Usage Intention and Behavioural Adoption of Intelligent Automation in Manufacturing: An Empirical Study of Chennai-Based Firms

Intelligent Automation (IA), which is a mix of artificial intelligence (AI), robotic process automation (RPA), and data analytics, is making big changes in the industrial sector. IA has made things work better and faster. In many Indian factories, especially in regional clusters like Chennai, the strategic goal often comes before the work itself. There may be strategic benefits to IA, but no one has done a complete study on how manufacturing companies expect to utilize it and how they actually respond when they do. It's crucial to undertake study in the actual world on the things that effect this gap, such as how ready the organization is, how hard the technology is, and how resistant the consumers are. This study used a blend of two existing models as its research method: the Technology-Organization-Environment (TOE) model and the Unified Theory of Acceptance and Use of Technology (UTAUT2). The sample had 220 persons, including workers and supervisors from 15 different manufacturing enterprises in Chennai. We used SmartPLS to run Structural Equation Modeling (SEM) to see how performance expectations, effort expectations, social influence, organizational and technological factors, and facilitating environments all affect behavioral intention. The results reveal that both the desire to use and the actual behavior of using are greatly affected by performance expectations and supporting conditions. The scale of the company and the digital infrastructure it possesses both help govern these linkages. The model had good fit indices. The SRMR value was 0.052 and the R2 value for behavioral intention was 0.67. When compared to more common models like TAM, DOI, and basic UTAUT, the accuracy was 15−24% higher than what was expected.