As I delve into the world of artificial intelligence, I’ve been stunned by the numerous legal risks that businesses face, including those related to copyright, privacy, misinformation, and compliance. While AI is still growing, the risks are growing rapidly with it.
The legal landscape is changing, especially with Europe leading the charge through the EU Artificial Intelligence Act. In the US, almost 20 states have enacted AI-related legislation. Yet, the federal government’s stance on keeping regulations light is evident in the AI policy wishlist from the White House.
Despite the pace at which new regulations appear, AI isn’t reshaping the legal landscape; it’s accelerating it. Risks often trace back to known legal domains such as intellectual property, privacy, consumer protection, and liability.
So rather than considering ‘AI law’ as something entirely novel, it’s more beneficial for me to identify where familiar legal risks stem from within business operations.
I learned that AI risks are prominently apparent in nine business areas. Addressing them doesn’t require legal expertise, just keen questioning to address each concern effectively.
Let me walk you through these areas:
1. Intellectual Property The key question here is: Who owns the work, and are we unknowingly using someone else’s intellectual property?
In AI, ownership is still being defined. However, the U.S. Copyright Office indicates that works purely generated by AI are not protected. Human creativity must play a significant role in shaping AI’s outputs for potential protection.
Using patented ideas conceived by humans but developed with AI remains in question as per the U.S. Patent and Trademark Office’s revised guidelines. These questions aren’t theoretical; they highlight real, current challenges organizations face.
Emerging case filings, such as The New York Times lawsuit against OpenAI, showcase the ever-growing concern over infringement risks.
Two primary risks stand out: unintentional incorporation of protected material in AI outputs and proving ownership without sufficient human creativity involved. In content creation, human involvement isn’t a luxury; it’s an absolute necessity.
2. Advertising and Misinformation The pivotal question I consider is: What message are we crafting, and is it accurate?
AI tools empower us to create vast amounts of content, which is advantageous. However, the risk of distributing misleading or incorrect information exists. I witnessed Google Bard’s numerous errors during a product demo, which negatively impacted its market value by $100 billion.
The emergence of hallucinated data, fabricated citations, and flawed reasoning are challenges businesses face when publishing under their brand. I understand that a single error can severely damage reputation.
3. Privacy and Personal Data The question guiding me is: Are we handling people’s data lawfully, transparently, and respectfully?
Consumer expectations on data privacy have significantly shifted. Legal frameworks like the EU’s GDPR, Canada’s PIPEDA, and California’s CCPA set new standards for collecting, using, and disclosing personal data.
We’ve seen how regulators treat these matters seriously; Italy blocked ChatGPT over privacy issues. Clear policies on data handling are crucial for any organization, and swift communication is required when a customer inquires under prevailing laws.
As I continue exploring AI’s implications on business, these areas underscore the necessity of thoughtful and deliberate strategies to manage AI’s legal implications effectively.
I recently discovered how AI is revolutionizing the way customers find local businesses. Tools like Google AI Overviews, Gemini, and Ask Maps are paving the way for more detailed, conversational searches.
It’s clear to me that traditional search rankings are no longer the sole factor in gaining visibility. Ensuring your business details are complete and accurate—like your Google Business Profile, reviews, and local content—can make a big difference.
I’m excited to join SOCi and Google for an exclusive webinar, Winning the Next Era of Local Visibility, on June 3. It’s a golden opportunity for anyone looking to stay ahead of the curve.
During this webinar, I look forward to learning:
How AI is transforming local search dynamics.
The types of signals that AI considers for recommendations.
Strategies to boost visibility on Search, Maps, and Gemini.
The implications of Ask Maps for your brand.
I’m convinced that AI is already shaping customer discovery, so it’s crucial to ensure your business isn’t left behind.
I’ve noticed that more and more of us are finding ourselves suddenly and, at times, permanently locked out of our Facebook accounts. What used to be just an occasional issue has turned into a widespread frustration impacting not only everyday users but creators and business owners as well.
So, what’s driving this increase? It’s a mix of AI moderation, enhanced security protocols, platform dynamics, and changing user habits. Let’s dive into the underlying factors behind this trend.
