Textbook in PDF format Study a structured maturity model that guides organizations from foundational steps to advanced, responsible AI practice Learn from best practices and examples that make complex concepts accessible and actionable Master best practices in data management, security and risk monitoring to protect sensitive data and secure AI systems Written from the perspective of an experienced IT expert, this book leverages a maturity model framework to guide organizations through each stage of adopting, securing, scaling, and tracking the value of low-code AI responsibly and efficiently. Unlike other works that focus only on AI’s technical aspects, this book boasts a practical roadmap for responsible AI adoption and provides a clear, structured maturity model that guides organizations from foundational steps to advanced, responsible AI practices. In a world where organizations are under pressure to innovate quickly and responsibly, this book provides a structured approach, addressing essential elements such as data management, governance, ethics and compliance in low-code AI environments. Each chapter represents a maturity level, from foundational to optimized, offering readers insights, practical steps and examples to support their journey. The Low-Code AI Maturity Model takes a comprehensive look into the transformative potential of low-code and AI. What You Will Learn Identify, assess and mitigate risks to ensure stable and reliable AI deployments Implement robust governance, aligning with compliance standards and ethical principles at each maturity stage Evaluate the real business value and ROI of AI projects, empowering data-driven decision-making Who This Book Is For IT leaders, decision-makers, and technology enthusiasts interested in the transformative potential of low-code and AI