iKala Explores AI Commercial Shifts: From Generative Engine Optimization to Agentic Commerce

As generative AI intervenes in search, comparison, and consumer decision-making, channels between brands and consumers are shifting. Sega Cheng, co-founder and chairman of iKala, notes that AI agents are evolving from providing answers to executing tasks, potentially selecting products and completing transactions directly to advance agentic commerce. In this environment, marketing priorities are expanding from traditional search ranking toward Generative Engine Optimization (GEO), requiring companies to manage how AI indexes, describes, and cites their information. Chiao-Tung Hsu, Director of AI Marketing at iKala, observes that enterprises must monitor brand visibility and citation contexts across AI platforms in addition to tracking consumer signals. Cheng also highlights corporate internal adoption challenges, noting that leadership unfamiliarity with AI often prevents transformation initiatives from addressing core pain points, and recommends incremental validation starting with key scenarios. Furthermore, to address localized understanding, iKala supports the open-source TMMLU+ benchmark to evaluate model performance on Traditional Chinese and Taiwan-specific knowledge.

Key takeaways

• AI agents are gradually acquiring task execution capabilities, driving consumer journeys toward agentic commerce models.
• Brand competition is expanding from SEO into GEO, emphasizing how AI cites and recommends corporate information.
• Internal corporate AI adoption hurdles frequently stem from leaders lacking hands-on experience, favoring an incremental validation approach.
• The open-source TMMLU+ benchmark is used to evaluate model comprehension of Traditional Chinese and regional context.