Data and AI at the Edge in Operational Technology

This whitepaper discusses the integration of Data and AI at the edge within operational technology (OT) across various sectors. It outlines how embedding AI into OT can lead to significant improvements in efficiency, quality, uptime, and safety. The document details the benefits of localized analytics and autonomous decision-making, which optimize asset performance and streamline workflows. It also emphasizes the importance of aligning edge capabilities with enterprise-wide digital architectures to ensure secure data flows and effective decision-making. The paper presents real-time analytics, predictive maintenance, quality control, and autonomous operations as key applications of edge AI. Furthermore, it highlights the impact of edge AI on sectors such as manufacturing, energy, logistics, healthcare, and smart cities, illustrating how organizations can achieve proactive operations and enhance overall business outcomes. The strategic and financial considerations for investing in edge AI are also examined, providing insights for leaders aiming to scale these technologies effectively.