The era of AI marketing has arrived: Why must companies establish their own AI customer acquisition and brand awareness systems?

The era of AI marketing has arrived: Why must companies establish their own AI customer acquisition and brand awareness systems? Over the past decade or so, companies conducting online marketing usually focus on several core actions: Build an official website, do SEO, run advertisements, manage a WeChat public account, create short videos, operate social media, and then wait for potential customers to find you on their own. But today, the way companies access information is changing. More and more users are starting to ask questions directly to ChatGPT, Gemini, DeepSeek, Doubao, Tongyi Qianwen, and other generative AIs: "Which industrial AI companies in Shenzhen are worth collaborating with?" "How should manufacturing enterprises deploy an enterprise knowledge base?" "How can foreign trade companies use AI to improve inquiry conversion rates?" "How should small and medium-sized manufacturing enterprises start AI digitization?" "Which enterprise AI solution companies can provide on-premises deployment?" In the past, users might have needed to open a search engine and look for answers on dozens of web pages one by one. Now, AI may directly provide users with an organized, compared, and summarized answer. This means that business marketing is undergoing a very important change: The competition among enterprises is no longer just about 'whose website ranks higher,' but about 'who can more easily become an information source understood, cited, and recommended by AI.'

1. Traditional SEO is still important, but it is no longer the entirety of digital marketing for businesses.

This does not mean that SEO is outdated. Google's currently published official guidelines clearly state that AI search still relies on search indexes, crawling, relevance, and website quality, and traditional SEO remains an important foundation for generative AI search. (Google for Developers) Therefore, what businesses truly need in the future is not: SEO or GEO. Rather: SEO GEO content marketing brand authority third-party sources. SEO addresses: After users search, can they find you? GEO solves: After users directly ask AI, is it possible for AI to understand, reference, and recommend you? Content marketing addresses: Why do users trust you? Brands and third-party information sources address: Why does AI think you deserve to be recommended? These four parts will eventually form a new digital marketing infrastructure for the enterprise.

2. The biggest change in AI marketing is not 'AI helping companies write articles'

Many companies' understanding of AI marketing still stays at: "Let AI generate ten articles every day." This is a big misunderstanding. If a large number of articles merely repeat information that already exists on the internet, then such content is unlikely to form real corporate competitiveness. Google's latest AI search guidelines clearly emphasize that businesses should create original, valuable, non-duplicated, user-centered content, rather than mass-producing low-value pages aimed at search algorithms. (Google for Developers) Truly valuable AI marketing should accomplish four things: First, establish the company's own knowledge assets Including: • Company capability • • Product Information • • Technical Specifications • • Industry knowledge • • Customer issue • • Solution • • Project Experience • • FAQ • • Product Comparison • • Implementation method • • Cost Analysis • • Selection Guide • This content should ultimately form the company's own 'digital knowledge assets'. Second, let this knowledge be searchable A corporate website cannot be just a 'company brochure.' It should gradually become: Corporate public knowledge base. For example, manufacturing companies can continuously release: How do manufacturing companies deploy AI knowledge bases? "Why do industrial enterprises need on-premises AI?" How to choose GPU memory for an AI server? "How should industrial vision edge AI choose computing power?" "How do manufacturing companies use AI to automatically process quotations?" This content not only serves customers but also establishes the company's information entities in AI search systems. Third, Enable AI to Understand Enterprises AI needs to know: Who are you? What are you doing? Serve whom? In which industries do you have capabilities? What products are there? What technical skills do you have? Solve what problem? What is the difference from competing proposals? The clearer the corporate website, the more consistent the third-party content, and the more complete the brand entity, the easier it is for AI to establish a stable corporate profile. Fourth, turn AI traffic into real customers This is the ultimate goal. A company cannot remain at: "AI recommended us." But should form: AI discovery → Official website visit → AI assistant consultation → Lead capture → Sales follow-up → CRM → Deal closed.

3. Why do B2B companies especially need AI marketing?

One of the biggest differences between B2B marketing and consumer goods marketing is that the customer decision-making cycle is long. A corporate client purchase: AI servers, industrial network devices, enterprise knowledge bases, digital employees, industrial AI Box, Usually, people don't buy something immediately just by looking at an advertisement image. Customers will keep searching: What is the product? What scenarios is it suitable for? What brands are there? What is the price? Is deployment difficult? What hardware is needed? Does it support privatization? Are there any cases? What advantages does it have compared to other options? Therefore, B2B companies are naturally suited for 'knowledge-based marketing'. Generative AI is precisely turning the Internet into a huge 'answer system'. Those who possess more high-quality, credible, and well-structured professional knowledge are more likely to become part of the answer.

