tips from this and we'll definitely be you know talking about AI where it makes sense in the future. And obviously if you want to talk to us about AI, make sure to hit us up as well as we are definitely as

France mentioned going be looking into providing some services around that as well u to help people out so that way they're not maybe de-risk a little bit of their internal side of things. Um but anyways, thanks for everyone for listening. Hopefully you enjoyed the show and we'll catch you guys next time. [Music] If you enjoyed today's episode, whether on YouTube or your favorite podcast app, make sure to like, subscribe, comment, or give a fivestar review. And if you want to reach out or provide feedback, shoot us a note at [email protected] or find us on Twitter and LinkedIn. Plus, if you want to learn more about what Navic has to offer, make sure to check out our website, www.navic.co. There you can sign up for the number one games industry newsletter, Navic Digest, or contact us to learn about our wide-ranging consulting and advisory services. Again, that is www.navic.co. [Music] Thanks for listening and we'll catch you in the next episode.