AI · Qualitative in-depth interview study using open and axial coding, literature triangulation, and a researcher focus-group card sort.
Ready or Not, AI Comes- An Interview Study of Organizational AI Readiness Factors
Business & Information Systems Engineering · 2021
Summary
Five readiness categories were identified-strategic alignment, resources, knowledge, culture, and data-with 18 factors and 58 illustrative indicators; readiness is purpose- and context-specific and should be assessed continuously.
For your marketing
Possible founder application
Use the five categories as a pre-sales or implementation-readiness checklist: align the AI use case to strategy, budget data and skills, build an adoption culture, and define measurable readiness gates.
Reported result
What the study found
Five readiness categories were identified-strategic alignment, resources, knowledge, culture, and data-with 18 factors and 58 illustrative indicators; readiness is purpose- and context-specific and should be assessed continuously.
Research question
What the authors investigated
What factors and actionable indicators constitute organizational readiness for adopting AI?
Design
Qualitative in-depth interview study using open and axial coding, literature triangulation, and a researcher focus-group card sort.
Sample and setting
25 purposively selected AI experts across different adoption stages, industries, organizational sizes, and user/provider contexts.
Scope and transfer
Limitations to keep in view
The evidence is qualitative and based on expert informants rather than a probability sample of adopting firms; the authors present it as an initial conceptualization and note the need for further validation.
Research sources
Fetched Springer publisher page establishes title, authors, journal, DOI, abstract, 25-expert interview design, categories, and indicators; page identifies the article as CC BY/open access. Firecrawl research job 01a1436c-f86b-77df-af1c-9a2f87e3535e returned this citation and metadata.