AI in commercial banks can reduce losses in lending, increase security in processing payments, automate compliance work, and improve customer targeting, but challenges include technological advantages, embedding AI in business processes, and ensuring user acceptance.

Applications of Artificial Intelligence in commercial banks – A research agenda for behavioral finance

AI adoption in Malaysia's banking industry faces challenges like regulatory requirements, data privacy, and IT infrastructure, but customer attitudes and norms significantly influence their intention to adopt AI in services.

Adoption of artificial intelligence in banking services: an empirical analysis

AI in banking offers opportunities for personalized services, smart wallets, decision-making, and cybersecurity improvements, but must overcome challenges like job loss, privacy breaches, and loss of emotional "human touch".

Opportunities and Challenges of Artificial Intelligence in Banking: Systematic Literature Review

AI in banking has significantly disrupted the sector, making it more customer-centric and technologically relevant, but trust deficits remain a major challenge in its implementation.

Awareness and Impact of Artificial Intelligence Technology in Banking: A Study Among Bank Employees in Changanacherry Municipality, Kerala, India

Data science and AI are revolutionizing the banking and finance industry, but face challenges like data quality, privacy, and ethical concerns.

A review article: -the Growing Role of Data Science and AI in Banking and Finance

AI in the banking sector can combat fraud, improve compliance, and reduce costs, but it comes with risks and regulatory constraints.

Artificial Intelligence in the Banking Sector – A Critical Analysis

AI-oriented role models and process capabilities are essential for successful AI implementation in the banking sector, reducing human involvement and moral trepidations.

Drivers of Artificial Intelligence in Banking Service Sectors

AI-enabled technologies in the banking industry can improve decision-making, reduce fraud risk, and enhance customer experience in various domains.

The use of Artificial Intelligence in the Banking Industry

AI in banking can enhance security, fraud detection, and anti-money laundering, while addressing privacy concerns and addressing limitations like data scarcity and biases.

Artificial Intelligence for Futuristic Banking

AI integration in banking and finance has improved decision-making processes, reduced operational costs, and increased profitability, but data privacy, bias, and ethical implications must be addressed for responsible use.

Role of artificial intelligence in banking and finance

AI implementation in the Indian banking sector significantly improves performance, but challenges like linguistic diversity, customer trust, and data security hinder its widespread adoption.

Artificial Intelligence and Robotics and their Impact on the Performance of the Workforce in the Banking Sector

Awareness, attitude, norms, perceived usefulness, and knowledge of AI technology positively influence consumers' intention to adopt AI in the banking sector, while perceived risk has a negative but significant impact.

Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective

Compatibility, privacy, security, and technology advantages are crucial for successful AI-based HCM adoption in banks.

AI-enabled human capital management (HCM) software adoption using full consistency method (FUCOM): evidence from banking industry

AI-driven banking services in emerging markets can provide personalised experiences, but require human intervention and infrastructure improvements for successful implementation.

AI-driven banking services: the next frontier for a personalised experience in the emerging market

AI-powered cybersecurity systems can effectively identify threats in digital banking, supporting business efficiency and mitigating cyber risks.

AI-Powered Cybersecurity: Identifying Threats in Digital Banking

Russian business and consumers perceive AI in the banking sector positively, with Sberbank specialists embracing its implementation, but consumers show some mistrust due to misunderstandings.

Consumers’ Perception of Artificial Intelligence in Banking Sector

Singapore's Monetary Authority has issued guidelines on AI and data analytics (FEAT Principles) to ensure a unified approach and minimize risks in the banking sector.

Deployment Of Ai In Banking: Comparison Of Russian And Singaporean Approaches

Digital natives value convenience and fast banking, but not AI-enabled mobile banking, suggesting a need for improved features and accessibility.

Mobile banking and AI-enabled mobile banking

AI does not affect banking performance, while operational risk management positively affects it, with regulations strengthening the influence of AI on banking performance.

The Effect of the Use of Artificial Intelligence and Operational Risk Management on Banking Performance with the Implementation of Regulation as a Moderation Variable

AI integration in banking leads to growth, efficiency, and increased user convenience, enabling banks to innovate more quickly, compete with digital natives, and achieve sustainable increases in valuations and profits.

Banking Industry's Transformation with Aid of AI Technology

what are the challeneges in implementing AI in banking

These studies suggest that challenges in implementing AI in banking include regulatory requirements, data privacy, IT infrastructure, user acceptance, trust deficits, job loss, ethical concerns, and maintaining the human touch.