Aim/Purpose.
The paper addresses the two important dynamic features of business intelligence (BI) – maturity and agility – and the interrelation between the two, projected into support for BI agility.

Background.
An analysis of published research sources, together with interviews with BI professionals, resulted in defining important traits of BI environment that support its ability to change and renew.

Methodology.
The research used a literature analysis to confirm contradictory issues between the ultimate stages of known BI maturity models and the need to develop BI agility. The most important issues have been projected against similar issues from interviews with BI professionals.

Contribution.
This paper attempts to define possible “pillars” of BI agility that have to develop together with growing BI maturity.

Findings.
The interviews, combined with previous research and literature sources, have shown that the ultimate goal of BI maturity journey is an optimized system encompassing the entire organization. Such approach often introduces rigidity and limits BI ability to change and adapt. On the other hand, this ability seems to be supported by certain managerial and human factors, where organizational culture appears to play a key role.

Recommendations for Practitioners.
There are certain types of organizational culture that are supportive for BI agility and contradict optimized and rigid maturity.

Recommendations for Researchers.
The presented conclusions are to an extent based on assumptions and should be tested by quantitative analysis, where possible. Further research models might include related and under-researched sets of issues like BI resilience and informing resilience in general.

Impact on Society.
Against wider context, value creation by advanced IT does not guarantee success by itself if human and especially cultural factors are neglected.

Future Research.
Testing of assumptions and hypotheses based on the findings of this paper. Expansion of research ideas to wider network of research partners to test assumptions against different backgrounds.