Hello, I'm Jeffrey from Kakao's IR. We will now begin Kakao's 2026 third quarter earnings conference call. Today, I am joined by Shina Chung, the CEO, and Jaden Shin, the CFO. Please be reminded that the earnings results are consolidated estimates under the K-IFRS basis and are subject to change upon the auditor's review. Also, forward-looking estimates are based on assumptions, so actual results may differ from figures included in today's presentation. Now, we will have a presentation from CEO Shina Chung. Good morning. This is Shina, CEO of Kakao. In the global B2C AI market, the emergence of new technologies and services is bringing important changes to the competitive landscape for AI agents. In the past, the competitive factor was how accurately AI could answer users' questions and provide useful information. Recently, however, the execution capabilities of AI performing real tasks on behalf of users have been advancing rapidly. As a result, it is becoming increasingly important how many different AI services can utilize and how much real value it can deliver in users' everyday lives. Over the past year, Kakao has introduced a range of AI features and services, experimenting with how KakaoTalk can evolve in the AI area and connect to new growth drivers. Through these experiences, we confirmed the potential to expand AI services centered on KakaoTalk. However, we concluded that to respond to the rapidly changing global competitive environment, we need to advance our existing strategy to the next level. Accordingly, Kakao will evolve its strategy toward connecting the user experiences of various AI services into one and rapidly expanding the execution capabilities of AI. At the center of this strategy is Kanana Space, which we unveiled at the recent if(kakao). Kanana Space is a new AI layer that users can enter from anywhere in KakaoTalk with a light two-finger swipe. Previously, users had to find and navigate to the features or services they needed on their mobile screens to get things done. Going forward, we expect that users will simply make a request by voice or text in a single AI hub called Space, and the AI agent will carry it out on their behalf. At the simple feature level, users can change basic KakaoTalk settings, such as font size. Beyond that, AI agent can also execute frequently used services within KakaoTalk on users' behalf, such as Talk Gift and money transfers. Also, even when users ask a simple question in Space, it identifies context and intent, and depending on the difficulty of the query, calls on ChatGPT for Kakao, Kanana in KakaoTalk, or even Kanvas to provide an answer or perform the requested action. The tasks that can be executed through Space will not be limited to KakaoTalk and are planned to be integrated with external services going forward. In this way, we expect Space to connect the fragmented AI features and services previously provided by individual services into a single touchpoint, delivering an integrated AI services to users. When the everyday conversational context of KakaoTalk is added through our own on-device model, Space can deliver an even more personalized experience. KakaoTalk holds a wide range of information closely tied to users' daily lives, such as appointments, schedules, and interests accumulated in conversations with family, friends, and colleagues. Within the scope users have consented to, Space can understand this context, find the information they need, and connect it to the right next section. This reduces the need for users to explain their situation from scratch every time. As this experience accumulates, we expect a new usage habit to take hold where users naturally turn to AI agents within KakaoTalk. Kanana Space will launch a pilot service in December, starting with users who have pre-registered, and begin evaluation in a real usage environment. We will then improve the service quality based on user feedback and expand the range of tasks AI can perform while scaling up the user base in earnest next year. To build a mass-market AI service that 50 million users can trust and safely use in their daily lives, Kakao has prioritized A2A-based integrations with external partners. However, during the actual integration process, we found that there were more variables than expected. These included not only partners' development resources and timelines, but also the business value of AI agents, which still requires validation and alignment of interests. Recently, global AI agent services have been demonstrating the ability to perform tasks on behalf of users across various services without separate partnerships through CUA approaches that control VMs or local browsers. In fact, we are also seeing active usage among some early adopters. The CUA approach clearly has the advantage of enabling broader and easier integration with long-tail services. However, the