The rise of AI moderation — and its tradeoffs
At the core of this issue is Meta, Facebook’s parent company, which relies heavily on artificial intelligence to oversee user activities across billions of accounts. These AI systems are tasked with:
Identifying harmful content,
Thwarting scams and abuse,
Enforcing community standards at scale.
However, there’s a significant tradeoff with AI moderation. Unlike humans, AI struggles to grasp context and nuance, which often leads to:
Flagging normal behavior as suspicious,
Misinterpreting the context of communications,
Imposing account restrictions based on patterns instead of intentions.
This has triggered an increase in false positives, where users find themselves unjustly locked out. Reports of wrongful account deactivation are rampant, typically due to AI-only moderation with little human oversight. Astonishingly, appeals can sometimes be resolved immediately, hinting at minimal human involvement despite official policies.
Account takeovers are increasing
With the surge in cybercrime over recent years, social media platforms have increased their security measures. Facebook now deploys more aggressive signals to spot:
Logins from unfamiliar locations or new devices,
Frequent changes to account settings,
Unusual messaging or posting patterns.
While these steps aim to block malicious actors, they also come with unintended side effects:
Travel, using a VPN, or device changes can cause lockouts,
Legitimate users may be snared alongside malefactors.
When hackers access an account, they often alter the registered email and password, activating security alerts and locking the original owner out entirely. From Facebook’s viewpoint, the account is indeed compromised; however, recovery processes don’t always fast-track access back to the rightful owner.
The role of new features and identity verification
In recent years, Facebook has introduced new security layers, including:
Two-factor authentication,
Identity verification checks,
Paid support options connected to account verification.
While these features enhance security, they also introduce complications, making account recovery more cumbersome:
Adding steps to recover accounts,
Creating barriers for users who struggle with identity verification,
Causing lockouts when verification fails.
Some users report being asked to submit identification several times without resolution, escalating the frustration.
The business incentive behind platform changes
Meta’s motivations for investing in AI moderation and automated enforcement boil down to cost-effectiveness. Automation provides instant scalability, reduces operational expenses, and manages ‘standard’ cases effectively. However, this efficiency comes at a price. For those outside agencies or larger entities operating within Business Manager, finding significant support can be a challenge — leaving some of us without a clear path for escalation.
Meta’s commanding position in the social media advertising space, coupled with robust financial performance and political influence, leads to minimal external pressure to reform its support systems. Meanwhile, search queries related to account recovery are often dominated by Meta’s resources, directing users back into the same narrow support ecosystem, even when alternative solutions might exist.
Platform scale is working against users
One can’t ignore the sheer enormity of Facebook’s operations. With a global user base of billions, even minor error rates can affect millions of individuals. Consequently, Meta’s support systems can’t possibly offer personalized support to everyone, leading to automation as the norm, despite its imperfections.
Additionally, internal fragmentation complicates matters further. Facebook isn’t a singular system — it’s an expansive ecosystem including personal profiles, Pages, ad accounts, Business Manager, and platforms like Instagram, Threads, and WhatsApp. Each operates with distinct rules and support channels. When issues traverse multiple systems — as they often do — no single team fully ‘owns’ the problem, making resolutions slower, more complex, and harder to navigate.
What can seem like a deeply personal problem is often the result of a system optimized for global efficiency, sometimes at the expense of individual support. Facebook aims to minimize risk on a large scale, which can clash directly with the need for prompt, personalized support.
Lack of human support and regaining access
One of the ongoing frustrations isn’t just the lockouts but what follows them. Many users, including myself, face challenges such as:
Limited access to human support,
Automated replies that fail to address the issue,
Confusing or ineffective recovery workflows.
Although Meta is introducing new support tools, much of the assistance process remains automated. If your problem doesn’t fit perfectly into one of their defined categories, resolution becomes even more challenging.
