With the rapid advancement of generative artificial intelligence, a new era of AI-driven marketing has arrived. The shift from SEO (Search Engine Optimization) "keyword rankings" to "natural language conversations" is fundamentally altering how brands connect with users. This transformation not only reshapes traffic entry points but also redefines brand recognition and trust systems. In this context, GEO (Generative Engine Optimization) has emerged as a critical capability for businesses to build core competitiveness in the AI search era.
On November 7, the "AI-Driven Marketing Paradigm—GEO White Paper Release and Forum on Brand Competitiveness in the AI Search Era," co-hosted by the CEIBS AI and Marketing Innovation Lab, Xsignal, and the CEIBS-TeZign AI and Business Innovation Research Fund, was successfully held. The CEIBS AI and Marketing Innovation Lab, a key research platform in AI and marketing at CEIBS, collaborated with Xsignal to release the "AI Search Era: A New Brand Blueprint from GEO to AIBE | GEO White Paper | 2026" (hereinafter referred to as the "GEO White Paper"). The white paper systematically presents the latest market trends, technological pathways, and corporate case studies in the GEO era. The forum brought together academic experts, industry leaders, and cutting-edge technologists to explore the new paradigm of "AI × Marketing × Brand" and help businesses seize cognitive high ground and build long-term competitiveness in the AI search era.
Zhu Tian, Associate Dean and Chinese Director of CEIBS, Professor of Economics, and Santander Chair in Economics, delivered opening remarks. He noted that AI technology is disrupting traditional information acquisition methods, as generative AI allows users to bypass traditional search portals and directly access integrated answers. This shift fundamentally changes the logic of brand exposure and reach. He emphasized that the GEO White Paper, a product of deep collaboration between academia and industry, addresses core challenges in brand-building posed by the AI search era and provides a forward-looking theoretical framework and practical guide for businesses. He expressed hope that the white paper would serve as a beacon for enterprises navigating this transformation.
Dou Dejing, Distinguished Professor at Fudan University's School of Computing and Intelligence, Chief Scientist at Beidian Digital Intelligence, Adjunct Professor at Tsinghua University's Department of Electronic Engineering, and recipient of the National Leading Talent Program, delivered a keynote speech titled "Breakthroughs and Industrial Applications of Large AI Models." He explained the core breakthrough of the Transformer architecture—self-attention mechanisms—which effectively address contextual understanding challenges in natural language processing. He also clarified the concept of "parameters," noting they refer to the number of connection weights between neurons in neural networks.
Based on an analysis of the human brain, Dou predicted that a 10-trillion-parameter model could achieve 10% of human brain capacity, making the pursuit of 100-trillion-parameter models uneconomical. He praised the breakthrough contributions of the domestic model DeepSeek, which achieved performance comparable to GPT-4 with fewer parameters and computing power, calling it "the greatest contribution by Chinese researchers in AI's 70-year development."
Wang Qi, Professor of Marketing at CEIBS, Director of the Marketing Department, Research Director of the CEIBS AI and Marketing Innovation Lab, and Executive Committee Chair of the CEIBS-TeZign AI and Business Innovation Research Fund, co-released the GEO White Paper with Liu Zhen (EMBA 2019), Founder and CEO of Xsignal. Wang Qi highlighted the white paper's core findings, explaining that as monthly active users of large AI models in China approach 500 million and exceed 1.27 billion globally, user information acquisition methods are undergoing a fundamental shift. GEO, unlike traditional SEO, focuses on whether brand content can be understood and recommended by AI models, reshaping user decision-making paths and necessitating new metrics for AI-era brand equity (AIBE).
Liu Zhen elaborated on the "CREATE" methodology for GEO, which includes competitive environment monitoring, user demand analysis, AI response parsing, source management, content feature analysis, and execution. He noted that traditional media is regaining value in the GEO era, as authoritative and professional platforms become preferred sources for AI citations. Liu emphasized that GEO is a new discipline requiring fresh standards and systems, and businesses should start with monitoring to build competitive advantages in the AI world.
Two panel discussions followed. The first, moderated by Lu Yi, Assistant Professor of Marketing at CEIBS, explored "How GEO Can Become a Growth Engine for Brands." Panelists highlighted the differences between GEO and SEO, stressing the need for brands to feed AI models high-quality content. In an era of content overload, visibility requires strategies that are "AI-friendly, AI-trusted, and AI-citable." The second panel, moderated by Chen Zhuo, Assistant Professor of Strategy at CEIBS, discussed "Business Reconstruction and the Future in the AI Era." Panelists noted that AI is elevating business logic from technical tools to ecosystem symbiosis, with competitiveness shifting from resource stockpiling to dynamic operational capabilities.
The forum concluded with remarks on the need for businesses to balance innovation with sustainability and actively shape their roles in the new AI ecosystem. The CEIBS AI and Marketing Innovation Lab, which focuses on AI-driven user insights, marketing content generation, and brand management, aims to foster cross-sector collaboration and practical solutions for digital transformation in marketing.