short-head players holding meaningful positions in each vertical have already begun restricting access by AI agents through browsers. In addition, as browser-based execution allows greater flexibility, token consumptions also rise significantly, and the success rate and the stability of actual tasks will still need further advancement. Furthermore, to implement an end-to-end process through payment via CUA, a privacy protection framework tailored to Korea's local environment must be established. Taking into account the scope and speed of expansion of task AI agents can confer, the value of the agentic experience users feel as a result, and the sustainable cost structure for use by the entire population, the optimal approach for Kakao is to pursue direct integration and CUA in parallel. Using the CUA approach, we will rapidly expand the ecosystem across a variety of long-tail services and begin validating user demand and business value. At the same time, based on validated demand and business value, we will continue to pursue direct integrations with major services in each vertical through partnership-based A2A and MCP as before. Through ongoing collaboration with key external partners, Kakao was able to identify in detail prerequisites for agency AI integration and also confirm the limits of resources partners can commit. Accordingly, we have built technical foundations such as Agent Builder and PlayMCP to minimize the direct resources partners need to invest. In addition, we have also secured our own model specialized agentic actions and browser control capabilities on par with global competing services. On efforts over the past year, where meaningful process through which Kakao accumulate the technologies and experience needed to build an agency AI ecosystem. At the same time, it was an opportunity to confirm the strong needs of partners who want to use KakaoTalk as a key user acquisition channel in the AI era. Going forward, we will rapidly expand the execution scope of AI agents and the service ecosystem so the users in Korea can experience the new value of agentic AI in their daily lives. There are services where you can see how Kakao's browser control technology is actually implemented in Kanvas, which we unveiled at the recent if(kakao). Kanvas is Kakao's first AI service designed as a productivity tool. Unlike the VM approach, which operates a browser on a separate virtual computer, Kanvas uses a local browser control approach that runs and controls the browser within the user's PC environment. With Kanvas, user can search for information and organize materials and even automate the repetitive tasks. For example, an office worker can entrust the agent with the service of task previously handled by switching across multiple programs, from gathering work files scattered across their PC to finding necessary information on the web, writing reports, and sharing with the colleagues. Users can also easily create specialized agents with simple natural language instructions, and we plan to introduce an agent marketplace where users can share the specialized agents they have created with anyone. As Kanvas is integrated with KakaoTalk, users can give tasks to agents in the familiar chat window and receive the results of completed work back there as well. Through this, we aim to show the potential for KakaoTalk to expand beyond the space for everyday communication into touchpoint for execution, where AI carries out users' various work and tasks on their behalf. Kanvas already began internal beta testing last week. Kakao will launch the pilot service of Kanvas Space in December and is also preparing the official launch of AI for All and Kanvas within this year. In addition, active users of our already launched AI services are also trending upward. As we shared on last quarter's earning call, we are fully on track to achieve our goal of 10 million monthly active AI users by end of this year, and we are building the foundation to secure more than 20 million daily active AI users by 2030. As CEO, I humbly accept the painful assessment that the pace of AI service adoption this year has fallen short of the capital market's expectations. However, amid uncertainty created by the great wave of AI, Kakao has continued a variety of experiments and attempts to position itself as a winner to sustain its high growth. During this period of governance transition, the gap between the market's current valuation of Kakao and the future growth potential we see internally, based on our fundamentals, has become wider than ever. Accordingly, as disclosed just a moment ago, we have decided to repurchase and cancel KRW 150 billion worth of treasury shares. Beyond the shareholder return, Kakao believes that the most important thing is to concentrate all of the resources on rapidly introducing AI services that exceed the market's