Baidu, Inc. (NASDAQ:BIDU) Q3 2025 Earnings Call Transcript

Baidu, Inc. (NASDAQ:BIDU) Q3 2025 Earnings Call Transcript November 18, 2025

Baidu, Inc. beats earnings expectations. Reported EPS is $1.56, expectations were $1.2.

Operator: Hello, and thank you for standing by for Baidu’s Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Today’s conference is being recorded. If you have any objections, you may disconnect at this time. I would now like to turn the meeting over to your host for today’s conference, Juan Lin, Baidu’s Director of Investor Relations.

Juan Lin: Hello, everyone, and welcome to Baidu’s Third Quarter 2025 Earnings Conference Call. Baidu’s earning release was distributed earlier today, and you can find a copy on our website as well as on Newswire Services. On the call today, we have Robin Li, our Co-Founder and CEO; Julius Rong Luo, our EVP in charge of Baidu Mobile Ecosystem Group, MEG; Dou Shen, our EVP in charge of Baidu AI Cloud Group ACG; and Henry Haijian He, our CFO. After our prepared remarks, we will hold a Q&A session. Please note that the discussion today will contain forward-looking statements made under the safe harbor provisions of the U.S. Credit Securities Litigation Reform Act of 1995. Forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from our current expectations.

For detailed discussions of these risks and uncertainties, please refer to our latest annual report and our filings with SEC and Hong Kong Stock Exchange. Baidu does not undertake any obligation to update any forward-looking statements, except as required under applicable law. Our earnings press release and this call include discussions of certain unaudited non-GAAP financial measures. Our press release contains a reconciliation of the unaudited non-GAAP measures to the unaudited most directly comparable GAAP measures and is available on our IR website at ir.baidu.com. As a reminder, this conference is being recorded. In addition, a webcast of this conference call will be available on Baidu’s IR website. I will now turn the call over to our CEO, Robin.

Yanhong Li: Hello, everyone. In Q3, Baidu Core reported total revenue of RMB 24.7 billion, AI Cloud revenue reached RMB 6.2 billion, increasing 21% year-over-year sustaining value growth momentum. Apollo Go’s growth accelerated sharply. We delivered over 3 million fully driverless operational rides in Q3, representing 212% year-over-year growth, up from 148% last quarter. This quarter demonstrated how AI is driving transformative value across our business. From enterprise services to consumer-facing products to smart mobility, our AI capabilities are delivering proven tangible impact at scale. Starting with the enterprise side, where our AI Cloud business continues to scale with healthy momentum and deliver measurable business impact.

In Q3, AI Cloud continued its strong growth trajectory. Within AI Cloud, the areas most central to AI achieved the fastest growth. In particular, subscription-based revenue from AI accelerator infrastructure surged to 128% year-over-year, becoming the primary driver of AI Cloud’s expansion. This reflects both a healthy shift towards a more recurring, structurally healthier revenue model and the strong demand for our AI products and solutions. Our ability to serve this growing demand stems from our early and strategic deployment across Baidu’s full stack in AI architecture, spanning infrastructure, framework, models and applications, which allows us to support enterprises at every stage of their AI journey. At the infrastructure layer, our AI infrastructure is among the most advanced in China powered by a diverse mix of domestic and international high-performance computing resources, including our own self-developed AI computing architecture.

Through continuous technical innovation, we drive performance and efficiency improvements while consistently reducing inference costs. Additionally, our industry-leading resource management capabilities significantly boost utilization and scalability. These advantages make our AI infrastructure reliable, scalable and highly cost effective for enterprise clients. And the model layer, we feature our self-developed early foundation model, which continues to iterate rapidly. At the recent Baidu World 2025, we unveiled ERNIE 5.0, our first native omni-model, foundation model with exceptional performance in omni-model understanding, creative writing and instruction following. ERNIE not only represents the cutting edge of our AI technology, but also serves as a backbone behind much of the AI-driven innovations across our businesses.

At the application layer, we have a range of AI applications tailored to enterprise business needs. Let me share some examples. The first is [ Famou ] or FM agent, a self-evolving agent, we recently launched that significantly improved enterprise efficiency; built on ERNIE, it autonomously explores countless possibilities and continuously evolve its strategies to identify best solutions for highly complex, constantly changing real-world problems. FM agent is now deployed across industries including transportation, energy, logistics and ports, optimizing complex operations that traditional approaches struggle to handle. Its capability is particularly valuable in China, where we have diverse industrial sectors with numerous scenarios demanding efficiency improvements, when you can meaningfully boost efficiency across such varied use cases, the social impact is profound.

