How to Cite:
Rajan Selvam, "AI-Driven Product and OT Strategy Framework for Resilient and Autonomous Operations" IJERMES, Vol. 1, No. 1, pp. 14-22, 2026.

Abstract:
The convergence of artificial intelligence (AI), full-stack software engineering, large language models (LLMs), and operational technology (OT) is creating new opportunities for organizations to develop resilient, adaptive, and increasingly autonomous operational environments. Traditional product engineering and OT management approaches generally rely on predefined rules, manually supervised workflows, fragmented monitoring systems, and reactive incident management. Such approaches become increasingly inadequate in highly distributed environments where software applications, cloud infrastructure, industrial assets, edge devices, and physical processes continuously generate heterogeneous operational data. This research proposes an AI-Driven Product and OT Strategy Framework (AIPOT-SF) for integrating product lifecycle intelligence with OT observability, AI-based decision-making, and LLM-agent-based autonomous operations. The proposed framework establishes a continuous feedback loop between product requirements, full-stack applications, telemetry, industrial assets, operational risks, AI reasoning, and automated remediation. The architecture combines event-driven data ingestion, digital representations of assets and applications, predictive analytics, LLM agents, tool-enabled reasoning, policy enforcement, simulation, and human oversight. A conceptual comparative evaluation indicates that the proposed framework can improve operational resilience, decision speed, cross-domain visibility, and adaptive resource management compared with conventional monitoring and rule-based automation. The research also identifies important challenges involving safety, explainability, cybersecurity, model reliability, legacy OT integration, and governance. The proposed framework provides a foundation for organizations seeking to transition from reactive IT/OT management toward resilient and autonomous product operations.

Keywords: Artificial Intelligence, Large Language Models, LLM Agents, Full-Stack Development, Operational Technology, Product Engineering, Autonomous Operations, Digital Twin, AIOps, Resilience, Industrial AI, OT Security.

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