Digital transformation is having a dramatic impact on several industries, including financial services (Harvard Business Review, 2016). Given the pressures of digital transformation and the myriad options of technologies to adopt, executives face an increasing number of questions and factors to consider when deciding on their transformation approach. Further, with artificial intelligence (AI) on the rise, executives must consider how to incorporate AI into their plan and their business processes. For customer-focused industries such as financial services, a positive employee experience can translate into an improved customer experience. Executives can leverage various AI use cases to improve the employee and customer experiences, including after call summarization, agent assist co-pilots, next-best action suggestions, canned responses, sentiment analysis, and agent coaching/training. To dissect the factors that can improve employee experience and thus help executives make sound technology choices, this study took a quantitative deep dive with 340 customer service employees in the financial services industry to study how two real-time AI-powered tools, Agent Assist and After Call Summary, positively impact the employee experience. Using the Technology Adoption Model (TAM), the findings reveal that use of these real-time AI-powered tools improves the overall employee experience in terms of both perceived ease of use and perceived usefulness. The study also extended the TAM to examine employee attitudes towards and trust in AI. The findings show that both attitude and trust have a direct effect on the employee experience of AI tool use, as well as a moderating effect on the perceived ease of use of the After Call Summary tool. In addition to extending the literature on the TAM and on attitude towards and trust in AI in relation to real-time AI-powered tools, this study offers executives practical guidance for managing employee attitude towards and trust in AI when adopting these tools.