4. What exactly should GEO do?

GEO is not simply about adding a few keywords in an article. A true GEO should include five levels.

1. Brand Entity

First, let AI accurately understand: Company Name English Name Product Industry Region Capability. For example: Jilianxin (Shenzhen) Technology Co., Ltd. Intellisiontech Enterprise AI Solutions Trade Enterprise AI AI for Manufacturing Enterprises AI Knowledge Base AI Agent AI Automation AI server Edge AI Industrial network These concepts need to form a stable association on the official website, articles, and third-party platforms.

2. Question-Type Content

Don't just write: "Enterprise AI Solutions." Should write: "How do manufacturing companies choose AI servers?" "How can trading companies use AI to improve inquiry conversion rates?" "Should the corporate knowledge base be deployed on the cloud or on-premises?" "What is the difference between an AI Agent and RPA?" Because the questions that users pose to AI are themselves problem-type language.

3. Professional Evidence

The article cannot just say: "AI can improve efficiency." Should explain: Improve what efficiency? Through what technology? What kind of businesses is it suitable for? What data is needed? Where is it deployed? Are there any restrictions? In what situations should it not be used? The more specific, the easier it is to create truly professional content.

4. Third-party sources

GEO cannot rely solely on the company's own website. Research from 2025–2026 increasingly focuses on AI systems' reliance on third-party authoritative sources, as well as the significantly different patterns of information adoption across different AI platforms. (arXiv) Therefore, enterprises should gradually form: Official website Zhihu Toutiao Baijiahao WeChat Official Account LinkedIn Facebook YouTube Industry media Industry directory Third-party case. Form consistent brand messaging from multiple sources.

5. AI Citation Monitoring

In the end, we can't only look at: Baidu ranking. Should also be tested regularly: ChatGPT: "Recommended Chinese enterprise AI solution company." DeepSeek: "Which AI service providers are there in Shenzhen?" Steamed Bun: Recommendations for AI knowledge base companies for manufacturing enterprises. Gemini: Enterprise AI solution providers in China. Then record: Is there a brand? Is it accurate? Is the description correct? Are there any competitors? Which websites were cited? Is there any error message? This is the real AI brand monitoring.

5. Enterprise AI marketing should truly form a closed loop

Future corporate digital marketing can form: Content assets ↓ Official Website/GEO ↓ Search and AI Discovery ↓ AI Recommendation ↓ Official website access ↓ AI Agent Reception ↓ Lead enters CRM ↓ Sales Follow-up ↓ Transaction completed ↓ Customer Case ↓ Form content again Finally formed: Content → Traffic → AI Cognition → Clues → Customers → Cases → Content This is the marketing flywheel that truly has long-term value in the AI era.

6. For trading and manufacturing enterprises, where should one start?

It is not recommended for enterprises to build a 'big and comprehensive' AI platform from the start. A more reasonable approach is to start with a high-value scenario. Trading enterprise Can start from: AI Official Website GEO Product Knowledge Base AI Inquiry Assistant Start. Solution: • Product Information Organization • • Multilingual content • • Customer Question Response • • Inquiry Classification • • Customer Information Organization • • Sales Support • Manufacturing enterprise Can start from: Enterprise Knowledge Base AI Assistant Start. Bring: Product information, technical documents, SOPs, FAQs, maintenance materials, sales materials, training materials, Gradually settle into the company's own AI knowledge assets. Add later: Capabilities such as AI Agent, RPA, digital employees, privatized AI, AI servers, and Edge AI.

7. The real core of AI marketing is not 'using AI to write content'

Rather: Make the enterprise itself a source of knowledge that AI can understand, verify, and recommend. This is also one of the most important changes in future business marketing. For businesses, what truly needs to be built is not hundreds of isolated articles, but a system that can continuously accumulate: Enterprise digital knowledge assets, brand information source system, AI customer acquisition system. Jilianxin (Shenzhen) Technology Co., Ltd. / Intellisiontech currently focuses on trade and manufacturing enterprises, providing AI upgrade paths for companies from solution design to technical products and implementation delivery, centered around GEO website growth, enterprise knowledge bases, AI agents and business automation, enterprise AI computing power, Edge AI, and industrial networks. AI marketing is not something that will only happen in the future. It has already begun to change the way customers 'discover businesses, understand businesses, compare businesses, and choose businesses.' For businesses, the real question is no longer: “Should I do AI marketing?” Rather: "When my clients start asking questions to AI, will the AI know who I am?"