CES 2026: AI Steps Out of Screens and Into the Physical World
January has long functioned as a kind of “direction-setting moment” for the global technology ecosystem. CES, for this reason, is not merely a consumer electronics show; it is a signal field that reveals which problems the industry will focus on over the next 12–24 months, which product categories are reaching maturity, and which technologies are moving beyond demos to become commercial realities.
January has long functioned as a kind of “direction-setting moment” for the global technology ecosystem. CES, for this reason, is not merely a consumer electronics show; it is a signal field that reveals which problems the industry will focus on over the next 12–24 months, which product categories are reaching maturity, and which technologies are moving beyond demos to become commercial realities.
CES 2026 (January 6–9, Las Vegas) left me with one dominant impression: AI is no longer confined to screens—it has entered the physical world. In other words, AI is now embedded in systems that perceive, decide, and act: physical or embodied AI.
This shift is not driven solely by “better models.” It is enabled by more efficient hardware capable of running at the edge, declining sensor costs, mature connectivity and device management infrastructure, and enterprise customers nearing the threshold from experimentation to deployment. The sheer scale of CES makes this transition visible: with over 4,500 exhibitors, 140,000+ visitors, and nearly 1,400 startups—especially within Eureka Park—the event has become less a product showcase and more a global innovation distribution platform.
The broader narrative of CES 2026 was perhaps best summarized by two short but powerful statements from NVIDIA CEO Jensen Huang on the CES stage. “Every 10–15 years, the computer industry resets with a new platform transition,” he said—emphasizing that what we are experiencing is not incremental feature evolution, but a platform-level shift. His follow-up captured the essence of AI’s impact on product development: “You no longer program software; you train it.”
When applied across the CES 2026 landscape, these ideas point to a clear conclusion: AI’s value is no longer defined by being a “smart feature” inside an application, but by becoming the operating system of products themselves—systems that perceive their environment, interpret context, and take action safely.
From an investment perspective, the most critical implication of this shift is that physical AI significantly extends the value chain. Growth is no longer limited to the model layer; it now spans compute, connectivity, device management, security, energy efficiency, and field service operations. NVIDIA’s platform announcements and ecosystem messaging during CES reinforced this view—particularly its emphasis on scale, trust, and physical AI models for robotics and autonomy—strengthening the market narrative that the next major AI inflection point will unfold in the physical world.
Looking at the startups that stood out to me at CES 2026, a common pattern emerges: the most compelling companies were not those with the flashiest demos, but those capable of turning AI into deployable, manageable, and scalable products.
Take Sixfab’s ALPON X5 AI device, for example. It addresses one of the biggest real-world challenges of edge AI—not inference alone, but connectivity continuity, remote device management (OTA), and operational sustainability. By combining Raspberry Pi Compute Module 5 with DEEPX NPU–based on-device analytics, Sixfab packages edge AI in a form that is truly enterprise-ready. Its recognition as Best of Innovation in the CES Innovation Awards (Enterprise Tech category) is no coincidence. From a VC lens, the real value here is not just selling hardware, but standardizing field operations, the most painful part of edge AI deployment. That standardization meaningfully lowers the enterprise adoption threshold.
In digital health, another notable shift is the move from measurement to intervention. VHEX Lab’s SITh. XRaedosolution explores new interaction paradigms in grief therapy through therapist-controlled avatars in XR environments and was recognized in Digital Health Innovation Awards listings. These are not investments driven by demos alone; they demand rigorous clinical validation, ethical frameworks, data security, regulatory compliance, and seamless integration into therapist workflows. Yet when executed correctly, such solutions unlock scalable access to care—opening a meaningful market opportunity firmly on the VC radar.
One of CES 2026’s quieter but more powerful messages was the repositioning of accessibility—from a niche category to a core market narrative. Naqi Logix’s “neural earbuds,” highlighted as Best of Innovation, point toward a new input layer: micro-gestures and biosignals enabling control in environments where screens or manual interaction are impractical. The investment thesis here goes beyond hardware; it lies in the potential to create a platform-level interaction standard. With the right SDKs, partnerships, and real-world adoption in verticals such as elderly care, assistive technologies, and field operations, value can quickly migrate toward software and services.
In robotics, we are seeing the return of the once-dismissed “companion robot” concept—this time on far more mature technical foundations. Products like Ollobot’s OlloNi, featured among CES’s notable robotics examples, reflect advances in contextual understanding, sensor fusion, and on-device inference. While B2C hardware risks remain high, the key investment metric here is still clear: retention. If these products can evolve from novelty to genuine assistance—particularly in verticals like eldercare—the business models begin to open new doors.
Another striking observation from CES 2026 is that the AI narrative is increasingly driven by infrastructure, not just end-user products. Developments around companies like Groq reaffirm that inference efficiency itself is a standalone value domain. This inevitably leads to energy and data center realities: as AI scales, compute demand rises—and with it, energy and infrastructure constraints. By 2026, it is nearly impossible to discuss AI growth without simultaneously addressing energy efficiency.
From a Boğaziçi Ventures perspective, this landscape presents highly actionable opportunities for Turkey and the surrounding region. As the global model layer becomes increasingly crowded, real value concentrates in deployment-centric layers: edge-first architectures, integration, security, device management, regulatory compliance, and vertical expertise. Boğaziçi Ventures’ focus on applied AI aligns closely with this reality.
This also forces a redefinition of what an “AI startup” means. By 2026, it often translates to AI + hardware/edge + services/operations + integration. Accordingly, the questions investors and founders must ask together are evolving: not only How good is the model?, but How resilient is the product in the field? How easy is deployment? What are the maintenance costs? How strong is privacy and regulatory compliance? And how realistic is the PoC → pilot → contract conversion cycle?
My personal takeaway from CES 2026 returns to Jensen Huang’s “reset” framing. The reset button may have been pressed—but the winners will not be those who can merely talk about AI. They will be those who can make AI work. In 2026–2027, the strongest opportunities will not lie in eye-catching demos, but in products that deliver measurable efficiency, are deployable, and can scale. For the VC ecosystem, this represents both an opportunity and a call for discipline: maintaining excitement while asking tougher questions about unit economics, distribution, and operational sustainability.
