AI Ahead and the Future of Innovation | Global Investors' Symposium 2026

In this talk

1. 0:00

   Regional shocks and AI demand

   Cheng says Lenovo’s crisis committee prioritized employee safety and supply continuity after conflict began in the Middle East. The region accounts for a low single-digit share of Lenovo revenue, but its investment in AI and access to low-cost power make it a long-term opportunity. Kim says geopolitical events have not slowed Upstage; demand for AI calls is rising as companies seek efficiency.

2. 3:58

   Robots need touch, data, and integrated hardware

   David Lee describes physical AI as a combination of models, hardware, and data gathered from the real world. He says robotics depends on precise physical interaction, making manufacturing expertise and a robust data pipeline essential. Roy Lee says VITAI is developing vision-based tactile sensors to help robots judge force and friction, such as when handling an egg or a leaf.

3. 10:43

   General-purpose robots and AI readiness

   Panelists distinguish AI agents that operate computers from robots that act in the physical world, while seeing both as ways to extend AI’s capabilities. David Lee argues that one adaptable robot design could serve settings from factories to homes. Dawson says only 13% of surveyed organizations considered themselves ready to adopt AI across technology, governance, policy, and business planning.

4. 17:13

   Sovereignty, data control, and layered systems

   Cheng says Lenovo plans an agent that can connect to capable regional language models while combining public and private AI across personal and enterprise use. Kim says Upstage plans to buy about 10,000 AMD GPUs to keep data in Korea and improve token efficiency. David Lee and Roy Lee support keeping sensitive data local, with David outlining separate supplier skills, customer-specific knowledge, and broadly available knowledge.

5. 27:44

   Investment shifts from infrastructure to the edge

   Dawson sees continued technology investment despite varied short-term economic conditions, including demand driven by memory shortages. David Lee describes AI spending as a multiyear progression from training infrastructure and cloud services toward inference and devices. In closing, panelists expect more AI capability at the edge, wider access to smaller models, and continued movement from digital tools into physical robotics.