Another example is the Daniel Wu English coach, an ERNIE powered digital employee we created for Yashi Education, featuring the lightness of the well-known actor. It enables users to engage in one-on-one real-time English conversation practice anytime, anywhere. This directly addresses a key challenge. Yashi’s users require frequent on-demand speaking practice, which is difficult to scale with human instructors. The digital employee provides unlimited availability and an immersive engaging learning experience. Besides enterprises, our AI applications are creating value for individuals by enhancing productivity. Baidu Wenku and Baidu Drive, our largest AI applications for individuals, have been revitalized with AI. Their combined MAU has approached 300 million.

In August, Wenku and Drive jointly launched a general-purpose AI agent platform that orchestrates hundreds of specialized agents to complete complex end-to-end tasks through simple natural language interactions. The platform has gained strong traction since launch, demonstrating how AI can meaningfully enhance personal productivity at scale. In the physical world, autonomous driving exemplifies the transformative value of AI, unlocking new possibilities for mobility, safety and efficiency. In Q3, Apollo Go’s growth significantly accelerated to new heights. During the quarter, we provided over 3 million fully driverless operational rides to the public, representing a remarkable 212% year-over-year surge compared to 148% growth last quarter. In October, weekly average fully driverless operational rides exceeded 250,000, marking one of the highest levels achieved in real-world Robotaxi operations globally.

To date, our fleets have accumulated over 240 million autonomous kilometers with more than 140 million of those being fully driverless, maintaining an outstanding safety record throughout. Achieving this rapid expansion while delivering exceptional safety performance is a powerful validation of our technology’s maturity and operational capabilities. We are proud to see our decade-long commitment to autonomous driving now bearing fruit in large-scale operations. Reaching this scale requires maturity across multiple fronts, advanced technology, a rigorous and widely recognized safety record, demonstrated business viability, deep operational expertise and the ability to expand rapidly. These years of unwavering investment have not only given us a first-mover advantage, but more importantly, have built comprehensive capabilities that position Apollo Go as the undisputed global leader in this field.

With this strength, Apollo Go has now entered a phase of rapid global expansion. As of October, Apollo Go’s global footprint expanded to 22 cities, an increase from 16 last quarter. In October, Apollo Go entered Switzerland through a strategic partnership with PostBus, the country’s leading public transport operator. Together, we plan to launch autonomous ride-hailing services in Eastern Switzerland, representing a key step in our European market expansion and another milestone in our global journey. In the Middle East, we secured one of the first fully driverless commercial operation permits in Abu Dhabi recently and deepened our collaboration with local partners. In Dubai, Apollo Go was granted exclusive authorization to conduct self-driving trials on open roads at the fourth Dubai World Congress for self-driving transport in September.

RT6 provided trial rides to global attendees, including government officials, business leaders, media and investors, showcasing our technology’s maturity on an international stage and demonstrating our global leadership. In Hong Kong, where Apollo Go has established by far the strongest presence in right-hand drive Robotaxi markets, we expanded our open road testing zones to include Kolon and Kung Tong District recently, further strengthening our position in the strategically important market. These milestones spanning Europe, the Middle East and Asia validate both our technology’s adaptability and our ability to partner effectively with leading local operators in different regulatory environments. Looking ahead, we will expand to more markets with strong commercial potential and partnership opportunities, maintaining our unwavering focus on safety and operational excellence as we work toward making smart mobility widely accessible.

In our mobile ecosystem, agents and digital humans represent AI-native monetization innovations that are transforming our online marketing business, creating substantial value for advertisers through higher engagement, better lead conversion and stronger ROI. Our agents help advertisers effectively clarify user intent through intelligent multi-round conversations and quickly find out the most relevant high-quality sales leads. This ensures advertisers receive more precise and qualified leads compared with traditional approaches. Building on this capability, agents have evolved into multiple forms; tech-based, voice-enabled and visually-embodied digital humans, each designed to address different scenarios and interaction needs. Such versatility enables advertisers to choose the most effective format for their specific use cases, achieving broader scenario coverage and higher conversion efficiency.

As a result, agents have gained strong traction across diverse industries, including healthcare, business services and lifestyle services. In September, around 33,000 advertisers generated ad spending through our agents on a daily basis. Digital humans also saw strong momentum. Powered by ERNIE, our digital humans provide 24×7 AI-powered live streaming for advertisers at low cost, making professional live streaming accessible across more scenarios and industries. The technology continues evolving, delivering greater realism, more natural interaction and real-time engagement with viewers. This enables performance that surpasses human hosts in many cases, making our digital humans increasingly attractive to advertisers. Adoption has broadened beyond merchants to sectors such as healthcare, automotive and legal services.

