Artificial Intelligence in BPM: Enhancing Process Optimization Through Low-Code Development

Kartheek Kalluri

doi:10.36948/ijfmr.2023.v05i06.23396

Artificial Intelligence in BPM: Enhancing Process Optimization Through Low-Code Development

Author(s)	Kartheek Kalluri
Country	United States
Abstract	The study examines integrated AI technology with low-code platforms in redefining Business Process Management (BPM). Presently, traditional BPM systems increase issues such as complexity, dependence on manual coding, and insensitivity to the modern pace of change in business. However, combined with low-code platforms, AI can well serve the basis of offering future solutions using predictive analytics, intelligent automation, and streamlined decision-making while remaining accessible to the majority of users whose work is unrelated to IT. This study is a completion of the mentioned three phases: (1) A literature review identifying knowledge gaps and analyzing the current use of AI in BPM; (2) Building the modeled order fulfillment process optimized with low-code tools and an AI model; and (3) Evaluation with qualitative and quantitative metrics like cost efficiency, gains, and user satisfaction. The results show that the January 1987 order processing time was reduced by 57%, operational costs had decreased by 40%, and customer satisfaction improved by 20%. There were some AI models, e.g., demand forecasting and logistics optimization, which reduced bottlenecks during the process and hence enhanced scalability. A good number of users, who were not yet connected to IT, indicated the importance of low code such as Microsoft Power Automate and Out Systems to enable them to deploy AI solutions. AI integration through low-code platforms democratizes BPM innovation, delivering scalable and efficient solutions to traditional BPM bottlenecks, concludes this study. Findings prove the validity of such an approach for boosting agility and thereby competitiveness in a dynamic business landscape.
Keywords	Artificial intelligence (AI), Low-Code Development Platforms, Business Process Management (BPM), Process Optimization, Predictive Analytics, Intelligent Automation
Field	Engineering
Published In	Volume 5, Issue 6, November-December 2023
Published On	2023-11-20
DOI	https://doi.org/10.36948/ijfmr.2023.v05i06.23396
Short DOI	https://doi.org/g82h4h

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Artificial Intelligence in BPM: Enhancing Process Optimization Through Low-Code Development

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