expectations. We will expand our AI services with greater speed and live up to our shareholders' expectations through tangible business results and enhanced corporate value. Next, Jaden, our CFO, will present the 2026 third quarter financial results. Hello, this is Jaden Shin. I will now present Kakao's consolidated financial results for the third quarter. I will now present Kakao's consolidated financial results for the third quarter. Consolidated revenue for the third quarter was KRW 2 trillion 86.7 billion, up 6% YoY and down 1% QoQ. Platform revenue reached KRW 1 trillion 235 billion, growing 17% YoY and remaining broadly flat QoQ. First, revenue for Talk Biz, Kakao's core business, was KRW 632.9 billion, up 13% YoY and down 2% QoQ. Third quarter Talk Biz advertising and subscription revenue reached KRW 391.5 billion, up 11% YoY and down 2% QoQ. Starting with Business Message, revenue grew 7% YoY despite a high base from the government's consumer relief coupon program in the same quarter last year. Excluding this one-off base effect, advertiser demand for Business Message remains solid. Business Message has firmly established itself as a core communication channel that meets advertisers' CRM needs. We are also strengthening its growth foundation by introducing various message products that improve users' ad experience and advertisers' campaign efficiency. With YoY revenue growth already accelerating again in October, we are confident that Business Message can return to double-digit growth in the fourth quarter. Moving on to Talk DA, revenue grew 35% YoY, supported by broader advertiser demand and a more diverse product lineup. Since the launch of feed ads, we have continued to attract small and mid-sized advertisers that had not previously advertised with Kakao. We have also introduced product catalog ads and engagement ads, making it easier for advertisers to run campaigns and addressing a wider range of marketing needs. These efforts continue to attract new advertisers and encourage existing advertisers to increase their marketing spend. With this strong growth foundation, we expect Talk DA to comfortably maintain double-digit growth in the fourth quarter, despite a high base from the launch of feed-based services in the fourth quarter last year. Moving on to commerce, third quarter Talk Biz commerce GMV was KRW 2 trillion 300 billion, up 13% YoY and 7% QoQ. Starting with Talk Gift, performance benefited from Chuseok shifting from the fourth quarter last year to the third quarter this year. We strengthened our product lineup, particularly in fresh food and health food, and actively ran holiday promotions. This Chuseok, we also attracted consumers looking to purchase holiday gifts to deliver in person, further broadening our buyer base. As a result, Talk Gift recorded its highest-ever monthly GMV in September. Self-purchases on Talk Gift also continued to grow through regular promotions such as For Me Week. In the third quarter, the number of self-purchasing customers grew 23% YoY, while self-purchase GMV increased 33%. The Chuseok peak season, together with expanding self-purchases, drove 13% YoY growth in total Talk GMV. For Talk Store, we expanded collaborations with major brands across various categories, including home appliances and food, and broadened purchase touchpoints through live commerce and influencer deals. As a result, third quarter Talk Store GMV grew 8% YoY. Beyond gifting demand, which has historically driven GMV growth, our commerce business has been actively addressing a wider range of purchasing needs since last year, broadening its role as a commerce platform. Encouragingly, self-purchase accounted for around 30% of total commerce GMV in the third quarter. We will continue expanding our products and services into everyday consumption, enabling customers to enjoy a wider range of shopping experiences within KakaoTalk. For reference, commerce revenue was KRW 241.3 billion, up 16% YoY, supported by higher 1P sales during the Chuseok peak season, and remained broadly flat QoQ. Platform and other revenue reached KRW 602.1 billion, up 21% YoY and 3% QoQ. Starting with mobility, steady revenue from its existing businesses was complemented by strong performance in new businesses, supporting continued YoY revenue growth. For Kakao Pay, growth slowed QoQ amid stock market uncertainty. On a YoY basis, however, both revenue and operating profit grew significantly, supported by balanced growth in financial and payment services. Pay also recorded a double-digit operating margin for the third consecutive quarter. Moving on to the content segment. Third quarter content revenue was KRW 851.7 billion, down 6% YoY and 2% QoQ. First, story revenue was KRW 200.6 billion, down 17% YoY and 5% QoQ. Piccoma and Kakao Entertainment's story business will maintain their focus on profitability while sourcing