We are seeing both existing clients increase their budgets and new clients rapidly coming on board. In September, the number of digital humans live streaming on our platform almost tripled year-over-year, underscoring quick adoption across industries and growing monetization potential. These innovations are already generating significant revenue with fast growth rates. In Q3, combined revenue from agents and digital humans reached RMB 2.8 billion, up 262% year-over-year, validating the strong market appetite for our AI native monetization approaches. Looking ahead, we see substantial opportunities to scale these innovations further, broadening adoption across more verticals and deepening penetration with existing advertisers. Now let me review the key highlights for each business.

In our AI Cloud business, our client portfolio continued to improve in Q3, demonstrating deeper collaboration across the board. Leading enterprise clients increased spending and expanded usage beyond AI infrastructure. Mid-tier enterprise clients delivered healthy growth with both subscription-based revenue and client count rising. Several key verticals saw strong momentum. In embodied AI, our client base expanded to 35 from 20 last quarter, covering nearly all major industry players in China. The automotive vertical also delivered strong growth with revenue nearly doubling year-over-year. In addition, this quarter, we entered into new collaborations with leading players, including Neolix, a major provider of autonomous delivery vehicles in China.

Collectively, these results affirm the broadening adoption and strong recognition of Baidu AI Cloud. To address fast-growing demand, we strategically upgraded our MaaS platform Qianfan to be agent-centric. Qianfan is now positioned to provide not only leading model services with a constantly enriched model library, but also cutting-edge agent development capabilities and best-in-class agent infrastructure. By integrating high-quality proprietary and third-party capabilities and tools, Qianfan enables seamless agent creation and empowers enterprises to accelerate AI native application development. At the application level, we are driving productivity gains, both internally and externally. Internally, our developers widely leverage Comate, our AI coding assistant for developers.

In September, AI contributed to over 50% of new code generation under developer oversight substantially improving our overall engineering and R&D productivity. Comate exemplifies our belief that AI should liberate humans from repetitive tasks and deliver immediate efficiency gains. Externally, we are democratizing AI through Miaoda, our no-code platform. After continuous capability enhancements, we launched the Miaoda’s International version named MeDo in November, bringing powerful no-code capabilities to global users. By removing barriers like specialized training, we aim to empower more people worldwide to innovate and create with AI. On intelligent driving, Apollo Go provided 3.1 million fully driverless operational rides in Q3, up 212% year-over-year.

As of November 2025, cumulative rides provided to the public have surpassed 17 million. In terms of geographic expansion, Apollo Go added 6 new cities, bringing its global footprint to 22 cities as of October 2025. In Chinese Mainland, Apollo Go has already achieved 100% fully driverless operations in multiple cities including Beijing, Shanghai, Shenzhen, Chengdu, Chongqing, Wuhan, Haikou, Sanya and more. These are not pilot zones, but represent real services already open to the public, which speaks to the maturity of our technology and operation. On our asset-light model and domestic partnerships, we also made good progress this quarter. The asset-light approach allows us to expand our autonomous driving services through partnerships and facilitate faster and more capital-efficient expansion.

Following the launch of fully autonomous vehicle rental services with CAR Inc, Apollo Go now enables cross-city travel in Hainan province with fully driverless rental vehicles, offering users a differentiated experience, not typically available through traditional car rental services, particularly for tourism and leisure travel. In addition to our partnership with Hello Ride, we achieved scaled fully driverless operations in 2 cities in China, further validating the feasibility of the asset-light model. Looking ahead, we will continue to expand rapidly while prioritizing safety, accelerating the adoption of autonomous ride-hailing services across broader markets. In our mobile ecosystem, the AI transformation of Baidu Search continued to progress in Q3.

At the end of October, roughly 70% of mobile search result pages contain AI-generated content. We believe this represents an optimal and sustainable level. This quarter, we prioritized enhancing the quality of multimodal content within AI search results while expanding our overall content ecosystem. AI generated multimodal content saw rapid growth in both volume and quality. In particular, with daily AIGC video generation consistently at the scale of millions, our total AIGC video content continues to expand quickly while daily distribution within Baidu App is also seeing strong growth. As content supply improves, users experience richer, more relevant and engaging search results, user metrics continue to improve. In September, Baidu App MAU reached 708 million, up 1% year-over-year.