This is primarily because Facebook’s support system is structured around rigid, predefined pathways like “my account was hacked,” “I can’t log in,” or “my ad was rejected.” But most issues don’t neatly fit into one of these categories. They’re often multifaceted: part hack, part lockout, or linked to both personal and Business Manager accounts, further complicated by unclear or incorrect policy flags.
When my situation doesn’t match a single category, the system struggles to process it correctly. Instead of progressing towards a solution, I’m often routed through repetitive workflows — submitting forms that don’t entirely apply — leaving me trapped in exhausting loops without a clear way forward.
William Jennings, who runs WKJ Consulting, a social account recovery consultancy, has observed how these gaps have led to an underground recovery market. Some dubious services even exploit locked-out users by demanding payments through unconventional means like game credits — a problem that persists because legitimate recovery channels remain limited.
Accounts that link through Meta’s Account Center (including Facebook and Instagram) generally have a more straightforward recovery process. Sometimes, users can subscribe to Meta Verified on a linked Instagram account to access chat support and initiate an administrative claim.
Jennings highlights that:
“Meta Verified acts almost like paid protection — approximately 90% effective in preventing wrongful restrictions or disabling, though it doesn’t offer a guarantee if the rules are violated.”
A well-structured recovery method often involves:
Subscribing to Meta Verified to gain chat support,
Filing an administrative dispute with necessary documentation (such as error screenshots, emails, account URL, and ID verification),
Escalating to legal support in more acute scenarios.
It’s crucial that hacked accounts follow dedicated channels like facebook.com/hacked or instagram.com/hacked, and it’s far more effective to focus on prevention than recovery.
After regaining access, it’s essential to undertake steps like enabling two-factor authentication, saving recovery codes, and adopting advanced security measures.
Enforcement has scaled — recovery hasn’t
Facebook lockouts are an inherent consequence of the platform’s development. As Meta continues to emphasize automation and efficiency, many of us engage with systems built for speed, security, and risk minimization.
Most of the time, these systems function silently in the background. But when they falter, it feels abrupt, opaque, and incredibly hard to navigate.
Access to meaningful support often correlates with high ad spend, established business accounts, and tied to paid verification products. This leads to an unbalanced support landscape where major advertisers receive better assistance, leaving individuals and small businesses with fewer options.
For a platform operating on a global scale, this setup is intentional. But for those entangled in the process, it’s incredibly frustrating.
I’ve witnessed firsthand how ChatGPT ads are evolving with self-serve buying options, enhanced measurement features, and a vision to create a scalable advertising platform.
OpenAI is stepping up its game with the ChatGPT ads platform by introducing self-serve buying, CPC bidding, and improved measurement methods to invite more advertisers into its ecosystem.
What’s happening. The ChatGPT ads initiative is shifting from a limited pilot to a broader rollout, providing businesses new methods to purchase and manage their campaigns. Advertisers can now access inventory through agency and tech partners or directly via the new beta Ads Manager, which is currently rolling out in the U.S.
This marks a significant move from a controlled test phase to a promising, scalable ad platform.
Why we care. In the past, access to ChatGPT ads was restricted and costly, limiting it to major advertisers. These updates are lowering the entry barriers, allowing SMBs, startups, and diverse brands to experiment with this channel.
By introducing CPC bidding, ChatGPT aligns more closely with established performance platforms, enabling advertisers to optimize for actions rather than just impressions.
Self-serve Ads Manager. With the new Ads Manager, advertisers gain direct control over campaigns, including budgeting, bidding, creative uploads, and performance tracking.
Even though it’s still in beta, it demonstrates OpenAI’s commitment to building a full-service ad platform, beyond a mere partner-led ecosystem.
Between the lines. This approach is not new. Typically, platforms start with high-touch, partner-led campaigns before transitioning to self-serve tools that enhance scalability. ChatGPT is entering this second phase.
CPC bidding arrives. Originally, ChatGPT ads were sold on a CPM basis. The inclusion of CPC enables advertisers to align expenditures with user actions—a critical evolution for performance marketers.
The nature of ChatGPT queries—often exploratory, comparative, and decision-driven—means that clicks could become an effective indicator of user intent.
