Abstract

This research examines barriers and solution approaches relating to the deployment of Generative Artificial Intelligence (GAI) in contact centre businesses in the Australasian region. We find six main barriers to implementation and six key methods of strategies to solve the challenges with regard to obstacle responses from management and non-management staff, with a qualitative descriptive analysis of 53 obstacle and 30 solution responses. The most common were Data Quality and Availability (83.0 percent), Integration and Infrastructure (77.4 percent), and Cost and Resource Constraints (71.7 percent). The data shows that there is a strong relationship between the barriers to implementation, as, in fact, data challenges were co-occurring with infrastructure problems (34 instances) and trust concerns (33 instances) often. The solution strategies are not only fragmented but the maximum prevalence is just 16.7%, indicating there is a lack of agreement on the best implementation pathways between stakeholders. The findings suggest a paradox: stakeholders are highly aware of the governance priorities, but they are unable to describe concrete governance mechanisms and innovation frameworks. Our discussion provides evidence-based suggestions for organisations that have struggled with GAI adoption in customer-service situations, focusing on the prioritization of data foundations, integrated capability development, partnership-based strategies, and operationalised governance models for organisations that have struggled with GAI adoption in customer-service situations.


Keywords:
Generative AI, Service Sector, Contact Centres, Adoption Barriers, Readiness, and Governance.

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