The daily average time spent per user in Q3 increased 2.3% year-over-year. We are also extending our AI search capabilities to external partners through the Baidu AI search API, which enables integration of our industry-leading search technology that delivers superior accuracy, authority and comprehensiveness. Leading companies such as Samsung, Xiaomi and Honor have already adopted the API. This strategic initiative expands our technology’s reach beyond our own ecosystem, unlocking new business models and creating broader value across the industry. Underpinned by our full stack AI capabilities, each business group within Baidu has seen rapid progress with AI driving both product innovation and business growth. From an AI-native perspective, our portfolio cuts across business groups with a comprehensive range of AI-powered businesses from AI Cloud Infra to AI Applications, such as Baidu Wenku and Baidu Drive and to AI native marketing services, including agents and digital humans, all of which are showing strong growth momentum.

In the physical world, Apollo Go, our largest AI application continues to scale rapidly, and these are just a few examples, underscoring the broad-based growth of our AI-powered businesses and the meaningful business impact our AI capabilities are already delivering at scale. Looking ahead, we will continue to expand our AI-powered revenue streams and strengthen our position to capture the long-term opportunities ahead. We are confident that our AI capabilities will bring even greater transformative value across our portfolio in the years to come. With that, let me turn the call over to Henry to go through the financial results.

Haijian He: Thank you, Robin, and hello, everyone. Robin just mentioned our AI-powered businesses, and I’d like to elaborate. Based on ongoing feedback from investors and to better reflect valuation drivers based on our current portfolio, we are introducing a new AI native view this quarter cut across business groups to track AI-empowered assets company-wide. This new view organized our business according to the nature of our products and services, helping investors better understand the fundamental valuation drivers across our diverse product and service offerings. Going forward, we will provide business updates through this AI native view on an ongoing basis, while continuing to disclose results under the existing reporting methods, giving investors complementary lenses to assess the value of our portfolio.

From this AI native view, we have a rich array of AI in power assets. We are highlighting 3 categories this quarter. AI Cloud Infra, AI applications and AI native marketing services. First, AI Cloud Infra, which refers to the AI infrastructure and platform services we provide to enterprises and public sector. In Q3, revenue from AI Cloud Infra reached RMB 4.2 billion, up 33% year-over-year. We operate one of China’s most advanced AI accelerator infrastructure, enabling highly efficient and cost-effective training and inference across diverse enterprise workloads. Within AI Cloud Infra, subscription-based AI accelerator infrastructure revenue grew 128% year-over-year. Second, AI Applications. These are AI-native or AI-powered product offerings addressing specific use cases for individuals and enterprises, including our flagship software products such as Baidu Wenku, Baidu Drive and digital employee.

AI is transforming how applications create value, enabling far more powerful capabilities that address real-world scenarios more effectively. We built a leading and comprehensive portfolio across both individuals and enterprises. Most of our AI applications are based on sticky subscription models, delivering high-quality revenue. In Q3, AI Applications generated revenue of RMB 2.6 billion. Third, our AI native marketing services, such as agents and digital humans continue to scale rapidly. This represents our second growth curve beyond our legacy business. These innovative products are gaining strong traction with customers seeking performance-driven AI-native solutions. Customers are increasingly willing to pay a premium for cutting-edge AI technology that delivers measurable improvements in productivity, marketing efficiency and ROI.

In Q3, revenue from AI-native marketing services reached RMB 2.8 billion, representing a robust 262% year-over-year increase, accounting for 18% of Baidu Core’s online marketing revenue. Now let me walk through the details of our third quarter financial results. Total revenues were RMB 31.2 billion, decreasing 7% year-over-year. Revenue from Baidu Core was RMB 24.7 billion, decreasing 7% year-over-year. Baidu Core’s online marketing revenue was RMB 15.3 billion, decreasing 18% year-over-year. Baidu Core’s non-online marketing revenue was RMB 9.3 billion, up 21% year-over-year. Driven by the boost of AI Cloud business within Baidu Core’s non-online marketing revenue, AI Cloud revenue was RMB 6.2 billion, increased by 21% year-over-year. Revenue from iQIYI was RMB 6.7 billion, decreasing 8% year-over-year.

Cost of revenues was RMB 18.3 billion, increasing 12% year-over-year, primarily due to an increase in costs related to AI Cloud business and content costs. Excluding impairment of long-lived assets, operating expenses were RMB 11.8 billion, increasing 5% year-over-year. And Baidu Core’s operating expenses were RMB 10.4 billion, increasing 5% year-over-year. Baidu Core SG&A expenses were RMB 5.7 billion, increasing 14% year-over-year, primarily due to an increase in expected credit losses and channel spending expenses. SG&A accounted for 23% of Baidu Core’s revenue in the quarter compared to 19% in the same period last year. Baidu Core R&D expenses were RMB 4.8 billion, decreasing 3% year-over-year. R&D accounted for 19% of Baidu Core’s revenue in the quarter, which was basically flat from last year.

