- Centralize and improve data quality around customer interactions to enhance the accuracy, completeness, and timeliness of data insights;
- Improve customer retention and prospect conversion rates by developing gen AI use cases aimed at personalizing marketing content campaigns;
- Facilitate change management in marketing and sales by gaining adoption in a few winning approaches and sharing best practices rather than serially experimenting with many capabilities.
Target call center and service operations
Call centers, customer service departments, IT service desks, and other support services have significant amounts of data in the form of service tickets, knowledge bases, and user profile information from CRM and HCMS platforms. Gen AI applied in these areas can have a force-multiplying impact by improving customer or employee satisfaction scores, reducing costs, and improving job satisfaction for service desk employees.
“In support functions, gen AI expedites call center operations by generating rapid, context-aware responses to intelligently route queries, reduce average handling time, and improve resolution rate,” says Ram Ramamoorthy, director of AI research at ManageEngine. “In IT service management, AI-driven knowledge graphs provide issue diagnosis and proactive resolution, decreasing downtime.”
Ashwin Rajeeva, co-founder and CTO of Acceldata, recommends CIOs collaborate with department leaders on gen AI use cases and “track Net Promoter Scores and resolution times in customer support to quantify AI’s impact on loyalty and efficiency. In HR, measure time-to-hire and candidate quality to ensure AI-driven recruitment aligns with business goals. Observability metrics such as data quality, freshness, and consistency provide essential insights that enhance the reliability and precision of these AI-driven outcomes.”
