Research Methodology & Respondent Profile

Quick Glance: Who Took the Survey

The survey included 820 respondents sourced from a leading global online panel provider. They were selected from the panel based on geographic and role-based quotas, as well as screening questions based on role in IT, decision-making role, company size, and familiarity with DevOps practices. Participants were IT decision-makers and purchase influencers with the ability to accurately understand DevOps, platform engineering, and the role of AI. Selected respondents were further screened based on self-reported DevOps knowledge and attentiveness to survey questions.

Who Took the Survey?

Roles: All respondents were required to indicate that they were responsible for or had influence in evaluating and/or selecting enterprise IT solutions, including infrastructure, cloud, platforms, developer tooling, and mission-critical application services for their organizations.

Information level: In our experience, it is possible to have “qualifying respondents” who nevertheless prove to have too little information or knowledge about the space to provide useful data from which to draw insights. We therefore apply an “information” screen to respondents as well. Specifically, we ask whether or not respondents could explain certain terms to their colleagues if asked to do so. In order to qualify for this survey, a respondent must say “yes” to this question for the term “Agentic AI”.

DevOps Maturity Model Definitions

This report uses the following definitions when referring to DevOps maturity levels:

• High-maturity organizations are defined as those with standardized delivery practices, highly effective incident response with automated rollback, and at least 61% deployment automation. 
• Mid-maturity organizations have mostly-to-highly standardized practices, effective incident response, and at least 31% deployment automation, but lack the full automation and governance of high-maturity organizations.  
• Low-maturity organizations have ad hoc or partially standardized practices, poor incident response capabilities, and minimal deployment automation (below 31%). 

Respondent Screens

It is technically impossible and improper to list a margin of error for a survey of this type. The respondents for this sample were drawn from an online panel with an unknown relationship to the total universe, about which we also do not know the true demographics. As such, the exact representativeness of this, or any similarly produced sample, is unknown.