AI-enabled benefits realization management

Sammanfattning

In this age of digital transformation and rapidly evolving landscape, organizations are under constant pressure to deliver value from their investments through various initiatives and projects. As a result, benefit realization management (BRM) has emerged as an important and critical area in project management (PM) practices to ensure that companies align with organizational strategy and can measure the value creation and sustainment from the project/program outcomes. In parallel, the rise of artificial intelligence (AI) has introduced many multiple transformative capabilities for the organizations across multiple business areas and processes, including PM practices. The problem is that BRM is not used on the scale it can be used to make organizations more effective in their PM practices in IT projects leading to long-term benefits for the organizations. The study examines the ways in which AI can be used to introduce or enhance the use of BRM practices amongst IT practitioners. It also looks into tangible opportunities and challenges AI bring to the table when applied across BRM framework. To conduct the research for this study, qualitative research strategy was chosen with semi-structured interview approach as the data collection strategy with thematic analysis as chosen data analysis method. In terms of sampling strategy, purposive sampling of IT PM practitioners from companies across Sweden, India and US, with knowledge of BRM and familiarity with AI tools, was done resulting in seven interviews. The results of the study can be divided into three buckets, each answering the chosen research questions – the first bucket maps the opportunities to the BRM framework, namely benefits identification, execution and sustainment. The second bucket sheds light on the opportunities AI brings for BRM practices across data processing related, process related, people related and ease of use advantages. The third bucket highlights the challenges that PM practitioners are likely to face when applying AI in BRM practices, including, issues related to trust, data, cost, technology, organization and hard to replaces human connection across BRM framework applications. The results are followed by discussions related to the findings including the interpretation, surprises and implications found throughout the research process. To summarize, it is clear that AI brings wide range of positive impacts to ease the use and implementation of BRM framework into organizational IT practices; understanding the pointed challenges, the companies can be more prepared and get success to overcome the hardships quicker, thus setting them to a path to remain ahead of their competition in the market. The study also discusses about some of the ways in which research quality has been ensured, limitations in the research and related future work that can be taken up further to enhance the importance of BRM and AI in the field of academia.