## 2 Literature Review
### Relevant Norms and Standards in Affersales and Warranty Management  
In order to effectively implement advanced technologies in warranty management, it is essential to follow international standards that govern both the use of artificial intelligence (AI) and asset management. These standards ensure security, transparency, and quality in processes, facilitating an ethical and reliable application of new systems. Among the most prominent standards in this area are the standards represented in Figures 2-10, developed by us, the ISO standard/IEC42001 (AI Systems Management) [25], ISO 55000 (Asset Management) [3], and ISO 9001 (Quality Management) [4], which play a key role in regulating and optimizing warranty management. ISO/IEC 42001 establishes guidelines for the management of AI systems in organizations that use this technology in critical operations, such as failure prediction and warranty optimization [25]. Its objective is to ensure that AI systems operate in an ethical, transparent and secure manner, minimizing risks associated with automated decisions and protecting data privacy. This standard emphasizes three essential aspects:  
* Ethics and Transparency: ISO/IEC 42001 highlights the importance of implementing unbiased AI in automated decision-making. This includes managing data in compliance with privacy regulations, ensuring it is handled fairly and ethically--a vital aspect in customizing assurance services. * Safety and Reliability: In critical applications, such as predictive maintenance, the standard states that AI systems must be highly reliable and accurate to avoid unforeseen failures. Accurate failure prediction is critical to optimizing asset life cycles and reducing warranty claims. * Continuous Evaluation: AI systems must undergo regular evaluations to ensure their alignment with continuous improvement principles. This involves constantly monitoring algorithms and adapting their parameters based on the latest data. A practical example can be seen in [26], which adopted the ISO/IEC 42001 standard for its Railigent platform, using AI for predictive maintenance in trains. This system allows monitoring the status of assets in real time, anticipating the right time for maintenance interventions and improving operational efficiency by complying with the transparency and security principles of the standard. Another example is seen in [3; 4], where AI is employed in a customer relationship management (CRM) system using IoT sensors in vehicles. Thissystem allows BMW to personalize warranty management, ensuring that automated decisions about aftersales services remain within the ethical and safety standards of ISO/IEC 42001. ISO 55000 and ISO 9001 are essential standards for ensuring efficiency and reliability in asset management and the quality of warranty service. Both standards allow organizations to optimally manage the life cycle of assets and offer high-quality service in warranty resolution and aftersales support. ISO 55000 establishes a global framework for asset management throughout the life cycle. This approach encourages preventive and predictive maintenance, minimizing risks and optimizing operating costs. In warranty management, ISO 55000 allows decisions to be made based on the actual performance of assets, maximizing their useful life and reducing claims. An example of its application in the industrial sector can be seen in [27], which applies ISO 55000 together with predictive maintenance platforms to adjust warranty policies. Through real-time analysis and the use of historical data, GE maximizes the performance of its turbines and reduces downtime [28]. This use of ISO 55000 ensures that warranty decisions are based on accurate data, optimizing resources and increasing customer satisfaction [29; 30]. ISO 9001, on the other hand, is the international standard for quality management. In the context of warranty management, it ensures that all processes related to aftersales services maintain high quality standards.