AI taking over, touching many sectors at CES in Las Vegas

Editor’s note: “Behind the News” is the product of Sun staff assisted by the Sun’s AI lab, which includes a variety of tools such as Anthropic’s Claude, Perplexity AI, Google Gemini and ChatGPT.

 

The Consumer Electronics Show in Las Vegas drew hundreds of thousands from the tech industry this week to preview the year ahead in consumer technology.

What attendees saw was a fundamental shift: AI has turned CES from a hardware show into a software‑and‑systems show, where “intelligence” is now the main feature.

Devices learn, adapt and act on a user’s behalf instead of just responding to taps and clicks. That transformation is reshaping what products look like (more screens, sensors and assistants) and how they feel to use (more conversational, predictive and personalized).

How AI is changing tech ‘look and feel’

Devices are designed around AI first, with prominent “assistant” buttons, mic arrays, cameras and dedicated AI chips so products can run models on‑device instead of in the cloud. This makes laptops, phones, TVs, cars and home devices feel like collaborators rather than tools, because they can run complex AI tasks locally and respond faster with more privacy.

Consumer tech now highlights features like “learns your behavior,” “anticipates needs” and “acts for you” as core selling points. At recent CES events, smart homes, vehicles and wearables are marketed less by raw specs and more by how their AI can understand context, moods and routines.

Interfaces are becoming more conversational and multimodal: voice, natural language and camera inputs sit alongside classic apps and menus. In gaming and entertainment, AI is used to generate adaptive environments and personalized experiences, which makes products feel more alive and reactive.

Automation of routine tech work

In software development, AI coding assistants and copilots generate boilerplate code, write tests and suggest fixes, cutting time to develop features and improving code quality. Many organizations now plug these tools into CI/CD pipelines so repetitive work like unit‑test generation, documentation drafts and refactoring passes is partially automated.

In IT operations, AI systems monitor logs, traffic and performance metrics to detect anomalies, predict outages and auto‑remediate common incidents. This moves teams away from manual ticket triage toward supervising AI‑driven runbooks and focusing on higher‑level reliability engineering.

Cybersecurity teams are using AI to filter huge volumes of alerts, detect patterns indicative of attacks, and surface high‑priority threats in real time. At the same time, attackers are also adopting AI for phishing, malware generation and vulnerability discovery, which forces defenders to adopt “AI versus AI” strategies.

Personalization and data‑driven experiences

Customer experience and marketing are seeing deep personalization: Recommendation engines, “next best action” models and predictive churn analytics tailor what each user sees, when and on which channel. Companies using these AI systems report higher lifetime value and reduced churn because offers and content match user intent much more closely.

In consumer electronics, smart home hubs, TVs and wearables now learn individual preferences for content, lighting, temperature and routines, then proactively adjust environments. Cars are integrating AI for driver monitoring, adaptive interfaces and predictive maintenance, changing vehicles from static products into evolving software platforms.

Across sectors, AI‑powered analytics turns large operational and customer data sets into dashboards and recommendations that executives actually act on. This shrinks experimentation cycles in areas like product design, R&D and supply chain, enabling faster decisions and more frequent iteration.

Shifting human roles: From doing to directing

AI is moving work up the value chain: Humans increasingly specify goals, constraints and guardrails, while AI handles many execution steps. Developers, analysts and operators spend more time on architecture, strategy, prompt design and validation rather than manual coding or data wrangling.​

In knowledge work, AI tools summarize information, draft communications and generate reports, so people can focus on negotiation, creative framing and complex decision‑making. For scientists and engineers, AI acts as a lab or design assistant, proposing hypotheses, simulations or design variations that humans then evaluate.

Rather than straightforward replacement, most organizations are adopting “collaborative intelligence” models where AI augments frontline workers, from customer support agents with suggested responses to field technicians with predictive diagnostics. This model requires new skills around oversight, critical thinking and understanding AI limitations, not just traditional technical expertise.

New challenges and risks

Security and privacy risks are intensifying as models ingest sensitive data and can be attacked via prompt injection, data poisoning or model theft. Organizations are responding with stricter data controls, model isolation and continuous monitoring for AI‑specific threats.

Workforce impact is uneven: Repetitive tasks shrink, new AI‑related roles expand and many existing jobs are being rescoped around AI tools rather than eliminated outright. This makes reskilling, change management and clear communication central to AI strategy across industries.

Hype remains a factor, especially at high‑profile events, but many companies are shifting from experimentation to measured deployment focused on ROI and tangible workflows. That means fewer flashy demos over time and more integrated AI capabilities inside everyday products and enterprise systems.

Sources

https://www.linkedin.com/pulse/ai-transformation-2026-26-predictions-redefining-cx-ex-saltz-gulko-twspf

https://www.fullstack.com/labs/resources/blog/2025-ces-ai-innovations-recap-consumer-trends-in-ai

https://geniusee.com/single-blog/ai-trends-in-2026

https://finance.yahoo.com/news/what-to-expect-from-ces-2025-techs-biggest-show-goes-all-in-on-ai-142424278.html

https://news.microsoft.com/source/features/ai/whats-next-in-ai-7-trends-to-watch-in-2026/

https://www.forbes.com/sites/charliefink/2025/01/10/ces-2025-a-year-of-ai-hype-and-quiet-evolution/

https://www.ibm.com/think/news/ai-tech-trends-predictions-2026

https://quantilus.com/article/ai-innovations-take-center-stage-at-ces-2025/

https://www.deloitte.com/us/en/insights/topics/technology-management/tech-trends.html

https://www.ces.tech/videos/how-ai-is-changing-consumer-behavior/