Transition from Traditional SAP/SaaS-Based Systems to AI/ML-Based Enterprise Structures for Energy Companies
Year: 2025
Type: article
Abstract: As the global energy industry navigates unprecedented challenges- ranging from decarbonization and renewable integration to regulatory demands and consumer expectations- the limitations of legacy SAP/SaaS systems have become increasingly evident. This article explores how energy enterprises are transitioning toward AI/ML-based digital structures, emphasizing scalable system architecture, workforce upskilling, and organizational relearning. Drawing upon real-world examples from leading global and Indian companies, recent policy developments, and academic studies, the article illustrates how AI/ML adoption transforms energy operations. It presents comparative analyses, enriched system requirement insights, capacity scaling, and case examples highlighting cost reductions, efficiency gains, and sustainability improvements. Visuals, tables, and references are integrated to provide clarity and depth, making this piece relevant to both academic researchers and business leaders.
Author: Vineet Khandelwal
Institution: Indian Institute of Technology Dhanbad
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4414486961