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Images and ideals of organization design have changed dramatically in the past decade in response to the need for a redirection in the purpose and strategy as well as leadership styles following the global economy, new brave networked world, emerging new forms of organizing, and social innovations. This chapter is an invitation to explore a new genre of organization design and organizing as if life matters. It is a call to embrace organizations designed to affirm, nurture, and sustain life. The chapter discusses two key questions: “What Gives Life to Human Organizing” and “What Are We Designing.” The first part aims to uncover what gives life to human organizing through an exploration of nine principles of appreciative organizing. The second part aims to expand what we mean when we talk about organization design through an examination of six fundamental structures that seem to be at play in organized action.

Appreciative Inquiry has clearly made a significant impact on the field of organization development and change. This article presents an assessment of 50 studies based on a review of more than 400 publications and papers. The article covers four sections: first, an overview of the growing significance of AI since the initial Cooperrider and Srivastva article in 1987, with a brief summary of the history, definition, awards, and chronological presentation of the growing body of AI literature. The second section presents a description of the data search process and descriptions of data categories. The third section describes the nature and extent of AI activities and results based on the review of the 50 studies. The final section includes a summary and discussion of the current state of Appreciative Inquiry.

The purpose of this paper is to contribute with knowledge concerning how to drive, generate and energize change and development in social systems. A potential key to meet this challenge is the strength-based change management approach called appreciative inquiry (AI). A central component of AI is the “AI interview”, which has evolved into a distinct activity that enables the past and the future to be used as a generative source for on-going learning about strengths, opportunities, aspirations and results. The AI interview has in previous studies shown an often surprisingly high ability to generate development and change in social systems. However, the understanding of the generative “mystery” of the AI interview, focusing on the value experienced by both the people conducting the interview and those being interviewed, is still in need of further exploration. Furthermore, the evident generativity of the AI interview has not yet been integrated to any large extent into quality management. The purpose of this paper is to change that.

The researchers have studied the customer experience of conducting an AI interview based on feedback from 97 AI students at Mid Sweden University.

Among the results, eight categories of value are identified.

The paper contributes with new knowledge concerning the values experienced during participation in an AI interview. The paper also highlights ideas on how the generativity of the AI interview could be increasingly integrated into quality management.

The purpose of this study is to identify how at‐risk high school students in an alternative school describe how they best learn and to extrapolate their preferred learning practices to improve teacher pedagogical practices.

The authors used a qualitative case study design to facilitate the first two stages of an appreciative inquiry (AI) 4‐D cycle – discovery and dream. Eight alternative high school students, four males and four females, were purposively selected as participants. Data collection methods included: group discussions, semi‐structured paired interviews, and participant generated documents and visual presentation for district administrators and teachers. Data were analyzed using content analysis, open coding, axial coding, text analysis software, and pattern matching.

The study produced four salient findings: relevant experiences were important for learning; a cooperative and respectful learning environment is a core value; learning should be enjoyable; and, the concept of family became an important metaphor for the learning environment.

The findings from this study suggest that further research with AI in educational settings may have important implications to inspire educators to think in new ways about learning.