Context is All You Need

Discover how context drives AI personalization and the future of digital identity management.

Paper reviewed:

Esber, Jad and Thielen-Esparza, Sean and Fu, Yondon and He, Tina, Context is All You Need (May 27, 2025). Available at SSRN: https://ssrn.com/abstract=5277474 or http://dx.doi.org/10.2139/ssrn.5277474

Summary

This research paper reveals the significance of context in AI personalization, introducing the concept of 'half-life of context' and exploring the emergence of personal context servers. It highlights the importance of integrating diverse context sources and the potential shift towards distributed, horizontally-integrated approaches.

Key Findings

• The value of context in AI personalization lies in its ability to create a deeper understanding of users, going beyond mere data collection to integrate discrete information into meaningful patterns.
• The "half-life of context" concept suggests that recent context is more valuable than historical context, creating a premium on platforms that can maintain real-time understanding of a user's evolving context.
• Different interfaces and form factors generate unique types of context, and combining diverse context sources improves the richness of a user's digital portrait.
• The emergence of personal context servers, such as those using the Model Context Protocol (MCP), enables individuals to control and port their digital identities across services.
• The future of context aggregation may involve distributed, horizontally-integrated approaches, rather than relying on centralized, vertically-integrated models.

Implications

Business and Policy Implications

• Businesses should prioritize designing interfaces that encourage natural context generation and earn the right to gather context from users.
• Companies must balance the need for personalization with user agency and privacy concerns, potentially through the use of emerging standards like MCP.
• Policymakers should continue to enact and enforce regulations that promote context portability and interoperability, such as the EU's Digital Markets Act.
• The development of new interfaces and technologies will require businesses to adapt their strategies for context aggregation and utilization.

Introduction

The emerging landscape of AI assistants and agents is transforming how we interact with technology, with context becoming the most valuable currency. As AI systems become more perceptive and responsive, the question arises: who will win the race to aggregate as much context as possible, and will individuals control their digital identities or will they be locked in corporate walled gardens? This paper explores the emerging models for context aggregation and portability, the evolving interfaces through which context is generated and applied, and how aligning business incentives and user agency is essential for genuine value creation.

Background and Context

The early internet era focused on data collection, optimizing engagement, and monetizing through ads. However, today's AI-driven landscape has reframed the challenge, shifting from data collection to sharing context—a flexible, semantic understanding of the user. The rise of AI assistants and agents has created new opportunities for personalization, but also raises concerns about context control, portability, and monetization. As the industry moves forward, understanding the evolution of context, the role of different interfaces, and the emerging models for context aggregation will be crucial for businesses, policymakers, and individuals alike.

The concept of context has evolved significantly over time. Initially, context was primarily about capturing user behavior, such as clicks and scrolls, to infer intent and preferences. However, with advancements in AI and the proliferation of various interfaces, context has become more nuanced. Today, context encompasses not just user behavior but also environmental cues, device state, and intent. This richer understanding of context enables more sophisticated personalization and user experiences.

Different interfaces generate unique types of context. For instance, text-based interfaces reveal how users express problems and desires in their own words, while visual interfaces capture attention patterns and aesthetic preferences. Spatial interfaces, such as AR/VR, reveal physical interaction tendencies. The diversity of interfaces creates complementary dimensions of understanding but also raises questions about trust and who should have access to this context.

The "half-life of context" is another critical concept in understanding the value and management of context. It emphasizes that recent context often carries more value than historical context. This concept has significant implications for how businesses and AI systems prioritize and manage context. It suggests that maintaining a real-time understanding of a user's evolving context is crucial for delivering relevant and personalized experiences.

The emergence of personal context servers represents a significant shift in how context is managed and controlled. These servers, potentially utilizing standards like the Model Context Protocol (MCP), allow individuals to maintain control over their digital identities and selectively share context with services they authorize. This development has the potential to redefine the relationship between users, businesses, and AI systems, enabling more personalized experiences while respecting user privacy and agency.

As we move forward, the landscape of context aggregation and utilization will continue to evolve. The tension between centralized, vertically-integrated models and distributed, horizontally-integrated approaches will shape the future of AI personalization. Businesses, policymakers, and individuals will need to navigate these changes, balancing the benefits of personalization with the need for privacy, security, and user control.

The future of context is not just about technological advancements but also about creating systems that enhance human agency. By understanding and addressing the complexities of context, we can unlock new possibilities for AI-driven personalization that benefits both individuals and businesses. As the industry continues to evolve, it is clear that context will play a central role in shaping the next generation of computing, and those who earn the right to gather it, respect the responsibility of handling it, and create tangible value from it will be the ones to shape this future.

Main Results

The paper "Context is All You Need" presents several key findings that shed light on the emerging landscape of AI-driven personalization. The main results can be summarized as follows:

The Evolution of Context

The concept of context has evolved significantly, from simple data collection to a deeper understanding of user behavior and preferences. Advanced AI models and interfaces have enabled the creation of "digital twins" that can provide personalized experiences.

The Importance of Context Aggregation

Context aggregation is crucial for delivering breakthrough personalization. The paper highlights the need for platforms to earn the right to gather context and for users to have control over their digital identities.

Diverse Context Sources

Different interfaces and form factors generate unique types of context, each offering different windows into user needs and preferences. The richness of a user's digital portrait improves as diverse context sources are combined.