Impairment of long-lived assets was RMB 16.2 billion, attributable to an impairment loss of Core asset group with our rapid progress in high-performance computing capabilities. We proactively conducted a comprehensive review of our asset base and impaired including, but not limited to, existing infrastructure that no longer aligns with current computing efficiency requirements. This results in a healthier and more optimized asset portfolio that better supports the future growth of our AI native business. Operating loss was RMB 15.1 billion. Baidu Core’s operating loss was RMB 15.0 billion and Baidu Core’s operating loss margin was 61%. Excluding impairment of long-lived assets, operating income was RMB 1.1 billion and Baidu Core operating income was RMB 1.2 billion.

Non-GAAP operating income was RMB 2.2 billion. Non-GAAP of Baidu Core operating income was RMB 2.2 billion, and non-GAAP Baidu Core operating margin was 9%. Total other income, net was RMB 1.9 billion compared to RMB 2.7 billion in the same period last year. Income tax benefit was RMB 1.8 billion, compared to income tax expense of RMB 814 million in the same period last year. Net loss attributable to Baidu was RMB 11.2 billion and diluted loss per ADS was RMB 33.88. Net loss attributable to Baidu Core was RMB 11.1 billion, and net loss margin for Baidu Core was 45%. Excluding the impact of impairment of long-lived assets, net income attributable to Baidu was RMB 2.6 billion, and net income attributable to Baidu Core was RMB 2.7 billion. Non-GAAP net income attributable to Baidu was RMB 3.8 billion.

Non-GAAP diluted earnings per ADS was RMB 11.12. Non-GAAP net income attributable to Baidu Core was RMB 3.8 billion, and non-GAAP net margin for Baidu Core was 16%. We define total cash and investments as cash, cash equivalents, restricted cash, short-term investments, net long-term time deposits and held-to-maturity investments and adjusted long-term investments. As of September 30, 2025, total cash investments were RMB 296.4 billion, and total cash and investments, excluding iQIYI were RMB 290.4 billion. Operating cash flow was RMB 1.3 billion, and operating cash flow, excluding iQIYI was RMB 1.5 billion. Baidu Core had approximately 31,000 employees as of September 30, 2025. With that, operator, let’s now open the call to questions.

Operator: [Operator Instructions] Our first question today comes from Alicia Yap with Citigroup.

Q&A Session

Alicis a Yap: My question is on ERNIE 5.0 that was unveiled at Baidu World recently? And then so how will the new model drive the next stage of application such as the digital humans? And what are the key focus area for earnings, future iterations and also the differentiation?

Yanhong Li: Alicia, this is Robin. Over the past couple of years, I’ve been repeatedly saying that we’re taking an application-driven approach when it comes to earnings iteration. At the Baidu World just a few days ago, we unveiled ERNIE 5.0, our first native omni-model foundation model. It has reached world-class levels in omni-model understanding, creative writing and instruction following, which are very important capabilities to our current and future product portfolio. From ERNIE 4.5 and ERNIE X1 in March to ERNIE 5.0 in November, ERNIE keeps getting better. Digital humans are a good example. Powered by ERNIE, they deliver fluent, contextually accurate and highly expressive dialogue. These are capabilities rooted in ERNIE’s language strength.

Beyond language, our model also drives visual realism, appearance, movement and even subtle micro expressions, all synchronized with the conversation. When these elements come together, the performance of our digital humans is truly exceptional and genuinely persuasive, capable of driving user engagement and purchasing decisions. ERNIE also powers FM agent, our self-evolving agent that significantly improves enterprise efficiency. It has proven to be very effective in industries like manufacturing, energy, finance, transportation and logistics. Similarly, our AI search and cloud business benefit from ERNIE’s capabilities, too. Although ERNIE has delivered remarkable results for these applications, we see a lot of room for improvement. We like to see digital humans sell better than real humans in all kinds of live streaming e-commerce across many product categories.