Measurement catches up. OpenAI is also introducing pixel-based tracking and a Conversions API, allowing advertisers to measure actions like purchases, sign-ups, and leads.
Notably, this data is aggregated, ensuring no access to individual conversations, emphasizing OpenAI’s commitment to privacy.
Why this is a big deal. Measurement was a major gap in early ChatGPT ads. Without it, justifying ad spend was challenging for advertisers. These updates help bridge that gap, making optimization more feasible.
The ecosystem grows. OpenAI is expanding its network by partnering with agencies like WPP and Publicis Groupe, along with tech platforms such as Criteo and Adobe.
This allows advertisers to buy ChatGPT ads through tools and workflows they are already familiar with.
What to watch:
How quickly self-serve adoption scales
Whether CPC performance holds as competition increases
How measurement evolves to match advertiser expectations
I find it fascinating that Google’s Universal Commerce Protocol (UCP), which was initially limited to AI Mode, is now expanding into regular search results. It’s not just a fleeting trend; some retailers have already begun integrating this technology into their listing pages, making our online shopping experience even more intuitive.
Earlier this year, Google rolled out UCP for AI-agents to facilitate direct purchases from search results. It first launched exclusively within Google’s AI Mode but now, we’re seeing it implemented in Google’s main search results for retailers who support UCP.
Discovering what the UCP checkout looks like was made easier thanks to a post by Brodie Clark. He shared a screenshot showing how Wayfair’s listings on Google Search now feature a UCP-powered ‘Buy’ button. This button is a game-changer because it allows purchases directly from Google’s interface without navigating to Wayfair’s website.
The UCP protocol is paving the way for seamless transactions by establishing a common language for AI agents and commerce systems. No longer do we have to worry about bespoke integrations across different platforms.
Collaboratively developed with big names like Shopify, Etsy, Wayfair, and Target, UCP aligns with existing standards, such as Agent2Agent and Agent Payments Protocols, creating a more cohesive digital commerce space.
What really excites me is the potential for profit growth for retailers who embrace this technology. Although Wayfair might miss out on direct site traffic for specific searches, their affiliation with Google through UCP can still result in conversions.
While it’s clear that not everyone will bypass the traditional shopping journey, as many of us still prefer exploring products on the retailer’s site, the option to ‘Buy’ directly adds a layer of convenience. It’s definitely something worth monitoring as its prevalence in search results increases.
When I heard that Google is unveiling new measurement tools, I was eager to see how these could empower advertisers to connect data more effectively, prove their impact, and make smarter decisions.
Google’s latest tools are designed to give advertisers a better grasp of performance across increasingly complex customer journeys. As AI evolves in transforming campaigns, creative strategies, and targeting, Google is offering updates in data integration, experimentation, and media mix modeling. This helps us, as marketers, convert fragmented signals into actionable insights.
The reason why this matters to me is that while automation has simplified campaign management, understanding what truly works has become more complex. These updates aim to facilitate data connections, provide proof of what’s driving results, and enable smarter budget decisions across various channels. As AI manages more execution, robust measurement becomes crucial for performance and growth differentiation.
Data is the foundation here. Google’s expansion of its Data Manager offers a clearer view of data flow across platforms like BigQuery, HubSpot, and Shopify. A new map-based interface will allow us to visualize connections between data sources and address gaps in tracking or configuration. Additionally, updates to the Google tag are designed to simplify setups, enabling advertisers like me to enhance existing tags without additional coding.
The overall goal is to unify signals and improve data quality, which directly influences campaign performance. Google recognizes that advertisers often face more challenges in data setup and integration than in executing campaigns themselves. By streamlining tagging and data flows, Google aims to eliminate one of the biggest hurdles to effective AI adoption.
Introducing Meridian GeoX, Google provides a new geo-experimentation tool to measure incremental impact across regions. Built on an open-source framework, GeoX integrates with Google’s broader Marketing Mix Model, Meridian, offering a more robust way to validate performance — particularly when presenting results to finance teams.
This signifies a shift from merely correlating data to focusing on causal measurement.
