Integrating Artificial Intelligence in Cloud-Based Automation for Enhanced Performance and Cost Savings
Applying Artificial Intelligence in cloud-based automation can enhance efficiency and reduce enterprise operational costs. Automation in the cloud enables centralized management and execution of tasks, a better quality automation experience, and AI, which can empower intelligent decision-making in such work processes. Such behavior provides the options to maximize automation processes more accurately and efficiently with AI in real time. It can save a lot of money because it helps make mistakes and waste resources, and it helps conserve a lot of time. It can deal with and learn from data, making predictive maintenance and proactive decisions possible. This cloud-based integration also allows scale-up over time quickly, so demand-level changes do not lead to costly hardware and infrastructure upgrades. It is an affordable solution for businesses of all sizes. AI in cloud-based automation also enables more advanced technologies like machine learning, natural language processing and computer vision that can provide added performance and automate processes. Benefits of Combining AI with Cloud-Based Automation In what follows, we will indicate how the combination of cloud and automation to bring in AI-based, IT-embedded solutions provides a potent antidote to complex operations for enterprises seeking continuous performance enhancement with reduced operational costs, all backed up by data-based decision-making.
Authors
- T. Prem Jacob (ORCID: https://orcid.org/0000-0002-3383-0321)
- Suhas Ballal (ORCID: https://orcid.org/0000-0002-6041-8332)
- Trapty Agarwal
- Shrabanee Swagatika
- Lalit Khanna
- Mohan Garg
Institutions
- Jain University (IN)
- Siksha O Anusandhan University (IN)
- Maharishi University of Management and Technology (IN)
- Sathyabama Institute of Science and Technology (IN)
- Chitkara University (IN)
Publication Details
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1109/netcrypt65877.2025.11102494
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00