AI Coach Assist: An Automated Approach for Call Recommendation in
  Contact Centers for Agent Coaching
Md Tahmid Rahman Laskar Cheng Chen Xue-Yong Fu Mahsa Azizi Shashi Bhushan Simon Corston-Oliver
In recent years, the utilization of Artificial Intelligence (AI) in the
contact center industry is on the rise. One area where AI can have a
significant impact is in the coaching of contact center agents. By analyzing
call transcripts using Natural Language Processing (NLP) techniques, it would
be possible to quickly determine which calls are most relevant for coaching
purposes. In this paper, we present AI Coach Assist, which leverages the
pre-trained transformer-based language models to determine whether a given call
is coachable or not based on the quality assurance (QA) questions asked by the
contact center managers or supervisors. The system was trained and evaluated on
a large dataset collected from real-world contact centers and provides an
effective way to recommend calls to the contact center managers that are more
likely to contain coachable moments. Our experimental findings demonstrate the
potential of AI Coach Assist to improve the coaching process, resulting in
enhancing the performance of contact center agents.