Artificial Intelligence (AI): The New Look of Customer Service in a Cybersecurity World

Cybersecurity leaders are not adequately developed to guide the re-engineering of quality customer service (QCS) workflows, designed with automation and AI, that interrelate with people through customers' perceptions. Realizing re-engineering processes should be a team effort with well-versed leadership and stakeholders guiding the successful design through a follow-up process. Leaders must shape compelling and straightforward needs to learn and teach employees and chat boxes indispensable customer service skills demonstrating patience, self-discipline, flexibility, and resourcefulness in communication with irritated customers or difficult circumstances. Whether the analysis, design, development, and implementation struggles are vacuums in cybersecurity knowledge, skill, and abilities or a dearth of budget and resource limits, creating thorough QSC workflows and training requires time and purpose. This knowledge must be proactively, not reactively built. QSC re-engineering epitomizes a shift from reactionary behaviors to proactively preparing a well-defined collection of intends, activities, and aims delineating how organizations will contend through products and services. This article should benefit respondents absorbed in the success of updating and implementing QCS actions and workflows, practitioners who guide direct customer services initiatives, enterprise governance strategists, QCS and machine learning trainers, and learners who want to know more about QCS swathed in cybersecurity.