Executive Summary

At CES 2026, Samsung Electronics convened global experts to address the critical question of trust in artificial intelligence through their “In Tech We Trust?” panel. This case study examines Samsung’s trust-by-design approach, analyzes the industry outlook, and evaluates specific implications for Singapore’s AI ecosystem.

Case Overview

Event: Samsung Tech Forum at CES 2026
Date: January 6, 2026
Location: The Wynn, Las Vegas
Focus: Trust, security, and privacy in the AI age

Key Participants

• Shin Baik, Group Head, AI Platform Center, Samsung
• Allie K. Miller, CEO, Open Machine
• Amy Webb, CEO, Future Today Strategy Group
• Zack Kass, Global AI Advisor, ZKAI Advisory (former Head of Go-To-Market at OpenAI)
• Richard Edelman, CEO, Edelman

The Trust Challenge

As AI systems become increasingly autonomous and invisible—anticipating needs, curating routines, and operating across multiple devices—the panel identified trust as the defining factor in AI adoption. The core challenge: how do companies earn trust when the intelligence powering user experiences operates behind the scenes?

Samsung’s Strategic Response

1. Trust-by-Design Architecture

Samsung outlined three foundational principles:

Predictability: AI systems that behave consistently and understandably
Transparency: Clear visibility into AI operations and data usage
User Control: Empowering users to make informed decisions about their AI interactions

2. Technical Implementation

On-Device AI: Personal data remains local whenever possible, processing sensitive information directly on user devices without cloud transmission.

Selective Cloud Intelligence: Cloud-based processing deployed only when speed or computational scale requires it, giving users flexibility without sacrificing privacy.

Knox Security Platform: Over a decade of development protecting billions of devices from the chipset level upward.

Knox Matrix: A cross-device security framework where products authenticate and protect one another, creating a “shield network” across the user’s ecosystem.

3. Partnership Strategy

Samsung highlighted collaborations with Google and Microsoft to strengthen shared security research, improve interoperability, and establish ecosystem-wide protection standards.

Expert Insights & Industry Perspectives

The Transparency Imperative

Allie Miller emphasized that users want to be “leaders in their own personalized experiences,” requiring clarity on whether AI models run locally or in the cloud, assurance that data is secure, and explicit labels distinguishing AI-powered features from traditional functionality.

The Convenience Paradox

Amy Webb introduced a critical challenge to the trust narrative: consumers don’t necessarily purchase based on trust alone. “People aren’t paying for trust. They don’t buy things because of trust. They buy things because of convenience,” she noted. This suggests that AI adoption will be driven primarily by utility, with trust acting as a hygiene factor rather than a primary motivator.

Technology as Countermeasure

Zack Kass acknowledged the legitimate concerns around misinformation and misuse but maintained an optimistic stance: “For every risk, there is also a countermeasure and technology itself will play a critical role in mitigating AI’s downsides.”

Industry Outlook

Short-Term Trends (2026-2027)

Regulatory Acceleration: Expect increased government scrutiny and framework development around AI transparency and data protection, particularly in developed markets.

Security as Differentiator: As AI capabilities commoditize, security architecture and privacy features will become key competitive advantages.

Hybrid Intelligence Models: The on-device/cloud hybrid approach will become industry standard, balancing privacy with computational power.

Medium-Term Evolution (2028-2030)

Cross-Device Orchestration: AI will increasingly operate across entire device ecosystems, making Samsung’s Knox Matrix approach—where devices protect each other—more relevant.

Explainable AI Requirements: Both regulatory pressure and consumer demand will push companies toward AI systems that can clearly explain their decision-making processes.

Trust Metrics: Development of standardized trust scores and certifications for AI systems, similar to energy efficiency ratings.

Long-Term Transformation (2030+)

Invisible AI Norm: AI will be so deeply embedded that its presence becomes assumed rather than highlighted, making foundational trust even more critical.

Decentralized Trust Models: Blockchain and distributed ledger technologies may enable new verification mechanisms for AI authenticity and data integrity.

