Dell prioritizes AI use cases in field services based on return on investment, focusing on solving significant business challenges rather than just adopting technology. They employ a pilot testing approach with a select group of engineers for new AI capabilities before wider deployment, ensuring real-world feedback and smoother integration. A key example of their AI implementation is AI-powered label scanning for service tag and PPID (part identification) numbers, which significantly improved accuracy. Dell faces challenges like resource limitations, finding data scientists, ensuring data quality, managing compute costs, and monitoring AI model accuracy.