Managing AI in the enterprise : succeeding with AI projects and MLops to build sustainable AI organizations / Klaus Haller.
Haller, Klaus, author.
2022
HF5548.2 .H35 2022eb
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Managing AI in the enterprise : succeeding with AI projects and MLops to build sustainable AI organizations / Klaus Haller.
Author Haller, Klaus, author.
ISBN 9781484278246 (electronic bk.)
1484278240 (electronic bk.)
1484278232
9781484278239
DOI https://doi.org/10.1007/978-1-4842-7824-6
Imprint [United States] : Apress, 2022.
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-1-4842-7824-6 doi
Call Number HF5548.2 .H35 2022eb
Dewey Decimal Classification 658.0563
Summary Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists. For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization. What You Will Learn Clarify the benefits of your AI initiatives and sell them to senior managers Scope and manage AI projects in your organization Set up quality assurance and testing for AI models and their integration in complex software solutions Shape and manage an AI delivery organization, thereby mastering ML Ops Understand and formulate requirements for the underlying data management infrastructure Handle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects Who This Book Is For Experienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organization's AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams.
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Available in Other Form Print version: 9781484278239
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1. Why Organizations Invest in AI
2. Structuring and Delivering AI Projects
3. Quality Assurance in and for AI
4. Ethics, Regulations, and Explainability
5. Building an AI Delivery Organization
6. AI & Data Management Architectures
7. Securing & Protecting AI Environments
8. Looking Forward.

Browse Subjects

Show more subjects...

Statistics

from
to
Export