PassiveLogic Appoints Former Siemens Smart Infrastructure CTO Thomas Kiessling as CEO to Scale Autonomous Infrastructure for the Built World
Summary
PassiveLogic, a company developing an Autonomous Operating System for Commercial & Industrial infrastructure, announced the appointment of Thomas Kiessling as its new Chief Executive Officer on July 8, 2026. Kiessling, previously Chief Technology Officer of Siemens Smart Infrastructure and a clean technology entrepreneur, will lead PassiveLogic's commercial scaling and global expansion. His appointment comes as commercial and industrial buildings consume nearly 40% of global energy, with fewer than 5% operating as intelligent assets due to outdated control architectures. PassiveLogic addresses this by offering the industry's first Autonomous Platform for the Built Environment, utilizing its Quantum physics-based world model and Hive edge platform to create digital twins and apply thermodynamic AI for continuous building performance optimization. This approach significantly reduces deployment costs, enhances energy savings, and enables autonomous maintenance.
Key takeaway
For Directors of AI/ML evaluating next-generation building automation, PassiveLogic's appointment of Thomas Kiessling signals a maturing market for autonomous infrastructure. You should assess how physics-based AI platforms like theirs can democratize engineering, significantly reduce operational costs, and enhance energy efficiency across your commercial and industrial portfolios. Consider piloting autonomous operating systems to transform your buildings into self-managing, grid-interactive assets, moving beyond traditional, expensive control architectures.
Key insights
Physical AI and autonomous operating systems are emerging to transform commercial and industrial infrastructure into self-optimizing assets.
Principles
- Buildings can operate as autonomous, grid-interactive assets.
- Physics-based AI enables continuous performance optimization.
- Legacy control architectures limit intelligent asset adoption.
Method
The platform generates digital twins using a physics-based world model (Quantum) and operationalizes them via an autonomous edge platform (Hive) with thermodynamic AI.
In practice
- Achieve dramatically lower building automation deployment costs.
- Realize industry-leading energy savings and autonomous maintenance.
- Enable unprecedented grid flexibility for commercial assets.
Topics
- Autonomous Infrastructure
- Physical AI
- Building Automation
- Digital Twins
- Energy Efficiency
- Commercial Buildings
Best for: Entrepreneur, Executive, Investor, Director of AI/ML
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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI Journal.