We like to see FM agents find better and better solutions in more complicated scenarios in all industries. We like to see AI-generated content to match users’ interest better than KOL-generated content. We like to see ERNIE-based agents to be able to tell which piece of content has better quality regarding certain topics and so on and so forth. These are the areas where none of the existing models do a good job, not even close. So we aim to solve this problem. The application-driven approach actually reflects our deep conviction in where AI value will ultimately reside. While economic value today sits largely at the infrastructure layer, in a healthier AI ecosystem, the greatest value should come from applications where products deliver real impact to users, advertisers and enterprises.

Going forward, I think no foundation model can be better than anyone at any aspect. We will continue to focus on making ERNIE strongest where it matters most for our portfolio. Baidu has always been a company with strong belief in technology, and we will continue investing decisively in areas where technology can create real measurable value. So staying close to applications ensures a sustainable path forward for AI development.

Operator: And our second question today comes from Lincoln Kong at GS.

Lincoln Kong: So my question is about the Cloud business. So in the third quarter, we have seen Cloud growth has slightly moderated. So are we seeing any changes in terms of the Cloud demand? And should we expect a re-acceleration in the coming quarters? So what’s your outlook for the next year? And what are the key drivers that should support the sustainable growth of our cloud business?

Dou Shen: This is Dou. Thank you, Lincoln. If you look at our year-to-date performance, our Cloud business is growing well above the industry average. Well, for quarter-to-quarter, there can be some variability, but the overall trend is strong, and we remain very confident about this growth trajectory going forward. On the demand side, enterprises are applying AI across every aspect of the operations, driving strong broad-based demand for AI-centric Cloud services. Within AI cloud, the area most closely tied to AI workloads is scaling the [indiscernible]. Our clients are using our cloud not only for model training, but increasingly for inference tasks. In Q3, AI Cloud Infra revenue reached RMB 4.2 billion, up 33% year-over-year, outpacing overall cloud growth.

And the subscription-based AI accelerator infrastructure revenue grew 128% year-over-year, accelerating from around 50% last quarter. This results both strong — reflects both strong underlying AI-driven demand and a healthier revenue mix. This momentum is supported by our full-stack AI capabilities. At the infrastructure layer, our high-performance AI infrastructure, especially self-developed AI computing architecture continues to see strong adoption driven by superior performance, efficiency and cost effectiveness. Many can start with AI Infrastructure and then expand to additional offerings over time. Also, our Qianfan MaaS platform has been upgraded to be agent-centric. With expanded model libraries, integrated tools and strengthened support for complex agent workflows, Qianfan provides best-in-class agent infrastructure, enabling enterprises to easily build and deploy AI agents at scale.

At the application layer, we provide applications that can be readily applied to real business scenarios. Our cloud growth is not just about investment in AI infrastructure, we attach huge importance to applications. We have a comprehensive portfolio of AI products and solutions that is growing very fast, including digital employee, Yijian, Miaoda, FM agent and so on. So we firmly believe AI applications will create substantial value in our cloud businesses in the long term. So to sum up, if we look at our cloud business on an annualized basis, we believe that our full-stack AI capabilities and the strong demand for AI-centric cloud services will enable healthy, scalable and sustainable growth in the future. Thank you.

Operator: And our next question comes from Alex Yao with JPMorgan.

Alex Yao: The Baidu application evolves into an AI application and web search becomes a building feature for AI chatbots. The line between search and chatbot is getting blurry. How are — based on your observation, how are user behaviors changing? And what is your competitive strategy going forward?

Yanhong Li: Alex, let me answer your questions. And AI chatbot actually [Technical Difficulty] and evolve very quickly. So it’s necessary to stay flexible to offer different products for different scenarios. And within Baidu, we leverage the chatbot capabilities through 2 complementary offerings. The first one is the ERNIE assistant, which is the built-in chatbot inside the Baidu App. This supports multi-round conversations function, calling and thanks for its deep integration with search. Since many users assess the ERNIE assistant directly from search, so you can draw on query contacts and interaction history to deliver a more relevant and personalized answers. It also connects to a set of tools through MPT, allowing the users to move seamlessly from information discovery to task compaction.

And the ERNIE assistant is growing quite fast in our app. You can see that the conversation logs have increased around fivefold year-over-year and the DAU has surpassed 12 million with a very strong month-over-month momentum. And we expect this trend to be further continued in the coming few quarters. In parallel, we also offer the ERNIE bot as a stand-alone chatbot application. While it shares Core capabilities behind ERNIE assistants, the ERNIE bot takes an experimental and innovative approach with a near-term focus on improving retention and long-term ambition to compete at the forefront of the chatbot category. And for example, it provides some cutting-edge multimodel features such as the AI images or [ comic-style ] generations which have been especially popular among the younger users.

