Translating complexity: Thought leadership in artificial intelligence
A foundational series on human questions of a driverless world
In an industry with approximately 60% annual employee turnover, this research paper and presentation explore how generative AI can enhance agent performance. The work challenges the narrative of AI as a replacement for humans, especially when 71% of Gen Z customers still turn to phone calls for the most effective resolution. Instead, it advocates for a collaborative model where technology empowers, rather than replaces, human agents.
Drawing from real-world enterprise case studies, the research provides practical strategies and highlights several key findings:
- Human-AI Synergies: Generative AI can be used to provide instant answers to mundane questions. This synergy frees up human agents to focus their skills on more specialized and complex customer issues that require critical thinking.
- The Importance of Human Judgment: The paper underscores that human oversight is essential and, in some cases, legally required. For example, legislation like the Digital Services Act forbids purely automated decision-making for certain policy violation appeals.
- Localization at Scale: AI offers a significant leap forward for global operations. Modern AI localization systems can produce outputs on par with traditional machine translation for 50% of the cost and are 80% faster.
The central conclusion is that the future of customer service is not a zero-sum game between humans and technology. Because AI models lack empathy and cannot replace the nuance of human judgment, the most effective approach is a collaborative one that leverages the distinct strengths of both.
More information about this work can be found at the Information Research journal website.