As changes in privacy reduce visibility and make attribution more complex, we’re under pressure to prove impact. Tools like GeoX aim to offer that “ground truth” which many attribution models struggle to provide.
To simplify complex Marketing Mix Models (MMMs), Google is launching Meridian Studio, a Google Cloud-powered platform. This helps teams like mine to build, customize, and scale models more efficiently, focusing on making MMMs less resource-intensive and more accessible for enterprise teams handling large datasets.
What I’m keeping an eye on:
Whether simplified tools will encourage wider adoption of MMMs among advertisers
The effectiveness of GeoX in proving incremental impact
If improved data visibility will lead to better campaign performance
In summary, Google is strategically shifting focus: in our AI-driven world, it is better measurement — and not just better automation — that will dictate success.
Have you ever wondered how Google is ensuring the authenticity of AI bots? I recently stumbled upon Google’s latest experimental method, Web Bot Auth, which aims to address exactly that. This project is currently in a limited testing phase, specifically for AI agents hosted on Google’s infrastructure, but it could be expanded in the future.
In Google’s new help document, they clarify that Web Bot Auth is a “new cryptographic protocol that helps websites validate that bots are authentic.” This innovative approach is designed to automate the authentication of AI Agent bots, distinguishing between genuine and fraudulent bots.
Limited test phase: Google’s team mentions they are “testing the protocol with some AI agents hosted on Google infrastructure.” It’s important to note that not all Google user agents are currently using Web Bot Auth, and the company isn’t signing every bot request with this protocol just yet.
What is Web Bot Auth? Defined as “an experimental cryptographic protocol used to authenticate requests sent by bots,” this method moves away from self-reported headers and IP addresses. Instead, it allows agents to sign their requests cryptographically.
According to Google, Web Bot Auth offers several benefits:
Future-proofing: Supporting a trusted environment where agent providers and websites can mutually verify access.
Cryptographic certainty: Transitioning from easily falsified headers to a verified identity, separate from IP addresses.
Better observability: Gaining clear insights into agent interactions with your content.
Why this matters to us: As AI agents continue to proliferate online, managing access to our sites becomes increasingly complex. This new authentication method could effectively distinguish credible AI agents from deceptive ones, ensuring the right entities access our data.
Since Web Bot Auth is still “experimental,” I’ll be keeping an eye on its development. It might just transform how we manage AI bot access in the future.
In February 2025, I watched a captivating display as humanoid robots graced the CCTV Chinese New Year stage. Although their steps were shaky, it was still delightful to witness.
A year later, these robots at the Spring Festival Gala had transformed, executing smooth moves, somersaults, and full kung fu routines. This rapid progression felt like a decade’s worth of technological advancement condensed into one year.
The technological leap wasn’t limited to robots. It raised a crucial question for digital marketers targeting the largest web population: How have China’s search trends evolved recently?
A parallel in the Chinese search landscape
We’re seeing early signs of a major shift. AI hasn’t replaced traditional search engines yet. Instead of a single breakthrough, change comes from consistent, subtle advancements.
New language models frequently emerge, each refined for a specific niche. Tech companies in China are increasingly sharing these developments openly, with players like Baidu integrating advanced models like DeepSeek into their platforms.
To understand the current search behaviors in China, we need to grasp the shift from simple link searches to more reasoning-based approaches and adjust our 2026 SEO strategies accordingly.
The great narrative fallacy: Is web search dead in China?
There’s a persistent narrative in marketing circles that traditional search, especially on Baidu, is obsolete — that everything is happening on platforms like WeChat. But how true is this?
The social supremacy argument
Indeed, China’s web is mobile-first and dominated by super-apps. While social media is pivotal, it’s not the sole avenue for B2C brands aiming to thrive amidst such a vast, versatile environment.
For instance, platforms like Xiaohongshu excel in lifestyle research, while Pinduoduo and Douyin are social commerce powerhouses. Meanwhile, WeChat is indispensable for everyday tasks.
The B2B reality check
For B2B sectors, dismissing Baidu is a mistake. Metrics show ongoing engagement and tangible results from Baidu SEO, often outshining Western counterparts in lead quality and conversion rates.