And looking ahead, we believe the chatbots are not only all ultimate form of AI applications, the future of AI interactions will be multimodel real-time generative and interactive. And for example, at the most recent Baidu World, we have showcased the upgraded [indiscernible] digital human, which is capable of the instant interactions through the real-time voices and video like live conversations. As many of you may recall that we even had a very small technical hiccup during the live demo, which actually proved that it was truly real time and not prerecorded. And once resolved the digital human responding very vividly and deliver dynamic back and forth conversations that feel generally human. So we will continue to bring these advanced capabilities into search, making it more intelligent, personalized and capable of completing tasks.

This continuous innovation is how we intend to capture the long-term opportunities in the AI area and strengthen our competitive advantages. Thank you, Alex.

Operator: Our next question today comes from Gary Yu of Morgan Stanley.

Gary Yu: And also appreciate the additional disclosure on AI-powered businesses. Could management share more on the growth outlook and also the profitability of Baidu new AI-powered businesses? And how will these categories help accelerate our overall revenue growth going forward?

Haijian He: Thank you, Gary. This is Henry. Let me provide some background on this new AI-native views. Based on the investor feedback, we are seeing a need for greater transparency into our high-growth AI businesses. These views organize our portfolios by product nature, giving investors clearer visibility into the underlying value drivers. We will maintain both this AI native view and our existing reporting methods in parallel, offering complementary perspectives on our business performance. From this new perspective, I think we have a rich portfolio of AI-empowered assets. Let me give some highlights here. First of all, for the AI Cloud Infra, this part includes our industry-leading AI infrastructures containing self-developed AI computing architecture, cloud infrastructure and a best-in-class MaaS platform.

As AI adoption accelerates, demand for robust infrastructure is growing and our differentiated capabilities position us well. We are capturing long-term sustainable revenue and expect margin to improve as utilization increases. Secondly, for the AI applications, this part includes flagship products, for example, of our Baidu Wenku and Baidu Drive. AI has significantly enhanced functionalities across these products. We have one of the China’s broadest AI application portfolios, and most of these applications are subscription based and contributing to higher quality revenue and margins. Third, for the AI native marketing services, including agents and digital humans, this reflects how AI unlock greater efficiency and drive the second growth curve in our advertising business throughout enhanced engagement, conversation and ROI.

This quarter, AI-native marketing services reached 18% of our Baidu Core’s online marketing revenue, up from 4% a year ago, and we expect penetration to continue rising as adoption broadens. Customers are embracing these result-driven AI solutions and are willing to pay for tangible gains in productivities and marketing efficiency. Importantly, this AI-empowered business reinforce one another across Baidu’s ecosystem. And AI embeds deeper across products. So we expect accelerating growth of these businesses. So when we’re looking ahead, we remain confident in their revenue and profitability potential, which we believe will support for a stronger growth trajectory for Baidu over time. Thank you, Gary.

Operator: And our next question today comes from Miranda Zhuang with BofA Securities.

Xiaomeng Zhuang: The question is about the Robotaxi business. So Apollo Go has been accelerating growth this year. So looking ahead, can management update us on Apollo Go for next year and beyond, including your global expansion plans. And how do unit economics look across different markets? And how does management view the long-term profitability potential of the Robotaxi business?

Yanhong Li: This is Robin. If you remember, our Robotaxi’s journey started in 2013. So this is our 13th year. Today, Apollo Go is one of the world’s largest robotaxi service providers. And as of November, we have provided over 17 million rides cumulatively, a level very few players globally have achieved. In China, we are the undisputed market leader. Through the first 3 quarters this year, our ride volumes were over 15x higher than our nearest domestic peers according to publicly disclosed data. All these rides are fully driverless, demonstrating unmatched operational scale and technological excellence. Scale matters a lot. The reason we are able to achieve a leading position in autonomous driving technology on a global basis is that we have the scale.

We have encountered many issues, corner cases others have not seen. We were able to train our models to handle those cases and become smarter and smarter. I think robotaxi has reached a tipping point, both here in China and in the U.S. There are enough people who have chance to experience driverless rides and the word of mouth has created positive social media feedback, which I think will propel the opening or loosening of related regulations. For 2026 and beyond, we will continue to scale up our operations, both domestically and internationally. We will add more cars in our existing cities. We will expand to more cities. We will accumulate more fully driverless mileage and further improve our technology based on the operational data we gathered on the road.