The Half-Life of Context

The "half-life of context" concept emphasizes that recent context often carries significantly more value than historical context. This creates a premium on platforms that can maintain real-time understanding of a user's evolving context.

Key Findings and Statistics

• The paper identifies several key domains where specialized "memory fabrics" are emerging, including media consumption, coding, design, health tracking, and learning/education.
• Different interface modalities afford different types of context generation, each with unique strengths.
• The most comprehensive understanding of a user will come from integrating context across multiple modalities.

Examples and Implications

The paper provides several examples of how context is being used in different domains, such as:

• A therapy app revealing emotional patterns and inner struggles.
• A coding tool demonstrating problem-solving approaches and technical capabilities.
• A calendar interface revealing time management styles and prioritization patterns.

These examples illustrate the potential for context to create a more nuanced understanding of users and provide personalized experiences.

Methodology Insights

The research approach used in the paper involved a limited-time working group held over three sessions in May 2025. The methodology is important because it brought together experts from various fields to discuss the emerging models for context aggregation and portability.

The paper's focus on practical experiments and implementations, such as the personal MCP (Model Context Protocol) server, provides valuable insights into the technical challenges and opportunities associated with context aggregation and portability.

Analysis and Interpretation

The findings presented in the paper have significant implications for businesses, policymakers, and individuals. The analysis reveals that context is becoming a critical component of AI-driven personalization, and that companies that earn the right to gather context and respect user agency will be well-positioned for success.

The paper identifies four key shifts that are enabling context portability:

1. Regulatory momentum, with laws like the Digital Markets Act and CCPA mandating data portability.
2. Market dynamics, with new applications and services creating demand for context portability.
3. New interfaces driving adoption, such as personal media tracking services and AI agents.
4. Technological infrastructure, with advances in privacy-preserving technologies and shared standards.

These shifts are creating a complex landscape where users, businesses, and regulators must navigate the benefits and challenges of context aggregation and portability.

The analysis also highlights the need for a balanced approach to context integration, respecting user preferences for context compartmentalization, depth, customizability, and visibility. As the industry continues to evolve, it is clear that context will play a central role in shaping the next generation of computing.

Practical Implications

The findings of this research have significant implications for businesses, managers, and individuals. The ability to aggregate and utilize context effectively will be a key differentiator in the AI-driven landscape. Companies that can harness context to deliver personalized experiences will be better positioned to capture market share and drive user engagement.

Real-World Applications

The research highlights several real-world applications of context aggregation and portability, including:

• Personalized AI assistants that can anticipate user needs and take autonomous action
• Specialized services that can leverage context to deliver tailored experiences, such as media consumption, coding, and health tracking
• New interface modalities, such as ambient interfaces, conversational interfaces, and functional interfaces, that can capture different types of context

Strategic Implications

The research suggests that businesses and managers should prioritize context aggregation and portability as a key strategic objective. This will require investments in:

• Developing robust context infrastructure, including personal context servers and standards for context sharing
• Creating interfaces that are designed for natural context generation and user agency
• Building trust with users through transparent data handling practices and robust security measures

Who Should Care

The findings of this research are relevant to a wide range of stakeholders, including:

• Business leaders and managers seeking to leverage context to drive personalization and user engagement
• AI and technology developers looking to create context-aware systems and interfaces
• Regulators and policymakers seeking to balance the benefits and challenges of context aggregation and portability
• Individuals concerned about data privacy and agency in the AI-driven landscape

Actionable Recommendations

To capitalize on the opportunities presented by context aggregation and portability, businesses and managers can take the following actions:

1. Develop a context strategy: Identify key areas where context can drive value and develop a plan to aggregate and utilize context effectively.
2. Invest in context infrastructure: Develop or adopt technologies that enable robust context aggregation, storage, and sharing, such as personal context servers and standards for context sharing.
3. Design interfaces for context generation: Create interfaces that are designed to capture context naturally, such as conversational interfaces and ambient interfaces.
4. Prioritize user agency and trust: Develop transparent data handling practices and robust security measures to build trust with users and respect their agency.
5. Monitor regulatory developments: Stay informed about evolving regulations and standards related to context aggregation and portability.

Implementation Considerations

When implementing context aggregation and portability strategies, businesses and managers should consider the following:

• Balance context integration with user preferences: Respect user preferences for context compartmentalization, depth, customizability, and visibility.
• Address technical challenges: Develop solutions to technical challenges, such as secure encrypted storage, reliable synchronization, and user authentication.
• Foster a culture of transparency and trust: Develop transparent data handling practices and communicate clearly with users about context usage and benefits.

Conclusion

The research presented in this paper highlights the critical role that context will play in shaping the next generation of computing. As the industry continues to evolve, businesses, managers, and individuals must navigate the benefits and challenges of context aggregation and portability.

By developing robust context infrastructure, designing interfaces for context generation, and prioritizing user agency and trust, businesses can capitalize on the opportunities presented by context. As the landscape continues to shift, it is clear that context will be a key differentiator in the AI-driven world.

The path forward will require a balanced approach that respects user preferences, addresses technical challenges, and fosters a culture of transparency and trust. By working together, we can create a future where context is harnessed to enhance human agency and drive meaningful value for all stakeholders.