iKala Explores Agentic Commerce, Highlighting GEO and Localized AI Benchmarks
Frontier AI models · AI assistants · Enterprise AI
iKala leadership points out that shifting consumer entry points toward AI agents enables Agentic Commerce. Businesses face Generative Engine Optimization (GEO) needs and local language evaluation through TMMLU+.
iKala Co-founder and Chairman Sega Cheng, alongside AI Marketing Director Chiao-Tung Hsu, stated that AI agents are transitioning from providing answers to executing tasks, altering consumer discovery and transaction pathways toward Agentic Commerce. Cheng noted that competition is expanding from traditional SEO to Generative Engine Optimization (GEO), requiring brands to manage how AI systems describe and cite them. iKala detailed its marketing toolchain for sentiment analysis and citation tracking, stressed leadership adoption for internal transformation, and highlighted its ongoing work on the open-source Traditional Chinese benchmark TMMLU+.
Key takeaways
- Sega Cheng noted that as AI agents evolve from answering queries to executing tasks, commerce is shifting toward direct purchasing and autonomous transactions.
- Facing AI recommendation mechanics, marketing competition expands from SEO to GEO, requiring brands to monitor citation contexts within AI models.
- iKala stated that its marketing services integrate tools including Ontix, Kuroma, and Kolr to support workflows from diagnosis to tracking.
- To evaluate model comprehension of Taiwanese cultural context and language, iKala maintains and updates the open-source TMMLU+ benchmark.
Source：數位時代 Read the original ↗
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