When B2B professionals seek industrial solutions, they prioritize verified websites over endless scrolling on social media apps, indicating an undying need for structured web searches.
Mapping the 2026 landscape: Intent-based specialization
As someone deeply integrated into the Chinese market, I’ve noticed that users select tools based on intent rather than defaulting to search engines. It’s an everyday occurrence here.
While optimizing for Baidu, others in my circle might be using Pinduoduo for deals or Xiaohongshu for travel plans. The right tool for the right task wins their clicks.
1. Traditional web search: The authority tier
Traditional search continues to dominate B2B and high-authority research areas. Baidu, despite narratives of its decline, remains central to mobile and web searches.
Baidu: Dominates mobile search with a vast user base. Though AI-driven, it remains a key player in web search.
Microsoft Bing: Offers a professional experience for a tech-focused audience.
Haosou (360 Search): Known for its security and enterprise-centric approach.
Sogou: Integrates with WeChat, bridging between app-based and traditional searches.
Google: Despite restrictions, it’s accessed by tech-savvy users via VPN for global insights.
2. Social discovery: The inspiration tier
Here, search turns into discovery. Users are led by interests rather than predefined keywords, making SEO a matter of being on the right social platforms at the right time.
WeChat (Weixin): For brand news and internal communications.
Xiaohongshu (RED): Essential for lifestyle and luxury brand discovery.
Douyin: Offers visual insights into product utility.
Kuaishou: Used predominantly in emerging markets for grassroots content.
Weibo: Ideal for real-time trends and news.
Bilibili: Focus on long-form video content and niche interests.
3. Ecommerce: The transactional tier
While Westerners often end their buying journeys on Amazon, Chinese users tend to both start and finish on the same platform, whether for variety or efficiency.
Taobao / Tmall: The prime destination for diverse product offerings.
JD.com: Favored for electronics and efficient logistics.
Pinduoduo: A leader in group-buy and value-driven purchases.
Douyin Mall: Capitalizes on impulse purchases through engaging content.
Xianyu (Goofish): Supports second-hand markets and niche hobbies.
4. Generative AI (LLMs): The reasoning tier
This emerging layer focuses on “thinking” searches where AI synthesizes data into insights rather than mere lists.
Doubao (ByteDance): Popular for casual queries.
DeepSeek (Domestic): Integrated with WeChat for deep logic queries.
Kimi (Moonshot AI): Specializes in handling lengthy documents.
Qwen (Alibaba): Plays a crucial role in business and coding tasks.
Tencent Yuanbao: Focuses on WeChat content.
Wen Xiaoyan (Baidu): Represents the next stage of Baidu’s AI search capabilities.
5. Hyper-local and logistics: The utility tier
This sector addresses immediate, location-driven demands, prioritizing services that cater to “now” and “near me” needs.
Meituan / Dianping: Leading platforms for food and leisure services.
Amap (Gaode) / Baidu Maps: Vital for navigation and local search optimization.
Ctrip (Trip.com) / Railway 12306: Key for travel and transportation booking.
From mapping to maneuvering: The Baidu specialist’s edge
Optimizing Baidu SEO extends beyond ranking web pages; it’s about mastering search landscape intricacies.
The ‘walled garden’ SERP: A decade of distraction
Focusing solely on Google-style tactics might overlook nuances like Baidu’s ad-heavy SERPs and content positions.
The ad-heavy layout: Ads can dominate substantial SERP real estate.
The Baidu monopoly: Prime organic positions often favor Baidu properties.
The portal giants: High-authority contributors also claim space within results.
Riding the Chinese SERP dragon
In this scenario, relying on long-tail strategies often proves more lucrative than targeting head keywords due to the complex Chinese language and diverse user base.
Whether leveraging platform authority or becoming a trusted contributor, it’s essential to adapt upcoming SEO tactics to sustain visibility.
What is changing in Baidu SEO?
The competition among AI models emphasizes versatility over loyalty, making Baidu SEO a nuanced challenge.
