AHFE Open AccessAI Integration for Bridging Advanced Analytics and Business Value in a Regulated World
Abstract
The integration of Artificial Intelligence (AI) and advanced analytics into enterprise strategypromises substantial business value, from improved decision-making to new product innovation.However, realizing this potential is challenging, especially in highly regulated industries wherecompliance, data governance, and ethical constraints are paramount. This paper examines howorganizations can effectively bridge advanced analytics and tangible business value in a worldincreasingly defined by strict regulations. We present a comprehensive review of literature on AIadoption, value creation, and governance, identifying key enablers and barriers to successful AIintegration. A qualitative methodology is employed, synthesizing insights from academicresearch and industry case examples to outline best practices for aligning AI initiatives withbusiness objectives while upholding regulatory compliance. The results and discussion highlightcritical success factors, including strategic alignment of AI use-cases, robust data management,cross-functional governance frameworks, and a culture of responsible innovation. We find thatbalancing agility and compliance is essential: companies must innovate with AI under carefuloversight to avoid legal pitfalls and maintain stakeholder trust. This study contributes anintegrated perspective on deploying AI for business gain in regulated environments and proposesa roadmap to guide organizations. Conclusions emphasize the need for ongoing adaptation, asevolving regulations (such as the EU AI Act) and emerging technologies (like generative AI) willshape future integration efforts. Future work should explore longitudinal case studies to quantifyvalue realization and refine governance models for the next generation of AI solutions.
Keywords: Artificial Intelligence, Advanced Analytics, Business Value, Regulatory Compliance, AI Governance, Enterprise Integration, Responsible AI, Regulated Industries
DOI: 10.54941/ahfe1006924
Cite this paper
More from this volume
- Warnings and Multilingual Audiences
- EAT Da Vinci 3.0_Translating Cinematic Narrative into Media Art Installation
- From Manual to Automated: Enhancing Inclusivity in Foreign Language Education with Technology
- The effect of multi-sensory physical experiences in daily emotional self-tracking service for emotion self-awareness
- Parametric generation based graphic design and spatial expression research
- Gender Stereotypes in Video Gaming: Impacts of Anxiety Levels, Verbal Communication, and Performance
- Exploring Usability And User-experience Metrics With A Novel AR App In The MASTERLY Project
- Drawing Dialogues Between Generative AI and Children with Autism: A Qualitative Study on the Externalization of “Understanding”
- Human-Centered Design of Integrated Food Service Management Systems: Reducing Cognitive Load in Resource-Constrained Kitchen Operations
- The Design Futures Art-driven (DFA) Method: Structuring Art-Tech Collaboration for Sustainable Future of Food System
- Increasing importance of Instinct
- Bridging the Privacy Gap: Stakeholder Solutions to Support Transparent Data Management Practices in Digital Health Research