new IP and extending the life cycle of existing IP to build medium-to-long-term growth drivers. Next, music revenue was KRW 508.3 billion, down 10% YoY and 9% QoQ. Despite solid MD and licensing revenue, including aespa's IP collaborations, revenue declined due to fewer album releases by major artists and fewer large-scale concerts. Lastly, media revenue was KRW 142.8 billion, up 49% YoY and 44% QoQ, reflecting higher revenue recognition based on production progress for major titles. Next, regarding operating expenses, third quarter operating expenses were KRW 1 trillion 846.4 billion, up 6% YoY and 1% QoQ. Labor costs increased 4% YoY, reflecting one-off performance bonuses at certain subsidiaries. As we maintained a conservative hiring stance, they remained broadly flat QoQ at KRW 446.2 billion. Marketing expenses were KRW 89.7 billion, down 2% YoY and 7% QoQ, as the content segment continued to focus on efficient marketing spend. For reference, marketing expenses accounted for 4% of consolidated revenue in the third quarter. Cost of revenue was KRW 790 billion, up 13% YoY and 6% QoQ, reflecting higher media revenue and expanded 1P sales in commerce. Outsourcing and infrastructure costs declined 2% YoY as fewer large-scale concerts in the music business reduced outsourcing costs. On a QoQ basis, however, costs increased 8% to KRW 240.8 billion, reflecting higher infrastructure demand for AI model training and key service operations. Depreciation and amortization expenses were KRW 188.8 billion, down 3% YoY and 1% QoQ. The decline reflected cost efficiencies from reduced reliance on external data centers and greater utilization of our own data centers, as well as lower amortization of music-related intangible assets. Consequently, third quarter consolidated operating profit was KRW 240.3 billion, up 7% YoY and down 13% QoQ, with an operating margin of 12%. For reference, standalone operating profit for the third quarter was KRW 107.8 billion, up 17% YoY. The standalone operating margin improved by approximately 1% point up to 17%. Moving on to non-operating item and net income. Third quarter consolidated net income was KRW 177.7 billion, down KRW 15.2 billion YoY, but up KRW 159.7 billion QoQ. The YoY decline was due to a non-operating loss of KRW 16.7 billion compared with non-operating income in the same quarter last year. Last year's results included gains from the sale of stakes and associates. This quarter, lower exchange rates also led to higher foreign exchange losses on foreign currency deposits and trade receivables held by our subsidiaries. On a QoQ basis, income tax expense and losses from discontinued operations were significantly lower than in the second quarter, when the items reflected the simplification of our governance structure. As a result, net income improved substantially QoQ despite the non-operating loss. Lastly, total CapEx for the third quarter was KRW 186.3 billion, remaining at a similar level YoY and QoQ. This consisted of KRW 140.4 billion in PP&E and KRW 46 billion in intangible assets. 지금부터 질의응답을 시작하겠습니다. 질문을 하실 분은 전화기 버튼의 별표와 1번을 누르시기 바랍니다. 질문을 취소하시려면 별표와 2번을 누르시면 됩니다. Now Q&A session will begin. Please press star one, that is star and one, if you have any questions. Questions will be taken according to the order you have pressed the number star one. For cancellation, please press star two, that is star and two on your phone. 처음으로 질문해 주실 분은 HSBC의 김준현 님입니다. The first question will be provided by Junhyun Kim from HSBC. Please go ahead with your question. 네, 질문 기회 감사드립니다. 두 가지 질문이 있는데요. 첫 번째는 최근에 글로벌 AI 사업자들을 보면 AI 에이전트 활용 범위를 빠르게 확대하고 있다 보니까 경쟁도 본격적으로 시작이 되는 것 같습니다. 그래서 이런 환경 속에서 카카오가 기존의 카카오톡을 AI 전략의 중심으로 두는 이유가 무엇인지 궁금합니다. 특히 글로벌 경쟁사들을 보면 다양하게 새로운 서비스를 런칭하는 방식이다 보니까 이런 전략 차이가 어떤 영향을 미칠지, 그리고 카카오만의 약간 차별화된 경쟁력은 무엇이라고 보는지 궁금합니다. 아무래도 더 많은 외부 파트너 확보도 그중 하나일 것 같은데, 외부에서 봤을 때는 조금 어려운 도전일 것 같기도 해서 질문을 드리고요. 여전히 카카오톡이 메신저 앱으로 인식되다 보니까 저희의 AI 서비스 이용자 기반을 확대하기 위한 전략이나 그런 계획이 있으면 설명 부탁드리겠습니다. 그리고 두 번째 질문은요, AI 수익화 관련돼서 질문을 드리고 싶은데, 아무래도 가장 큰 영향이 광고 사업일 것 같고, 기존 광고 사업의 경쟁력 강화랑 새로운 광고 수익화 기회 창출, 이렇게 어떻게 기여가 될 수 있을지 구체적인 추진 방향과 함께 설명을 해주시면 감사하겠습니다. 또 광고뿐만 아니라 새로운 수익화 모델을 계획하고 계신지, 그리고 향후 AI 수익화에 있어서 가장 중요하게 봐야 할 게 광고일지 아니면 그런 새로운 모델일지 설명해 주시면 감사하겠습니다. Thank you for taking my question. I would like to ask you two questions this morning. Recently, we've seen global AI companies expand the scope of their agentic AI. So I would like to understand as to what competitive edge Kakao has vis-a-vis these other global players. I would like to first understand as to the key rationale behind you implementing a KakaoTalk-centric and AI-centric KakaoTalk strategies, and I would like to understand how your service offerings will be different from that of the global players. What is the differentiating factor that Kakao can offer to the market? And I would think that one of those competitive edge would be your partnership with the outside external partners. So if you could provide some insight on that would be helpful. And also because Kakao is mostly considered as a messenger platform, would like to understand as to what your plans and strategies are in expanding your user base. Second question, would like to understand as to what your plans are relating to monetization of AI. I would think that because your AI business takes up a big portion of your key business domain, strengthening the competitiveness of ad business must be one pillar, and the other will be creating new opportunities. So would like to know as to how these different effort is going to contribute going forward. Therefore, what are some of the new monetization models that you are currently considering? Do you believe going forward that it will be from the advertising business or from the new monetization model that you think is going to make bigger contribution? 네, 첫 번째 질문에 대해서 제가 답변드리겠습니다. 글로벌 경쟁 환경 속에서 카카오톡 기반으로 하는 이유와 그리고 AI 차별화 전략에 대해 질문 주셨는데요. 최근에 여러 AI 에이전트들이 출시되고 있는 가운데 이러한 서비스들이 이용자에 대한 이해를 높이고 개인화를 시작하는 첫 단계는 대부분 이메일이나 캘린더, 메신저와 같은 외부 서비스를 연동하는 것입니다. 별도의 AI 앱은 개인화에 필요한 정보를 확보하기 위해 외부 플랫폼과의 연결에 의존할 수밖에 없고, 해당 플랫폼에서 허용하는 정보와 접근 범위에 따라 제공할 수 있는 경험에도 제약이 생길 수 있습니다. This is Shina. I will respond to the first part of your question relating to under the current global competitive environment, what is the rationale behind us having that focus on KakaoTalk? As you know, many AI agents are currently being launched across the world, and the first step to personalize is to have the agents first understand the users. Way of doing that is to integrate with external services such as emails, calendars, and messengers. So if you look at AI standalone apps, it must be connected to external platform, and the experience thus is going to be limited subject to the scope and information access that the platform allows. 반면 카카오톡에는 이미 이용자의 일상과 밀접한 다양한 정보와 관심사, 관계의 맥락이 축적되어 있다는 점에서 출발점이 다릅니다. AI 기술과 실행 역량이 빠르게 고도화되더라도 5,000만 이용자가 오랜 시간 서로 대화하며 형성해 온 관계 네트워크는 단기간에 확보하기 어려운 카카오만의 강력한 경쟁력이라고 생각합니다. But the starting point is different for KakaoTalk because context is already there, what users are interested in and the relationship that they have. So even with fast advancement of AI technology and execution capabilities, Kakao's unique moat is the relationship network built by 50 million users through their engagement over the long period of time, which cannot easily be mimicked by others. 여기에 이용자의 동의를 바탕으로 각 서비스에 축적된 기억과 선호가 연결되면 AI 서비스나 에이전트가 달라지더라도 이용자에 대한 이해를 유지하면서 매번 자신의 상황을 설명하지 않아도 필요한 순간에 적절한 도움을 제안하고 실제 행동까지 연결할 수 있을 것이라 생각합니다. When we bring memory and preference based on users' consent, even though AI service and agents may undergo changes, there's no need for users to explain themselves every single time because AI will inherently understand the user, helping the user with suggestions and leading to actions. 특히 저희는 카카오톡의 관계 네트워크가 사람과 사람의 소통을 넘어 AI 에이전트 간 소통과 협업으로 확장될 수 있다는 점에 주목하고 있습니다. 카카오톡에서 이루어지는 대화는 단순한 정보 교환을 넘어 가족이나 친구, 동료와 약속을 정하고 서로의 일정을 맞추거나 다양한 일을 함께 결정하는 과정이기도 합니다. 이러한 소통의 구조는 AI 에이전트들이 각자 이용자를 대신해 정보를 확인하고 조건을 조율하며 협력하는 방식과도 본질적으로 닮아 있습니다. 따라서 AI가 대화의 맥락을 이해하고 실제 일을 수행할 수 있게 되면 카카오톡은 이용자와 AI 에이전트 간의 소통은 물론, 에이전트들이 서로 협력해 이용자를 대신해 일을 처리하는 공간으로 발전할 수 있을 것이라 예상합니다. We believe KakaoTalk-based relationship network can go beyond communications between people and expand to communication and collaboration between agents. Conversations within KakaoTalk is a process of making time commitments to friends and families, align each other's schedule, and making decisions together. This mimics the way that AI agents can collaborate in checking the information and coordinate in different terms and conditions on behalf of the users. If AI can understand the context of conversation and dialogue that takes place and actually perform the task, KakaoTalk will evolve into a space where not only users and agents interact, but where agents will collaborate to perform work on behalf of users. 나아가 이러한 관계 네트워크는 AI 이용을 빠르게 확산시키는 동력이 될 수 있습니다. 한 사람이 AI에 맡긴 일의 결과를 가족이나 친구와 공유하면 이를 계기로 기존에 AI를 적극적으로 사용하지 않았던 사람들까지 AI 활용을 시작할 수 있습니다. 이렇게 AI 이용자가 많아질수록 에이전트 간 협업과 소통의 기회도 늘어나고, AI를 통해 해결할 수 있는 일이 더욱 다양해지면서 이용 빈도와 활용 범위가 함께 증가하는 선순환을 만들어낼 것으로 기대합니다. Relationship network can facilitate the spread of AI usage. If one shares the output of AI with friends and families, then others will start to use it, even people who have not actively used such AI services. With more people using the agent, more opportunities for agents to collaborate and communicate with each other will take place, and there will be more tasks that AI can handle, which will lead to higher frequency and scope of use. We expect to be able to establish a virtuous flywheel. 두 번째 질문, AI 기반의 광고 수익화 추진 방향에 대해서 질문 주셨는데요. AI 서비스가 카카오톡 내에서 확산되면서 광고 사업에는 새로운 수익화 기회가 크게 확대될 것으로 전망하고 있습니다. 