"AI+Business Evolution Theory" Forum Held in Shanghai, Launching the Era of 'Intelligent Efficiency' with GEA

China Europe International Business School and Tezign held an AI forum in Shanghai, releasing the AI Business Evolution Blueprint white paper and launching the GEA enterprise-level intelligent agent, promoting companies from human efficiency to intelligent efficiency, having served over a hundred enterprises.

On April 10, the "AI+Business Evolution Theory: System·Closed Loop·Intelligent Efficiency" forum was held at the China Europe International Business School Shanghai campus, co-hosted by the school and Tezign Technology. Experts from academia and industry gathered to discuss new paths for AI-driven high-quality development of enterprises.

The white paper "Business Evolution Blueprint in the AI Era (2026)" was released on-site, systematically proposing a 3×3 strategic matrix that clearly outlines the upgrade path for enterprises from localized AI experiments to systematic "intelligent efficiency," identifying 2026 as a critical turning point for enterprise AI applications, providing an authoritative judgment framework and practical guidelines for the industry.

The forum focused on the core transformation from "human efficiency" to "intelligent efficiency." Experts unanimously agreed that AI is transitioning from an auxiliary tool to a business foundation, with future competitive barriers lying in data assets, industry experience, and system capabilities. Tezign shared practical experiences of the GEA enterprise-level intelligent agent system on-site, supporting the implementation of the white paper's concepts with a complete business closed loop, helping enterprises achieve replicable and scalable operational value.

During the forum, Tezign Technology founder Fan Ling proposed a new concept of "Intelligent Agent Business" and provided an in-depth interpretation of Tezign GEA (Generative Enterprise Agent). This system is designed specifically for real business scenarios, constructing a complete closed loop of "intention layer - orchestration layer - intelligent agent skill layer - context layer," enabling AI to deeply understand business, make autonomous decisions, and execute in a closed loop, achieving full-process intelligent operation from market insights, product innovation to operational optimization.

Leveraging the GEA enterprise-level intelligent agent, Tezign has served over 180 enterprises globally, widely applied in core scenarios such as product innovation, content growth, and user operations, upgrading AI from a mere "cost reduction and efficiency enhancement tool" to a business foundation capable of meeting KPIs, closing loops, and being replicable.

It is reported that Tezign has maintained steady and rapid growth in recent years, achieving record high growth rates, with year-on-year doubling growth, and annual recurring revenue (ARR) nearing $100 million, serving over 180 enterprises worldwide, covering more than 50 countries and over a million professional users, confirming the maturity and market recognition of the enterprise-level intelligent agent technology route.

Wang Hong, Dean of the China Europe International Business School, stated that the core of future enterprise competition is "intelligent efficiency," and only by achieving a value closed loop through intelligent agent systems can true competitive barriers be built. The white paper emphasizes that enterprise AI competition is no longer a simple technical contest, but a comprehensive strength competition of private data, industry experience, and intelligent agent systems.

Guests from companies such as Anker Innovations, Schneider Electric, Bosch, and Semir shared frontline practical experiences, engaging in in-depth dialogues around AI organizational transformation, scenario implementation, and data governance, with pragmatic viewpoints and vivid cases, providing reference paths for enterprise AI transformation.

(Source: Shangguan News Author: Xinmin Evening News Zhang Jiongqiang)

Category

Media & Press

Date

2026-04-23

Read Time

2 min read

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