Skip to content

Generative AI Adoption in an Energy Company: Exploring Challenges and Use Cases

2026 · arXiv.org · Vol abs/2602.09846 · 0 citations · 30 references
Computer Science

TL;DR

This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.

View source

Similar papers

Cybersecurity, and Artificial Intelligence

The study demonstrates that the successful deployment of AI Builder is contingent more on organizational readiness and accountability than technological maturity, and offers an informed blueprint to organizations adopting low-code AI platforms.

P. Vutla, Triveni Yenugu · 0 citations
Review Aug 2026

Integrating Generative AI Into Organizational Workflows: Evidence From Practitioner Reports

The findings indicate that GenAI use is widespread in the sample, but integration into business processes is incremental and localized rather than deeply embedded and governance practices are evolving alongside its use.

Shirin Hasavari, J. Zaveri · 0 citations
Open access Jul 2026

AI Builder Integration and Implementation: A Qualitative Study on Microsoft Power Platform

The study demonstrates that the successful deployment of AI Builder is contingent more on organizational readiness and accountability than technological maturity, and offers an informed blueprint to organizations adopting low-code AI platforms.

P. Vutla, Triveni Yenugu · 0 citations
Review Open access Aug 2026

Generative Artificial Intelligence in Business Decision-Making: Emerging Frameworks, Enterprise Applications, and Future Challenges

Evidence is synthesized that GenAI functions most reliably as an augmentation tool that aggregates and structures diverse inputs for human judgment, rather than as an autonomous decision-maker, and that the primary barrier to enterprise value is organizational and workflow integration rather than model capability.

M.SANGEETHA, Una Suman Kumar Patro, K.ARPITHA et al. · 0 citations
Conference Open access 2026

AI-enabled hybrid project management framework for software operations excellence

A conceptual framework that connects traditional project governance, agile execution and artificial intelligence (AI)-supported decision-making within one operating model is developed and argues that AI creates value only when its outputs are connected to an existing decision process at the point where action is still...

Sanjay Kumar, S. R. · 0 citations

Related blog posts

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

Microsoft Research Blog Jul 30, 2026

Echoverse: Deep, evolving environments for computer-use agents

Computer-use AI agents struggle with multi-step workflows like email and customer support. Echoverse trains agents in realistic environments rather than simply providing more training tasks, helping them improve as the tasks, tests, and environments evolve. The post Echoverse: Deep, evolving environments for computer-use agents appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.