이용자와 AI 간의 상호작용이 활발해진다면 그동안 파악하기 어려웠던 이용자의 의도와 맥락을 이해할 수 있게 됩니다. 기존 검색 광고의 문법과는 다르게 AI 서비스에서는 이용자의 직접적인 검색 행위가 없이도 의도를 파악하여 필요한 상품이나 서비스를 적절한 시점에 추천할 수 있게 되면서, 그동안 카카오에 없었던 검색 광고와 유사한 새로운 광고 수요를 창출할 수 있을 것으로 기대합니다. Responding to the next question about our monetization strategy based upon our AI-centric advertisement approach, as AI service in KakaoTalk adoption increases, we expect new opportunities in advertisement monetization as well. If interaction between the user and the AI grows, we can start to understand the intent and context much better, which was difficult to do in the past. Unlike the conventions of search ad, AI service will be able to recommend products and services at the right timing without user engaging in the act of searching. We believe that this would create new demand that Kakao previously did not have, but which is similar to search ad. 또한 앞으로 카카오톡 내 다양한 AI 서비스와 에이전트가 확대되면 이용자가 상품과 서비스를 탐색하고 추천받는 접점이 늘어나면서 새로운 광고 지면과 매출 기회도 함께 확대될 것으로 보고 있습니다. With more AI service and agents being embedded inside KakaoTalk, there will be much more touchpoint for search and recommendation, and we expect that this will create new advertisement inventory and revenue opportunity as well. 동시에 AI 기술을 활용해 광고 사업의 경쟁력을 강화하고 광고주의 성과를 개선할 계획입니다. 기존 머신러닝 기반 추천과 타겟팅 기술을 고도화하는 동시에, 이용자의 행동과 선호, 경험을 AI가 이해하고 활용할 수 있는 공통 메모리 인프라를 내년 1분기까지 구축할 예정입니다. 이를 통해 기존 클릭이나 구매 이력을 넘어 이용자의 관심사와 선호, 구매 의도까지 종합적으로 반영하는 정교한 광고 추천이 가능해질 것으로 기대합니다. Also, we will use AI technology to strengthen advertisement business and enhance advertisers' performance using machine learning to scale up recommendation and targeting. We will also complete common memory infrastructure by the first quarter of next year, which will enable AI to understand and utilize users' behavior and experience-related information. Using this data, we will be able to offer more precise ad recommendation that considers even the preferences and purchase intent of the users, going beyond simple usage of track records on purchases and click-through rates. 올해 12월에는 광고주의 광고 집행과 운영을 지원하는 AI 에이전트인 AI Crew의 비공개 베타 테스트를 시작할 예정입니다. AI Crew는 광고주가 대화형 인터페이스를 통해 비즈니스 목표를 입력하면 AI가 적합한 광고 상품과 운영 전략을 제안하고, 광고 설정부터 성과 분석까지 전반적인 과정을 지원하는 서비스입니다. 이를 바탕으로 광고 운영에 익숙하지 않은 중소형 광고주들도 보다 쉽고 효율적으로 광고를 집행할 수 있도록 하고, 기존 광고주의 운영 효율도 높여 신규 광고주 유입과 광고 집행 확대를 이끌어내고자 합니다. In December, AI Crew will go through closed beta testing, which is an agent that supports advertisers to manage and execute their advertisement. It will be based on conversational interface, so when advertisers enter their business target, AI will suggest the most befitting product and services as well as most effective strategy, supporting the whole process of setting up the ad to performance analytics. With this, even smaller and mid-sized companies can run their advertisement more efficiently, and overall ad efficiency will be enhanced. Through this approach, we are going to expand on onboarding of new advertisers as well. 이러한 전략을 바탕으로 내년부터는 광고 지면 확대 중심의 기존 성장 방식에서 나아가 AI를 통한 광고 효율 개선과 새로운 수익화 기회가 실질적인 매출 성장으로 이어지는 모습을 보여드리겠습니다. Based on this strategy, we will be able to create new monetization opportunities starting next year and drive revenue growth moving beyond the growth of simply expanding ad inventory. 다음 질문 받겠습니다. Next question, please. 다음으로 질문해 주실 분은 교보증권의 김동우 님입니다. The following question will be presented by Dongwoo Kim from Kyobo Securities. Please go ahead with your question. 질문 기회 주셔서 감사합니다. 저는 두 가지 질문드리겠습니다. 먼저 4분기 광고와 커머스를 비롯한 주요 사업 실적 흐름을 어떻게 전망하고 계신지 궁금합니다. 또한 연초 제시한 연간 매출 성장률이랑 OPM 가이던스 달성 가능성에 대해서도 설명 부탁드립니다. 두 번째로는 글로벌 빅테크들이 AI 모델과 에이전트 개발에 대규모 투자를 이어가는 가운데 카카오와 자체 AI 기술력을 바탕으로 충분한 경쟁력을 확보할 수 있을지 궁금합니다. 또한 향후 AI 서비스 이용자가 본격적으로 확대되면서 비용 부담도 커질 것으로 예상되는데, 이를 어떻게 관리하고 중장기적으로 AI 사업 수익성을 확보해 나갈 계획이신지 말씀 부탁드립니다. 이상입니다. Thank you for taking my question. First question relates to your outlook for the performance for your ad and commerce business in the fourth quarter. I would like to know whether you believe that you will be able to achieve the annual guidance that you shared in terms of your revenue growth rate and OPM. Second question is that the global big tech companies are making significant investment into their AI model and agent development. I would like to know that with Kakao's own AI technological competitiveness, do you believe that you will be able to achieve ample amount of competitive moat? The second part of the question is that going forward, as there is going to be more AI service users, there is going to be higher cost pressures as well. What are your plans to control that investment-related pressure? Do you believe that from mid to long term, you will be able to ensure AI business profitability? 예, 우선 4분기 실적 전망에 대해 답변드리겠습니다. 먼저 광고 사업의 경우 디스플레이 광고에서 전년 동기 다소 높은 기저가 부담이 되기는 하지만, 비즈니스 메시지 매출 성장이 회복되면서 두 자릿수 이상의 전년 동기 대비 성장률이 유지될 것으로 추정됩니다. 