Artificial Intelligence and Robotic Process Automation together became the biggest technology revolution for industries nowadays. The applications that have cognitive capabilities, deals with creating software with self-learning capabilities that are able to recognize their environment and solve problems, like humans. Artificial Intelligence will naturally alter the banking, insurance and other financial services over next few years, impacting customer service, fraud mitigation, loans and credit scores, investment advisories. These all will use AI and Machine learning to deliver an excellent customer experience and efficient operations for banks, insurance companies and financial sector of the companies. Insurance companies have different kind of adoption of AI and robotic process automation (RPA) than Banks or Financial Services. Insurance companies are more serious about using AI and RPA for customer support. The major objectives of implementing AI are personalized customer experience, having error-free back-end processes which run without human intervention and faster turn-around-time. The security and compliance appeared to be the last priority. The e-commerce and social media apps have already set the bar incredibly high so users are coming with very high levels of expectation in terms of usability from banking and insurance apps. That brings us to the impact; AI will have to be on job to meet customer expectations. The traditional approach will not be able to deal effectively with volume, velocity and variety of data being generated. Data has to be collected from different source and which is in disparate formats. The new approach to BFSI is that decision making often goes beyond the traditional consideration of speed, functionality, ROI etc. In insurance, underwriting or personal financial advice, there is a sizeable element of subjectivity. Feeding these rules in AI systems may be difficult than we think. To address this, IEEE has been working on Ethically Aligned Design which necessitates that transparency, accountability and algorithms will have to be considered right at the time of design [Also Read: Robotic Process Automation (RPA) in Banking Industry] Implementing Robotic Process Automation and Artificial Intelligence will result in job cuts but it is temporary. The new opportunities will get created which requires highly skilled resources. The repetitive and routine task will be performed by automation and people can focus on more critical and skillful tasks. The real concern of using AI is its lack of maturity in standards. This creates silos of options which make vendor identification a major task. Another issue is, Machine Learning depends on huge amount of data – respondents have found it challenging to train their deep learning systems with very less amount of data. Appropriate talent or skilled resource availability is also a bit challenge for adopting AI.