Ethical AI Standards: Industry-wide consensus on ethical AI principles will mature into enforceable standards and certification processes.

Impact on Singapore

Strategic Alignment with National Priorities

Singapore’s position as a Smart Nation and AI innovation hub makes the Samsung trust framework particularly relevant:

AI Singapore Initiative: The government’s AI strategy emphasizes responsible and ethical AI development, aligning with Samsung’s trust-by-design principles.

Personal Data Protection Act (PDPA): Singapore’s robust data protection framework creates a conducive environment for privacy-focused AI solutions like Samsung’s on-device processing approach.

Digital Trust Framework: Singapore’s ongoing work to establish digital trust standards meshes well with industry efforts to build transparent, accountable AI systems.

Economic Opportunities

Regional Innovation Hub: Singapore can position itself as Southeast Asia’s center for trusted AI development, attracting companies prioritizing security and privacy.

Samsung’s Regional Presence: As a major technology employer and R&D center in Singapore, Samsung’s trust initiatives could generate local high-skill jobs in AI security and ethics.

Smart Nation Deployment: Singapore’s extensive smart city infrastructure provides an ideal testbed for cross-device AI security frameworks like Knox Matrix.

Consumer Market Dynamics

High Digital Literacy: Singapore’s tech-savvy population is more likely to appreciate and demand the transparency features Samsung emphasizes.

Privacy Consciousness: Growing awareness of data rights among Singapore consumers aligns with market demand for privacy-preserving AI solutions.

Premium Market Positioning: Singapore’s affluent consumer base may be willing to pay premium prices for AI products that demonstrably prioritize security and trust.

Regulatory and Policy Implications

Model Governance Framework: Singapore could develop Asia’s leading AI governance standards based on principles discussed in Samsung’s forum, influencing regional policy.

Public Sector Adoption: Government agencies seeking to deploy AI across services will require exactly the kind of transparent, secure systems Samsung describes.

Cross-Border Data Flows: As ASEAN works toward harmonized digital economy agreements, Singapore’s expertise in balancing innovation with trust becomes increasingly valuable.

Challenges for Singapore

Talent Competition: Meeting demand for AI security specialists will require expanded education programs and talent attraction strategies.

SME Adaptation: Smaller Singapore companies may struggle to implement enterprise-level security frameworks, requiring government support programs.

Balancing Innovation and Control: Excessive regulatory caution could slow Singapore’s AI adoption, while insufficient oversight could undermine trust.

Recommendations for Singapore Stakeholders

For Government:

• Fast-track AI governance frameworks that incentivize trust-by-design approaches
• Invest in AI security research centers and talent development programs
• Create sandbox environments for testing cross-device AI security systems

For Businesses:

• Prioritize transparency and user control in AI product development
• Invest in local processing capabilities to minimize data export
• Participate in industry consortiums developing trust standards

For Consumers:

• Demand clarity on how personal data is used in AI systems
• Support companies demonstrating commitment to transparency and security
• Engage with public consultations on AI governance

Conclusion

Samsung’s CES 2026 panel reveals that the AI industry is entering a critical phase where trust, not just capability, determines market success. The company’s emphasis on on-device processing, cross-device security, and user transparency represents a pragmatic response to growing privacy concerns.

For Singapore, this shift presents substantial opportunities. The nation’s strong regulatory framework, digital infrastructure, and innovation ecosystem position it to become a regional leader in trusted AI development and deployment. However, success requires coordinated action across government, industry, and civil society to balance innovation with accountability.

Amy Webb’s observation that convenience ultimately drives adoption suggests that the winning formula combines Samsung’s trust architecture with seamless user experiences. For Singapore, the challenge and opportunity lie in demonstrating that security and convenience need not be trade-offs—that the most trustworthy AI can also be the most useful.

As AI becomes increasingly invisible, the companies and nations that establish trust as a foundation—rather than an afterthought—will lead the next phase of technological transformation.