그리고 커머스의 경우는 선물하기 성수기인 추석이 지난해에는 4분기에 위치했던 기저 효과가 있을 것으로 예상을 하고 있습니다. This is Jaejin responding to your question. For Q4 on the performance outlook, first, if you look at the advertisement business, it is correct that the high level of base effect from the previous year on the display ads will work as a bit of a pressure. However, we expect to be able to see a recovery in the top line growth of the Business Message, and we will be able to maintain a double-digit growth rate on a YoY basis. In terms of the commerce business, there is going to be a base effect because Chuseok last year, Chuseok, which is the peak season, was located in the fourth quarter. So we do expect there to be some of a base effect. 계속해서 플랫폼 부문의 성장은 견조하지만, 콘텐츠 부문의 실적 회복은 다소 지연되고 있습니다. 현재 콘텐츠 부문이 탑라인의 성장보다는 수익성 방어에 집중하고 있는 가운데, 전반적으로는 4분기에도 3분기와 유사한 흐름이 예상되는 만큼 수익성 측면에서는 제한적인 개선 흐름이 예상되고 있습니다. Now, broadly speaking, we see the growth from the platform segment quite solid, but it is true that on the content business side, there is a delay in the recovery trajectory. So right now for our content business, rather than focusing on growing the top line, we are more focused on defending the bottom line. So we expect the trend to be quite similar in the fourth quarter compared to the third quarter, which means that we are looking at a limited improvement in terms of profitability. 다만 카카오 별도 영업이익은 올해 3개 분기 연속 전년 동기 대비 두 자릿수 성장세를 이어온 만큼 개선세는 지속될 것으로 보고 있습니다. 따라서 카카오 별도와 플랫폼 부문의 성장이 이어지면서 연초 제시했던 연결 기준 매출 10% 이상 성장, 영업이익률 10% 가이던스는 충분히 달성 가능할 것으로 전망하고 있습니다. That being said, on a Kakao standalone basis, operating profit for three consecutive quarters this year have continued on with a double-digit YoY uptrend. Hence, going forward, we believe this trajectory to continue. Therefore, if you look at Kakao on a separate basis and platform business, growth is continuing. Therefore, we believe that it is amply achievable, meaning the guidance that we have shared at the beginning of the year, which is 10% of consolidated revenue and 10% guidance on the OPM. We expect that is amply achievable. 네, 두 번째 질문에 대해서는 먼저 AI 서비스를 대규모로 확대하면서도 비용 효율성을 확보하기 위한 기술적 접근에 대해서는 제가 말씀드리고, 향후 투자 계획과 재무적 전망에 대해서는 이어서 신종환 CFO가 답변드리겠습니다. 카카오의 AI 모델 차별성은 모든 요청에 동일한 고성능 모델을 활용하기보다 요청의 성격과 난이도에 따라 적합한 모델을 선택하고 필요한 만큼의 연산 자원을 활용함으로써 서비스의 품질과 비용 효율성을 함께 높여가는 것에 있습니다. Regarding the next question, I will address the technical side regarding how to secure cost efficiency while expanding AI-related investment, and I will turn it over to Jaden Shin, who will talk about the investment plan and the financial outlook. Kakao's AI model strategy is not to use high-performance model for all of the requests, but to select the right model depending on the type and the level of requests, and use only right-sized amount of computational resources. Now, this is to drive both quality and efficiency of our service offerings. 카카오톡에서는 고난이도의 코딩이나 전문적인 분석보다는 일상에서 필요한 다양한 작업들을 AI 에이전트에게 맡기는 수요가 다수를 차지할 것으로 예상합니다. 카카오는 난이도가 낮은 요청의 상당 부분이 이용자의 디바이스에서 처리될 수 있도록 카나나 온디바이스 모델을 지속적으로 발전시켜 나가고자 합니다. We expect most of the demand on the AI agent is going to be in relation to everyday tasks rather than highly difficult coding or any request that requires specialized level of analysis. So we are going to continue to evolve Kanana on-device model so that most of the simple and easy requests could be handled on-device. 예를 들어, 안 읽은 대화 요약하기나 보이스톡 내용 정리하기와 같이 직접적인 매출은 발생하지 않지만 이용자가 일상의 편의성을 느낄 수 있는 AI 기능들을 온디바이스로 처리하면서 비용 부담 없이 더 많은 이용자에게 AI 경험을 제공할 계획입니다. 나아가 카나나 온디바이스 모델은 이미지와 음성을 이해하는 멀티모달 역량을 확보하면서 이용자와 다양한 모달로 커뮤니케이션할 수 있도록 발전하고 있습니다. For example, summarizing and organizing conversations and Voice Talk dialogue, which does not directly generate revenue, are still very convenient features for our users, which will be dealt with on-device so that AI experience can be used by as many people as possible without giving them the burden of having to pay for such services. Also, Kanana's on-device model has multimodal capabilities, capable of understanding the voice of the users, and so it will be able to support various modes of communication going forward. 단순한 AI 기능이 아닌 에이전틱 액션을 요구하는 이용자의 복잡한 요청은 온디바이스보다 서버로 라우팅이 되지만, 이 역시 다수의 요청은 자체 모델인 카나나 2.6 플래그십 모델이 수행할 예정입니다. 최근 공개한 카나나 2.6 모델은 이용자의 요청에 맞춰 필요한 도구를 선택하고 API를 호출한 뒤 실행 결과에 따라 후속 작업까지 수행하는 에이전트 역량에서 글로벌 프론티어 모델 수준의 경쟁력을 확보했습니다. On the other hand, complex requests will be routed to the server as it requires agentic-based action and not a simple AI function. But majority of such requests will also be handled by our own proprietary model, Kanana 2.6 flagship model. We recently unveiled this model and we were able to demonstrate that it reaches the level of global frontier models in terms of the agent capabilities, as it can choose the tool based on the user's request, call on the relevant APIs, and perform the follow-up task after receiving the output. 