Developing business case for Artificial Intelligence for IT Operations
Panda, Sukant (2022)
2022
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022053013321
https://urn.fi/URN:NBN:fi:amk-2022053013321
Tiivistelmä
AIOps stands for Artificial Intelligence for IT Operations. AIOps combines big data and machine learning to automate IT operations processes, including event correlation, abnormality detection and root cause identification. At present the AI adoption is held back due to many challenges in the people (lack of knowledge), process (current maturity, data quality/ quantity) and technology areas.
This thesis studied the relevant theory to developing business case for AIOps adoption by companies.
The theories and frameworks presented in this thesis were gathered from academic papers, business books, personal experience and internet sources connected to AIOps, digital operations and modern IT practices. Qualitative research methods were used extensively used in the thesis like unstructured interviews, focus groups, and observations. The target group for data collection were key stakeholders from AIOps offering, sales, solution, and delivery team. The process included analysing the status of business case development, finding the gaps, and creating a framework to guide the future business case development for AIOps solution.
The results of this study provided practical knowledge of how business case of AIOps is developed for Enterprise level adoption. The findings and conclusion of the thesis will help to develop better business cases for AIOps solutions in future.
This thesis studied the relevant theory to developing business case for AIOps adoption by companies.
The theories and frameworks presented in this thesis were gathered from academic papers, business books, personal experience and internet sources connected to AIOps, digital operations and modern IT practices. Qualitative research methods were used extensively used in the thesis like unstructured interviews, focus groups, and observations. The target group for data collection were key stakeholders from AIOps offering, sales, solution, and delivery team. The process included analysing the status of business case development, finding the gaps, and creating a framework to guide the future business case development for AIOps solution.
The results of this study provided practical knowledge of how business case of AIOps is developed for Enterprise level adoption. The findings and conclusion of the thesis will help to develop better business cases for AIOps solutions in future.