What is Physical AI?
Unlike conventional AI that operates only in digital spaces, Physical AI refers to AI that directly acts and interacts in the physical world. In manufacturing, examples include robotic arms that autonomously learn optimal assembly paths, and AGVs that optimize in-factory logistics in real time.
At AW 2026 (Automation World 2026), Physical AI is a core theme, with over 500 companies participating to showcase autonomous manufacturing models.
Four Levels of Autonomous Manufacturing
Level 1: Monitoring Automation
Level 2: Decision Support
Level 3: Partial Autonomy
Level 4: Full Autonomous Manufacturing
Physical AI Adoption Strategy for SMEs
1. Build Data Infrastructure First
Physical AI's foundation is real-time data. Install IoT sensors on key equipment and establish an integrated data management platform (MES/SCADA) first.
2. Start with Pilot Processes
Automating an entire factory at once is unrealistic. Select one bottleneck process or quality-prone process, apply AI, verify results, then expand.
3. Leverage Edge AI
Cloud AI has network latency issues. For real-time manufacturing control, Edge AI (on-premise AI) is more suitable. Recent price drops in edge devices make adoption feasible for SMEs.
4. Utilize Government Support Programs
The 2026 Smart Manufacturing Innovation Program has strengthened support for AI-based smart factory advancement. Upgrading existing smart factories with AI is also supported.
Important Considerations
Contact KITIM
KITIM provides comprehensive support from smart factory strategy development to government program applications and AI solution implementation. Contact us through [KITIM Contact](/contact).