Strategies for Implementing Process Automation with Artificial Intelligence in Startups
Keywords:
Artificial intelligence, process automation, startups, qualitative research, strategy prioritizationAbstract
This study aimed to identify and prioritize the key strategies that enable startups to effectively implement process automation using artificial intelligence (AI), addressing both organizational and technological dimensions. A qualitative research design was employed, using purposive sampling to select 21 participants, including founders, senior managers, and technical experts from technology-driven startups in Tehran, Iran. Data were collected through in-depth semi-structured interviews designed to explore participants’ experiences with AI-driven automation adoption. Interviews continued until theoretical saturation was reached. All interviews were transcribed verbatim and analyzed using NVivo 14 through open, axial, and selective coding to generate themes. After the qualitative phase, the identified strategies were subjected to quantitative prioritization; participants rated the relative importance of each strategy, and descriptive statistical analysis was performed using SPSS to establish ranking and mean scores. Six major strategic factors emerged: Strategic Alignment & Vision, Data Governance & Quality, Resource & Infrastructure Readiness, Technology Selection & Integration, Change Management & Culture, and Performance Measurement & Continuous Improvement. Ranking results indicated that Strategic Alignment & Vision was perceived as the most critical (M = 4.72; 22.5%), followed closely by Data Governance & Quality (M = 4.56; 21.7%) and Resource & Infrastructure Readiness (M = 4.31; 20.5%). Technology Selection & Integration (M = 4.18; 19.9%) and Change Management & Culture (M = 3.97; 19.0%) followed, while Performance Measurement & Continuous Improvement (M = 3.85; 18.6%) was ranked lowest but still recognized as essential for long-term success. The study provides a practical, evidence-based roadmap for startups seeking AI-driven process automation. Aligning automation with strategic vision, ensuring robust data governance, and preparing technical and financial infrastructure are foundational. Equally, careful technology selection and fostering cultural adaptability support effective and sustainable automation.
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Copyright (c) 2024 Sina Fayezi, Mohammad Taghi Karimi (Author)
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