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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
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
One of his most significant contributions has been to Microsoft’s Center of Excellence (CoE) Starter Kit and the Business Value Toolkit—resources that have empowered organizations globally to deploy, manage, and drive value from low-code and AI solutions. As a recognized expert in low-code AI, he has a deep understanding of the practical and strategic elements required for successful adoption, from technical implementation to cultural alignment.
Part 1: Leadership and Culture.- Chapter 1: Foundational: Leadership and Culture.- Chapter 2: Emerging: Leadership and Culture.- Chapter 3: Operationalized: Leadership and culture.- Chapter 4: Integrated Excellence: Leadership and Culture.- Part 2: Establishing Trust and Governance.- Chapter 5: Foundational: EstablishingTrust and Governance.- Chapter 6: Emerging: Establishing Trust and Governance.- Chapter 7: Operationalized: Establishing Trust and Governance.- Chapter 8: Integrated Excellence:Establishing Trust and Governance.- Part 3: Data Readiness and Security.- Chapter 9: Foundational: Data Readiness and Security.- Chapter 10: Emerging: Data Readiness and Security- Chapter 11: Data Readiness and Security: Operationalized Stage.- Chapter 12: Data Readiness and Security: Integrated Excellence Stage.- Chapter 13: The Journey Forward: Leadership in the Age of Low-Code AI.
| Erscheinungsjahr: | 2025 |
|---|---|
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xxx
594 S. 150 s/w Illustr. 6 farbige Illustr. 594 p. 156 illus. 6 illus. in color. |
| ISBN-13: | 9798868817298 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Jeffery, Steve |
| Auflage: | First Edition |
| Hersteller: |
Apress
Apress L.P. |
| Verantwortliche Person für die EU: | APress in Springer Science + Business Media, Heidelberger Platz 3, D-14197 Berlin, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 34 mm |
| Von/Mit: | Steve Jeffery |
| Erscheinungsdatum: | 27.09.2025 |
| Gewicht: | 0,931 kg |
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