And yes, we need more data to train our models. Better models make the cars safer and faster. We will continue to drive down the cost per mile through technological innovation and operational efficiency. Right now, a few cities have achieved positive unit economics. As we scale, we hope to see more cities turn positive in 2026. Also, we’re scaling through flexible business models, including asset-light models, we are very — we are ready to enter any city quickly once regulatory and market conditions allow. As of October, Apollo Go’s global footprint reaches 22 cities with significant progress in Europe, Middle East and Hong Kong. We’re confident that UE will continue to improve as we scale. So in summary, for 2026 and beyond, we expect strong growth across 3 areas: rapid growth in ride volumes and [ fee ] size, geographic expansion in new markets — into new markets and accelerated adoption of new business models.

We believe Apollo Go is well positioned for continued global expansion and long-term profitability. Thank you.

Operator: And our next question today comes from Thomas Chong of Jefferies.

Thomas Chong: My question is about how is AI search monetization progressing? And what feedback are you seeing from advertisers and users? Can AI native marketing services offset traditional ad business? And how should we think about core advertising profitability going forward?

Rong Luo: Thomas, this is Julius. In October, nearly 70%, 7-0 of the mobile search result pages have content AI generated and multi-model first content. This format is quite unique to us, and we are the first or maybe only one doing this. We expect this level to remain relatively stable as we have largely covered the query types where the AI meaningfully improved the user experiences. Our focus now has shifted to improving the quality, particularly the rich media content like images, videos, and we are seeing very clear improvement in content quality this quarter, which translate directly into the better user experiences. And we can see that the users retention is higher and the users exposed to the AI search results are initiating 6% more queries and spending more time with us.

This tells us that users are finding real value in AI search and engaging more deeply. On monetization, we are actively testing and seeing some encouraging early results. First, we are testing MCP in the commercial modules in the AI search. For example, our e-commerce MCP module peaked nearly RMB 6 million in daily GMV during the recent Double 11 shopping festival. This is a very early stage, but the results are quite encouraging. Second, agents for advertisers are generating over RMB 25 million in daily revenue, and we expect this to grow as we bring more agents into the earning assistance as well. And third, we have started testing the digital human live streaming with the real-time interaction capabilities, try to explore the new ways to create engaging commercial experiences.

And looking ahead, we see the significant monetization potential for AI search, and we will continue testing actively. However, our near-term priority still remains the user experiences over immediate monetization. This AI transformation is necessary for long-term competitiveness and will inevitably create a near-term pressure on both revenue and margins. So we believe this is the right trade-off to capture the large opportunities ahead. Thank you.

Operator: And our final question today comes from Wei Xiong with UBS.

Wei Xiong: Actually, I have a few questions here. First, just a quick one. Could you please explain this quarter’s asset impairment and its rational? And second, what are your CapEx plans for next year? And how should we think about the margin trajectory as AI revenues grow? And lastly, could we please have an update on shareholder returns once the current buyback program expires?

Haijian He: Thanks, Xiong. First of all, on your first question on asset impairment, the background is we are accelerating investments in the latest AI computing technologies without any hesitation. So as part of this effort, we have conducted a comprehensive review of our infrastructure portfolio. Some of the existing assets no longer meet today’s computing efficiency requirements. So we actually proactively did some impairments. After this onetime of impairment, our asset base and portfolio profile is in a much healthy position and better aligned with advanced AI computing demand and higher value application scenarios going forward. Second, on the capital expenditures, we are maintaining a high level of investment. Just to give you one example.

Since Baidu launched ERNIE in March of 2023, we have invested well above RMB 100 billion in the AI investment. Going forward, we will continue increasing our investment intensity in the AI area. We do expect to see greater operational leverage as our AI business scales. We’re executing on 3 fronts. First of all, the asset review and impairments have left us with a leaner and more efficient asset base. Second, we are investing with a discipline to ensure capital efficiency. And of course, thirdly, we are enhancing utilization of our AI infrastructure, for example, through dynamic allocation of capacity across internal products and external cloud services. So as a result of these initiatives, we believe Q3 represents a low point for margins. Looking to next year, we will strive to improve our non-GAAP operational income and margins as these benefits start to flow through.

So on your last point regarding shareholder returns, under the plan and program authorized in 2023, we have already bought back a worth of USD 2.3 billion in shares. We are currently reviewing the future buyback mechanism. We understand we also think it is important to provide a greater certainty and clarity to reduce volatility of buyback programs going forward. We’re also actively exploring diversified return mechanisms, for example, setting a dividend policy potentially. Together, these efforts aim to deliver more consistent values to our shareholders. Thank you.

Operator: Ladies and gentlemen, that does conclude our conference for today. Thank you for participating. You may now disconnect.