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Data-Driven Transformation of Technical Pre-Sales Engineering through AI and Machine Learning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 41 |
| Year of Publication: 2025 |
| Authors: Divyanshu Joshi |
10.5120/ijca2025925719
|
Divyanshu Joshi . Data-Driven Transformation of Technical Pre-Sales Engineering through AI and Machine Learning. International Journal of Computer Applications. 187, 41 ( Sep 2025), 13-20. DOI=10.5120/ijca2025925719
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) are transforming the landscape of technical pre-sales engineering. This research analyzes studies from 2019 to 2025 to determine how AI/ML technologies are transforming pre-sales activities, simplifying deal qualification, improving predictions, and enhancing customer engagements. The literature review highlights three primary ways these technologies are utilized—augmentation, automation, and transformation—showing evidence that productivity can rise by as much as 30%, sales cycles decrease by 25%, and predictivity rates enhance by more than 20%. Industry-specific quantitative research and case studies indicate strong positive impacts on organizational performance, sales efficiency, and customer satisfaction. Ethical concerns like transparency in data usage, eliminating bias, and responsible data utilization are also addressed. The research concludes with proposed future studies, emphasizing the necessity of achieving a balance between the advantages of AI and human expertise to provide optimal value in technical pre-sales engineering.
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