The AI-switching reality
Chinese users frequently shift between AI models, seeking superior intelligence or alternatives when certain models falter. This behavior means SEO must account for broader dynamics.
Brainstorming the wisdom platforms
Understanding the foundational platforms for AI development can greatly boost a brand’s presence in AI-dominated searches.
Tencent is invested in Sogou: Hence, Sogou Baike becomes integral for WeChat-based AI queries.
Bytedance owns Baike.com: Engaging here helps brands appear in Doubao’s results.
The neutral giants: Zhihu sits at the intersection of multiple investments, making it a balanced source for varied AI insights.
The new SEO commandment
SEO is now about optimizing for diverse data sources that fuel AI models, across various ecosystems.
In the B2B realm, Baidu remains central. Yet for ecommerce, branching into Alibaba or Doubao ecosystems will expand visibility across key AI systems.
The 2026 China SEO/GEO blueprint: From keywords to semantic saturation
Anticipating a specific SEO guide for AI like DeepSeek or Doubao misses the evolving landscape’s essence. The need is not for singular-model focus but a diversified approach that shifts with frequently changing user and model preferences.
Optimize for citations and not just clicks
Chinese SEO centers around fact density, aiming for content immediately recognizable by AI as authoritative.
The logic: AIs like Kimi and DeepSeek rank content based on factual reliability.
The tactic: Use clear, concise, data-backed writing, enabling rapid fact verification by AI.
Build an entity moat across wisdom platforms
Given that AI models distill and share intelligence, maintaining consistent brand representation across various platforms is crucial.
The goal: Ensure uniformity in brand presentation across Baidu, Sogou, and Baike.com.
The result: Consensus between AI models establishes your authority.
Leverage information gain
AI in China demonstrates a preference for recent data by about 25% compared to traditional search engines.
The tactic: Present unique, timely insights to stand out amidst common knowledge.
The era of the entity architect
We’ve moved past the initial robotic steps of 2025. In 2026, China’s search landscape is a dynamic entity, requiring an intricate understanding of intent fragmentation.
Despite the dominance of super-apps, the real revelation lies in this fractured landscape. My personal experiences echo this as my wife seeks deals on Pinduoduo, and my colleagues navigate Bing for professional resources. Meanwhile, AI enthusiasts cycle through LLMs for varied answers.
As a Baidu specialist, my role has evolved from targeting websites to designing robust entities. Building for the source, not just the bots, ensures your brand is consistently recognized and trusted, no matter which AI models deliver the solutions.
Imagine your brand becoming the celebrated go-to source, regardless of the search model. That’s the ultimate goal for today’s SEO specialists.
As someone passionate about the convergence of AI and healthcare, I’m thrilled to share monthly updates from the Goodie team. We dive into the latest breakthroughs and trends in artificial intelligence and the medical field. It’s all here, waiting for you to explore.
As someone who has been on the internet exploration journey for years, today’s news hits home. Ask.com, which many of us fondly remember as Ask Jeeves, officially closed down on May 1, 2026, after a remarkable 29 years of service. It launched on June 3, 1996, even before Google made its debut.
Upon visiting the now-closed Ask.com, we are greeted with a heartfelt farewell message that feels like a trip down memory lane:
Every great search must come to an end. As IAC continues to sharpen its focus, we have made the decision to discontinue our search business, which includes Ask.com. After 25 years of answering the world’s questions, Ask.com officially closed on May 1, 2026.
I can’t help but feel gratitude as they graciously acknowledge, “To the millions who asked…”. They expressed appreciation for the brilliant engineers and loyal users who have been a crucial part of their journey. And yes, Jeeves’ spirit indeed lives on.
For those of us who relied on this answer engine in its early days, Ask.com and the iconic Jeeves butler will always hold a special place. In a world now dominated by AI and competitive answer engines, it’s understandable why IAC, the parent company, decided to step back in such a challenging market.
Ask.com has left a significant impact on the search marketing industry, and saying goodbye is indeed bittersweet. Until we meet again in some digital form, dear Jeeves.
