Integrating AI Adoption Frameworks with Digital Maturity Models: Strategic Pathways in a Rapidly Evolving Technological Landscape

The significant pace of technological change due to artificial intelligence (AI) is transforming the competitive and operational landscapes of contemporary organizations. While there are models such as the technology acceptance model (TAM), the unified theory of acceptance and use of technology (UTAUT) and the technology–organization–environment (TOE) framework, which can help set the context for understanding adoption behaviour, they are rarely considered in parallel with the longitudinal perspectives provided by digital maturity frameworks. This study provides a bridge across this divide by combining traditional adoption models alongside constructs from digital maturity, grounded in dynamic capabilities theory, to represent the processes whereby firms are sensing, seizing and reconfiguring resources in response to technology disruption. The study adopts a qualitative–descriptive design that will identify characteristics and constructs that are determinants of successful AI integration, incorporating a case illustration using secondary data. Four key determinants were identified to successfully integrate AI, including executive sponsorship, mature data governance, continuous skill development and ethical and regulatory compliance. The inclusive framework presented illustrates how the development from early adoption to mature stages occurs and demonstrates that sustained capability-building leads to greater adaptability and long-term value. The case illustration demonstrates how theory-based knowledge is transferable into practice, which reinforces the findings of the study and highlights its relevance for scholars and practitioners alike. The research findings provide a holistic, empirically supported model for guiding the adoption of AI in rapidly changing digital environments.