## 2 Literature Review
### The Impact of Automation Through Mechatronic Systems and AI on Banking Efficiency and Performance  
As automation and artificial intelligence become increasingly embedded in the banking sector, mechatronic systems and AI solutions are gradually starting to replace human employees in various financial operations. However, the role of human employees remains essential, especially in direct interactions with customers, where the human factor significantly influences consumer experience and loyalty to the banking institution. According to studies, in the retail financial industry, consumers have high bargaining power, as they are able to compare products and services offered by different financial intermediaries [74]. In such a context, employee performance becomes a determining factor [75; 76], and employees play an important role in meeting consumer needs [77; 78]. Research on the relationship between customers and banks emphasizes that direct interactions between employees and customers are essential for maintaining long-term relationships, which contributes to the profitability of financial institutions [79; 80]. Moreover, consumer perceptions of service quality are largely influenced by employee behavior, and employees are considered to be mainly responsible for a positive or negative experience with the bank [81]. However, technological advancement is driving a significant transformation in the industry, with artificial intelligence becoming central to redefining banking processes. While, on the one hand, human interaction remains essential in maintaining trusting relationships with customers, on the other hand, AI is consolidating its position in optimizing operational efficiency, risk analysis, and service personalization. In recent years, research on the impact of artificial intelligence in the banking sector has highlighted both the benefits and challenges of this technology. Bibliometric studies conducted by [PERSON] and [PERSON] [82], [PERSON] et al. [11], and [PERSON] et al. [83] highlight the role of AI in optimizing banking efficiency, managing risk, and driving innovation, but also the need for further investigation to fully understand its effects on the financial industry. Analyzing recent trends, [PERSON] et al. [84] highlighted the applicability of AI in risk assessment, operational efficiency, and banking performance, while [PERSON] et al. [85] identified the increasing influence of AI and IoT in financial engineering. Other studies [86], such as the one conducted on a university sample, showed that demographic factors such as age and education level influence trust in banks, while [PERSON] [87] highlighted the need to improve the use of AI in bank accounting in Jordan. In terms of AI adoption, [PERSON] [88] identified determinants such as perceived usefulness, perceived risk, and social norms, while [PERSON] et al. [89] showed that AI contributes to improving the return on banking assets, although in the long run it may create performance challenges [90; 91; 92; 93]. Thus, the following research hypothesis can be formulated:  
**Hypothesis 2 (H2). **_The heterogeneous impact of AI solutions on banking performance has a differentiated effect across banks with varying profitability levels._  
The adoption and effectiveness of artificial intelligence (AI)-based solutions in the banking sector do not have a uniform effect on institutional performance. Banks with high profitability (as measured by ROE) can more easily access advanced technologies and sustain the costs of staff training, systems integration, and data analytics, thereby realizing greater benefits from the use of AI. In contrast, institutions with low profitability may have difficulties in fully implementing these solutions or may use less sophisticated technologies, leading to more modest effects on performance.