The Centralization of Digital Services through Artificial Intelligence: A New Era of Application Interaction

The Centralization of Digital Services through Artificial Intelligence: A New Era of Application Interaction Kossi Sedjro Mawuli Dominique Houessou Computer Engineering Student, Sobral, Brazil October 2025 Abstract The way humans interact with digital applications has evolved rapidly over the past few decades. Today, most services—from banking to transportation—require navigating between multiple applications, each with its own interface and purpose. This fragmentation, while sometimes efficient, often leads to context switching and cognitive overload. With the advancement of Artificial Intelligence (AI), particularly conversational agents, a new paradigm is emerging: the centralization of digital services. This article discusses how AI may become the main gateway for accessing digital ecosystems, enabling a unified, intelligent, and personalized experience. It explores how applications could evolve into modular services invoked by intelligent systems, analyzing technical and security challenges while highlighting the transformative potential of this model. Keywords: Artificial Intelligence, Digital Transformation, Application Integration, OpenAPI, Automation, Future of Software. 1 1. Introduction The way we interact with digital applications has evolved dramatically. Currently, most digital services—such as payments, transport, or food delivery—require users to switch between multiple applications, each handling a specific function. While this model allows specialization, it also creates friction and complexity. A user who wants to transfer money must open the banking app, authenticate, and navigate through several screens. To order transportation, they must open Uber or 99, input the destination, and select a vehicle. This repetition of actions across different apps leads to cognitive fatigue and fragmented experiences. With the emergence of AI-driven interfaces, especially conversational systems, the interaction model is shifting. Users increasingly rely on intelligent agents to perform tasks on their behalf, often without explicitly opening specific applications. This paper hypothesizes that in the near future, applications will be designed to be invoked by AI systems, transforming the entire user-service relationship. 2. The Current Application Paradigm Under the current paradigm, digital ecosystems are composed of siloed applications. Each one operates independently, often duplicating user data and requiring repeated authentication. This approach, while functionally efficient, limits the integration and personalization of user experiences. According to Statista (2023), Brazilian users, on average, use more than 30 different apps monthly. The need to navigate distinct interfaces for related tasks creates friction and impedes workflow efficiency. As digital ecosystems expand, users face an increasing overload of notifications, settings, and visual environments. 2 3. The Artificial Intelligence Revolution In recent years, generative AI and conversational systems have changed how humans interact with technology. Tools such as ChatGPT, Copilot, Google Bard, and voice assistants now allow users to query, plan, and execute tasks without opening multiple apps. According to a 2025 report by AllAboutAI, AI adoption in digital services increased from 15% in 2018 to 82% in 2024 within technology sectors. McKinsey (2024) highlights that organizations integrating AI-driven workflows significantly reduced operational time and improved user satisfaction. Users are now migrating from traditional search engines (Google, Bing) toward AI-based assistants, seeking structured, contextualized, and personalized answers in a single environment. This represents not just a shift in interface—but a structural redefinition of how digital services are accessed. 4. The Centralization of Services through AI This article proposes a paradigm shift: future applications will not necessarily be accessed directly by users but invoked by intelligent systems. Instead of navigating through multiple apps, users will request tasks from an AI capable of identifying and executing the appropriate services. For example, when a user says, “Transfer $100 to John,” the AI interprets the command, selects the relevant banking API, authenticates the user, and performs the transaction automatically. Applications will evolve into modular, discoverable services—each exposing its capabilities through APIs accessible by intelligent agents. As PwC (2024) indicates, automation and AI integration are becoming central to business operations. Systems that fail to offer machine-readable interfaces risk obsolescence. Applications will need to expose structured endpoints and interfaces designed not only for humans but for AI systems to consume autonomously. 3 5. Implementation Proposal: OpenAPI and AsyncAPI Standards To ensure that digital applications can be seamlessly invoked by AI agents, adopting open documentation standards such as OpenAPI and AsyncAPI is crucial. OpenAPI is a widely used specification that defines RESTful APIs in a machineand human-readable format. It allows intelligent agents—or any external system—to discover available operations, required parameters, and expected responses. For instance, a payment service using OpenAPI can clearly expose its “transfer” operation, authentication method, and data schema, enabling AI systems to interact with it autonomously. AsyncAPI, in turn, extends this concept to event-driven architectures, supporting asynchronous communication via queues or message brokers. This enables real-time interaction between intelligent systems and distributed services. By adopting these standards, developers ensure interoperability, scalability, and automation readiness. According to the OpenAPI Initiative (2025), documenting APIs in open, standardized ways accelerates innovation and facilitates secure, autonomous integration by intelligent systems. 6. Security Considerations in API Documentation Using OpenAPI or similar standards does not mean that an API becomes publicly accessible. Security depends on backend implementation and proper authentication mechanisms. To protect data and transactions, authentication schemes such as OAuth2, JWT, or API Keys must be defined directly in the OpenAPI specification. This way, the documentation clearly states which endpoints require authentication and how agents should obtain authorization. Furthermore, encrypted communication, rate limiting, and access monitoring remain essential. OpenAPI serves as a descriptive layer, while true protection lies in secure implementation. Swagger.io (2025) emphasizes that security definitions in the specification ensure that only au4 thorized agents can access sensitive endpoints. 7. Challenges and Opportunities Centralizing services through AI brings significant challenges—technical, ethical, and social. Data privacy, interoperability, and legacy system adaptation remain critical barriers. According to PwC (2024), 67% of companies identify security as a major challenge in AI adoption, followed by privacy (61%) and interoperability (53%). Yet, this shift also creates new opportunities: integrated user experiences, reduced cognitive load, and emerging markets for “AI-oriented APIs.” Developers and organizations must balance automation efficiency with transparency and ethical governance. In this new landscape, success depends not only on technology but also on trust. 8. Conclusion Artificial Intelligence is redefining how users access and interact with digital services. By envisioning a future where applications are designed to be invoked by intelligent systems, this article highlights a path toward centralized, fluid, and intelligent user experiences. While still in development, this paradigm signals a transformative direction for digital ecosystems. Systems that fail to adapt to AI-driven orchestration risk obsolescence, while those that embrace open standards and intelligent integration will define the next era of software design. References [1] ALLABOUTAI. Global AI Adoption Report 2025: Is Your Country on the List? Available at: https://www.allaboutai.com/pt-br/recursos/estatisticas-de-ia/ adocao-global-de-ia/. Accessed: October 7, 2025. 5 [2] STATISTA. Average number of mobile apps used monthly in Brazil in 2023. Available at: https://www.statista.com/statistics/1107934/average-number-apps-used-monthly-brazil/. Accessed: October 7, 2025. [3] MCKINSEY. AI adoption and business impact. Available at: https://www.mckinsey. com/featured-insights/artificial-intelligence. Accessed: October 7, 2025. [4] PWC. AI predictions and challenges. Available at: https://www.pwc.com/gx/ en/issues/data-and-analytics/artificial-intelligence/ai-analysis. html. Accessed: October 7, 2025. [5] OPENAPI INITIATIVE. About OpenAPI Specification. Available at: https://www. openapis.org/. Accessed: October 7, 2025. [6] SWAGGER.IO. Authentication and Authorization in the OpenAPI Specification. Available at: https://swagger.io/docs/specification/authentication/. Accessed: October 7, 2025. 6