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31 I L T A N E T . O R G TECHNICAL REQUIREMENTS FOR DIFFERENT FIRM SIZES Scalability and efficient resource utilization are critical factors. Smaller firms may benefit from adopting cloud-based solutions and software-as- a-service (SaaS) models, which minimize the need for substantial upfront investments in technology. Conversely, larger firms might opt for customized systems utilizing microservices architectures and containerization technologies such as Docker and Kubernetes to manage complex workloads. Resource optimization strategies include leveraging serverless computing for cost-effective scaling and utilizing performance monitoring tools to ensure efficient resource usage. INTEGRATION WITH EXISTING LEGAL TECH STACK Ensuring compatibility with current systems minimizes disruption. Standardizing APIs helps with integration, allowing different software components to communicate effectively. Following industry standards and protocols enhances compatibility and protects the technology investment for the future. Data migration and transformation need careful planning. Implementing solid extract, transform, load (ETL) processes ensures data preservation as it transitions to new systems. Thorough testing and validation are necessary to maintain data integrity and keep operations running smoothly. CONCLUSION Integrating AI into modern legal practice offers excellent opportunities to improve efficiency, accuracy, and innovation. By embracing these advancements, legal professionals can provide better services, make more informed decisions, and stay competitive. However, it's crucial to address the technical challenges, ethical considerations, and professional responsibilities that come with these technologies. A well-planned and strategic approach to implementation will help the legal industry successfully navigate these new changes, ultimately benefiting both practitioners and clients. ILTA IMAN BADRI holds a bachelor's degree in software engineering and two specialized master's degrees in in- formation technology, focusing on AI system development, and innovation. His 20-year career spans various global industries like technology, finance, oil and gas, hospitality, and legal. Dedicated to bridging the gap between theoretical concepts and their practical applications, Iman consistently solves real-world problems by transforming complex concepts into tangible solutions. Iman shares his expertise in data science and AI through articles, book chapters, and presentations, aiming to con- tribute to the broader conversation within the professional community. FEATURES

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