Intelligent Automation focuses on integrating artificial intelligence with automated systems to enhance operational efficiency and decision-making. It uses machine learning, analytics, and rule-based algorithms to automate complex workflows with minimal human intervention. Intelligent automation improves productivity by predicting outcomes, optimizing processes, and reducing repetitive workloads. It enables adaptive and self-correcting operations across industries. By combining data insights with real-time responses, it ensures consistent and reliable performance. Intelligent automation strengthens digital transformation and supports end-to-end process enhancement. Overall, it drives smarter business operations and fosters innovation in modern automated environments.
| 2-5 Days | Initial Quality & Plagiarism Check |
| 25-35 Days |
Peer Review Feedback |
| 45-60 Days | Total article processing time |
| English | Publication Language |
| Single-Blind | Peer-Review Model |
| 17% | Acceptance Rate |
| <18% | Similarity Screening Guideline |
| Open Access | Access Model |
All manuscripts undergo editorial assessment and originality screening as part of the journal's evaluation process. The acceptance rate shown is based on journal-level editorial data and may change over time. Similarity reports are assessed editorially and are not interpreted solely on the basis of a numerical similarity score.