CES 2026 Day 2 Signals AI’s Shift From Platforms to Physical Systems

Day 2 at CES 2026 in Las Vegas shifted the show’s center of gravity from chip road maps and platform talk to hardware that bakes AI into the object itself, forcing models to operate within physical constraints such as form factor, power, latency, and human interaction.

CES runs from 6-9 January and has drawn more than 4,100 exhibitors, according to the Consumer Technology Association.

What stood out on Day 2 was also a pattern across categories: AI is increasingly being designed as a native system property, not a feature layered onto finished products.

On Device AI Reshapes Hardware Design

Several companies used CES to show how AI is beginning to influence the physical design of computing devices themselves. Lenovo showcased multiple concept systems that rethink the personal computer around adaptive interfaces, including laptops with flexible or motorized displays designed to respond dynamically to context and workload.

The strategic signal is less about form factor novelty and more about control. As more inference and personalization move on device, hardware is being built to accommodate AI-mediated interaction rather than fixed inputs and static screens. This has implications for enterprise computing, where end-user devices may increasingly adapt to workflows instead of forcing standardized interfaces.

The shift also redistributes decision-making across organizations, pulling AI capability closer to hardware, operating systems, and product teams rather than central cloud or data groups.

A similar logic underpinned Motorola’s expansion beyond clamshell foldables into book-style devices. Larger, flexible displays are being positioned as enablers for AI-driven multitasking, content generation, and real-time assistance, reflecting how AI workloads are reshaping expectations of mobile hardware.

Embodied AI Moves Closer to Deployment

Robotics demonstrations on Day 2 emphasized progress toward usable, task-oriented systems rather than research prototypes. Multiple exhibitors framed embodied AI as an execution challenge, focusing on balance, dexterity, navigation, and coordination in unstructured environments.

Humanoid platforms from companies such as EngineAI were positioned as general-purpose systems capable of operating in industrial and logistics settings, highlighting coordinated motion, manipulation, and autonomy. Meanwhile, firms including MagicLab showcased multi-robot configurations that stressed collaboration and sequencing rather than isolated demonstrations.

A related signal came from companies pushing intelligence deeper into constrained systems. Lego’s Smart Bricks, built around a custom low-power chip with integrated sensing and wireless charging, illustrated how computation and control are increasingly being embedded into objects where cloud dependence is impractical, reinforcing a broader shift toward edge-first system design.

Even consumer-facing robotics hinted at deeper technical progress. A stair-climbing vacuum concept from Roborock illustrated how advances in perception, mapping, and control are being pushed into constrained physical spaces, a longstanding bottleneck for autonomous systems.

Industrial AI and Digital Twins Gain Visibility

Beyond devices and robots, CES Day 2 also highlighted the growing role of AI in industrial engineering and simulation-heavy environments. A collaboration involving Siemens and Nvidia, alongside Commonwealth Fusion Systems, showcased how AI-enabled digital twins are being used to accelerate the design and iteration of complex physical systems.

The use of machine learning to augment physics-based simulation reflects a broader enterprise shift. AI is increasingly applied not to replace engineering judgment, but to shorten design cycles, reduce testing costs, and manage systems that cannot be exhaustively validated in the physical world.

Taken together, Day 2 reinforced a quieter but more consequential message. AI is moving out of the platform layer and into products, machines, and infrastructure, where it must operate under physical and organizational constraints.