과거에는 이용자의 요청을 실제 작업으로 연결하기 위해 서비스별로 처리 절차를 미리 설계해야 했지만, 이제는 모델 자체가 주어진 목표에 맞춰 필요한 기능을 판단하고 실행 결과에 따라 다음 행동을 결정할 수 있게 되면서 사전에 정의된 시나리오에 의존하지 않고도 다양한 요청에 대응할 수 있는 기술적 기반이 마련되고 있습니다. In the past, we had to design processes in advance in order to connect requests to actual performance of tasks, but now the model decides which function is required based on the objective that is given and performs the next step. We have the technological base to respond to various requests without depending on predefined scenarios. Kanana 2.6 모델 외에도 필요한 경우에는 외부 고성능 모델까지 선택적으로 활용할 예정입니다. 카카오가 기반 기술로 보유한 AI Conductor는 하나의 요청을 완결하기 위해 복잡한 작업을 단계별로 구분하고 각 단계에 적합한 자체 모델과 외부 모델, 전문 에이전트를 연결해 전체 실행 과정을 조율합니다. 이를 통해 모든 요청에 대규모의 연산 자원을 투입하지 않고도 응답 지연과 비용 부담을 최소화하면서 다양한 작업을 수행할 수 있는 구조를 만들어가고 있습니다. We will also use high-performance third-party model if necessary on top of Kanana 2.6 model. Kakao's foundational technology, AI Conductor, orchestrates between proprietary model and third-party model for complex processes required to complete one request. This can help minimize cost and response delays without having to use massive amounts of computational resources. 앞서 말씀드렸듯이 브라우저 컨트롤은 별도의 파트너 연동 없이 다양한 서비스에 접근할 수 있지만, 화면을 직접 분석하고 조작하는 과정에서 상당한 연산 비용이 발생합니다. 실제로 브라우저를 통해 결제까지 수행할 경우 모델 API 호출 비용만 건당 약 800원에서 900원이 소요될 수 있는 반면, A2A와 MCP를 통한 직접 연동이 가능하다면 비용은 약 5원 수준까지 낮아질 수 있습니다. As mentioned before, browser control can access variety of services without any separate partner integration, but it generates huge amounts of computational expense in the process of setting and maneuvering through what is on the browser screen. If you are using browser to, let's say, go up to the payment stage, cost per AI call or retrieval will be around KRW 800-KRW 900. But if direct integration through agent to agent, A2A, and MCP is enabled, it can go down, that cost level can go down to around KRW 5 level. 궁극적으로 카카오는 AI 서비스의 품질과 비용 효율성을 함께 높이는 기술적 경쟁력을 바탕으로 향후 이용자가 전 국민으로 확대되더라도 지속 가능한 서비스를 제공할 수 있도록 비용 효율적인 기술적 기반을 구축해 나가겠습니다. Ultimately, underpinned by technical competitiveness that can both drive AI service quality and efficiency, even if the user base expands to include the entire people of Korea, we will develop a foundation where cost efficiency is ensured. 이어서 AI 투자 현황과 향후 수익성 전망에 대해 말씀드리겠습니다. 재무적인 측면에서는 AI 투자가 실질적인 이익 증가로 이어질 수 있도록 비용 효율성을 철저히 관리하고 있습니다. AI 서비스 확산 초기에는 자본 투자 부담과 설비 운영 위험을 최소화하기 위해 GPU 직접 구매보다는 GPU 클라우드를 활용한 애셋 라이트 전략을 취하고 있습니다. Moving on to the answer on the AI investment update as well as our profit outlook going forward. In terms of the financials, we are rigorously controlling cost efficiency to make sure that AI investment actually leads to profit increases. In the very beginning of this AI spread of AI service adoption, in order to minimize the pressures of capital investment and also risk that may arise from operating the facilities, we are taking on an asset-light strategy using the GPU cloud rather than directly purchasing the GPU chips. 올해 연말부터는 AI 서비스 이용자 기반이 확대되는 동시에 반복 사용률 역시 함께 제고되면서 본격적인 서비스 경쟁력을 입증하기 시작할 것으로 기대하고 있습니다. 초기 AI 서비스 확대 과정에서 필요에 따라 일부 비용이 발생할 수는 있겠지만, 중장기 관점에서는 이용자 증가에 비례하여 비용이 선형적으로 증가하지 않도록 운영 효율성을 지속적으로 점검해 나갈 계획입니다. From the end of this year, we will see expanded user base for the AI service, and also we believe that we will be able to see and our AI services will be able to demonstrate its core service competitiveness with the increase in the usage, repeat usage. In the initial phase, there may be cases where cost may be incurred depending on the necessity, but from a mid to longer term perspective, we are going to monitor our cost efficiency very closely so that there is no linear and proportionate increase in the cost in step with the rise in the number of users. 내년부터는 에이전틱 AI를 활용한 새로운 수익 모델의 가능성을 검증하는 동시에 기존 광고와 커머스 사업 역시 AI를 적극 활용하면서 매출 성장을 가속화하겠습니다. 이를 기반으로 지난 실적 발표 컨퍼런스 콜에서 말씀드린 바와 같이 2028년에는 AI 신규 매출이 톡비즈 매출에서 두 자릿수 비중을 차지하는 새로운 성장 동력으로 자리 잡을 것으로 전망하고 있습니다. Starting next year, we are going to be validating new and different business models and revenue models that incorporate the use of agentic AI, and we will very actively use AI in our ad and commerce business so that we can speed up our top-line revenue growth. Underpinned by these efforts, as mentioned in our previous earnings conference call, in 2028, we expect that new AI revenue will account for a double digit compared against the Talk Biz revenue as a whole, and we think that it will establish itself as a key lever behind new growth. 이러한 매출 확대와 비용 효율화를 통해 2028년 AI 사업은 손익분기점 수준까지 수익성이 개선될 것으로 전망합니다. Driven by such revenue expansion and cost efficiency, we expect our AI business performance to improve to the level of break-even point. 시간이 다소 많이 흐른 관계로 2026년 3분기 카카오 컨퍼런스 콜은 여기서 마치도록 하겠습니다. 해결되지 않은 질문이 있으신 투자자와 애널리스트 여러분들은 카카오 IR로 연락주시면 바로 답변드리도록 하겠습니다. 참석해 주신 여러분 감사합니다. This brings us to the end of the third quarter 2026 earnings conference call of Kakao. For any of the unanswered questions, we at the IR team would be happy to assist you. Thank you.