Decision-Quality AI

Implement trusted AI systems that deliver measurable business value while managing risk, compliance and long-term performance.

Decision-Quality AI by Eva-Marie Muller-Stuler is a practical guide for data, product and technology leaders responsible for turning AI ambition into real-world outcomes. Covering the complete AI lifecycle from strategy and team design to deployment and governance, it provides the frameworks and technical foundations needed to develop AI products that are effective, responsible and aligned with business goals.

Designed for leaders implementing AI at scale, this book helps you move beyond experimentation and hype to build AI solutions that solve genuine business challenges while meeting regulatory and operational requirements.

You will learn how to:
- Define AI use cases that address real business needs
- Build teams, processes and governance for AI delivery
- Develop, test and deploy AI with confidence
- Manage risk, compliance, security and transparency
- Monitor performance throughout the AI lifecycle

Decision-Quality AI combines responsible AI principles with the practical disciplines required for successful implementation. It explores areas such as MLOps, ModelOps, AIOps, DevSecOps and cybersecurity, giving you a complete framework for delivering AI that creates lasting impact. Whether you are launching your first AI initiative or scaling enterprise-wide adoption, this book provides the tools, processes, and leadership guidance you need to build trusted AI systems that deliver results.

Themes include: AI development, AI governance, AI security, MLOps, ModelOps, risk management, DevSecOps, data architecture, AI strategy