Samsung Electronics: How Trust is Shaping the Future of AI

As AI becomes more and more embedded in daily routines, from smartphones to home appliances, the question of trust is moving to the centre of public conversation.

Samsung Electronics' panel during CES 2026 in Las Vegas, In Tech We Trust? Rethinking Security & Privacy in the AI Age, brought together technology, ethics and research leaders to unpack how trust impacts AI adoption and long-term engagement.

The session featured:

• Allie K Miller, CEO of Open Machine
• Amy Webb, CEO of the Future Today Strategy Group
• Zack Kass, Global AI Advisor at ZKAI Advisory and former Head of Go-To-Market at OpenAI
• Shin Baik, Group Head of Samsung’s AI Platform Centre

Making AI visible and understandable

AI increasingly works behind the scenes – anticipating needs, automating routines and operating across devices. In this context, the panel agreed that trust must be established through clear, consistent and user-facing design.

Allie outlined how clarity drives confidence: “When it comes to AI, users are looking for transparency and control. They want to be leaders in their own personalised experiences – to understand whether an AI model is running locally or in the cloud, to know their data is secure and to clearly see what is powered by AI and what is not. That level of visibility builds confidence.

"On the provider side, there is a responsibility to show up for users by designing personalised experiences around the core components of trust – clarity, security and accountability.”

Samsung used the session to outline its “trust-by-design” approach, focusing on transparency and user control. Its model relies on AI that is predictable, easy to understand and adaptable to user preferences. On-device AI plays a key role in this, keeping personal data local where possible and only leaning on cloud-based systems when faster processing or broader scale is required.

This hybrid setup gives users a balance between performance and privacy, allowing them to benefit from AI without surrendering control over their data.

Security for a connected AI world

As intelligence becomes is embedded in phones, televisions and household devices, traditional models of digital security must evolve.

Samsung positions its Knox security platform as a foundation for this shift. Built into its devices from the chipset up, Knox is designed to protect sensitive data across every layer.

Shin noted: “Trust in AI starts with security that’s proven, not promised. For more than a decade, Samsung Knox has provided a deeply embedded security platform designed to protect sensitive data at every layer.

"But trust goes beyond a single device – it requires an ecosystem that protects itself. With Knox, devices continuously authenticate and monitor one another, so each device acts as a shield for the rest, creating a resilient, secure environment users can rely on."

Knox Matrix – Samsung’s cross-device framework – builds on this idea. The system allows devices to check and validate each other, creating a network where each device helps safeguard the entire ecosystem.

This mutual authentication reduces the risk of a single point of failure and adds a visible layer of ongoing security, which is key for user trust.

Why trust is not just about security

Beyond encryption and authentication, the panel explored how trust in AI ties into ethical design, transparency and user control.

According to Shin, users must be able to observe AI behaviour and make informed choices. This means moving away from so-called “black box” systems – AI models whose decisions and processes are hidden – and offering clear signals that explain what the technology is doing and why.

Samsung highlighted industry partnerships with companies like Google and Microsoft as examples of collective work on interoperability, shared security protocols and system-wide protection. These alliances aim to deliver security at device level as well as the ecosystem level.

Allie continued to stress the value of transparency – both in data usage and in making it obvious where and how AI models operate. This includes the need for explicit labelling to identify what is AI-powered and what is not, making the invisible parts of AI more visible to users.

Zack acknowledged the risks of misinformation and misuse that can come with AI, but added: "For every risk, there is also a countermeasure and technology itself will play a critical role in mitigating AI’s downsides."

Meanwhile, Amy offered a pragmatic view by linking trust with user behaviour: “I don’t think they’re making decisions based on trust alone. People aren’t paying for trust. They don’t buy things because of trust. They buy things because of convenience. So, if the AI piece of this hooks people in, it makes their lives easier and more convenient."

The panel agreed that long-term trust is likely to be built by embedding transparency, accountability and clear user choice into every product from the outset.