From People to Algorithms: Does BPM Maturity Shape an AI-Ready Workforce?

Purpose: Introducing AI into an organization should not be limited to technological implementation alone. It also requires a coherent management framework that supports this transformation – especially regarding the workforce. The research focuses on the question: What are the relationships between BPM maturity, AI implementation, and workforce maturity in the organizations studied? The main objective is to examine how these three elements interact and what this means for organizations aiming to build readiness for AI-driven change. Design/methodology/approach: To explain the relationships between BPM maturity, AI implementation, and workforce maturity, a survey-based study was conducted among a convenience sample of 400 enterprises in Poland. In this study, multivariate data analysis methods were used: multiple correspondence analysis and binary logistic regression. Findings: Workforce maturity turned out to be a much more important predictor of AI implementation in organizations than BPM maturity. AI implementation was associated with the characteristics of the given organization: younger enterprises operating on the global market in the service and trade sectors had greater odds of AI implementation. Research limitations: The main limitation lies in the use of a non-random sampling technique. Furthermore, the level of AI implementation was assessed in general terms, without distinguishing between different types of artificial intelligence. Originality/value: The originality of this study lies in how it brings together BPM maturity, AI implementation, and the workforce dimension into a single framework. It served to produce a crucial insight: successful digital transformation is not just about having the right technologies – it’s about creating harmony between people, processes, and tools.