AI Adoption in the Research Component of Business Processes: Enhancing Effectiveness in Client Acquisition for IT Services Organizations

This study explores the adoption of Artificial Intelligence (AI) within the research component of business processes and its potential to enhance client acquisition effectiveness in IT services companies. In an environment where traditional research methods remain dominant yet inefficient, AI offers opportunities to streamline data collection, improve insight generation, and reduce time-to-strategy. However, AI adoption across IT research teams remains inconsistent due to barriers such as data privacy concerns, skill gaps, and limited organizational readiness. The research applies a qualitative approach using semi-structured interviews with nine professionals from a global IT services organization. Thematic analysis reveals that while AI tools such as ChatGPT and Microsoft Copilot are increasingly used for summarization and trend analysis, their integration remains exploratory rather than systematic. Barriers for AI adoption include limited AI literacy, lack of structured training, leadership hesitation, and concerns about trust and compliance. Conversely, enablers such as pilot testing, internal AI platforms, peer learning, and strong leadership support are identified as critical facilitators of successful adoption. A five-phase AI Adoption Framework is then proposed, offering a practical roadmap for organizations to transition from ad-hoc AI use to structured, outcome-driven integration. The findings contribute to academic literature by addressing gaps in B2B AI adoption research and offering practical implications for IT service organizations seeking to enhance research efficiency and client acquisition performance through AI.