The Rise Of AI-Driven Process Automation In Regulated Industries

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Bibliografski detalji
Izdano u:Journal of International Crisis and Risk Communication Research vol. 8, no. S7 (2025), p. 54-60
Glavni autor: Ahmad, Anwar
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Nicholson School of Communication and Media at the University of Central Florida
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Online pristup:Citation/Abstract
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100 1 |a Ahmad, Anwar 
245 1 |a The Rise Of AI-Driven Process Automation In Regulated Industries 
260 |b Nicholson School of Communication and Media at the University of Central Florida  |c 2025 
513 |a Journal Article 
520 3 |a This paper investigates how artificial intelligence (AI) technologies are transforming process automation in regulated industries, with a focus on financial services. We pose the research question: How can AI-driven automation improve operational efficiency while maintaining regulatory compliance in highly regulated sectors? Through a synthesis of industry data, case studies, and architectural analyses, we examine the deployment of intelligent document understanding (IDU), decision orchestration platforms (DOPs), generative AI systems, and AI governance frameworks. Our findings demonstrate that these technologies not only reduce processing time and operational costs but also enhance compliance transparency and auditability. We argue that the convergence of these AI capabilities enables a new paradigm of innovation that aligns with regulatory mandates, offering a replicable model for other regulated domains. 
653 |a Customer services 
653 |a Accuracy 
653 |a Technology adoption 
653 |a Decision making 
653 |a Financial statement analysis 
653 |a Natural language processing 
653 |a Compliance 
653 |a Automation 
653 |a Documents 
653 |a Regulated industries 
653 |a Financial services 
653 |a Generative artificial intelligence 
653 |a Financial institutions 
653 |a Banking 
653 |a Case studies 
773 0 |t Journal of International Crisis and Risk Communication Research  |g vol. 8, no. S7 (2025), p. 54-60 
786 0 |d ProQuest  |t Public Health Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3236930666/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3236930666/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch