Strategic Implementation of AI Agents in Consulting : Use Cases and Business Benefits - Vondrášek, Viktor (2025)
This thesis investigates the strategic implementation of AI agents within consulting firms, examining internal use cases, associated business benefits, challenges, and strategic approaches. Employing a qualitative methodology, seven semi-structured interviews with industry professionals were conducted in April 2025, with six held via Microsoft Teams and one in the respondent's office. The resulting data were transcribed, coded using MAXQDA, and analyzed thematically. The study found that AI agents are currently leveraged to automate repetitive tasks such as research, data handling, and document drafting, yielding substantial efficiency improvements. Significant implementation challenges include data quality and access, human factors like user adoption and skill gaps, technical limitations, and client concerns. Strategic considerations highlight diverse approaches, with hybrid models combining in-house development and outsourcing proving advantageous. Based on respondents‘ insights, the thesis concludes that effective AI agent adoption in consulting operations requires prioritizing data readiness, investing in training, managing organizational change, and maintaining client trust.