International Journal on Science and Technology

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The Rise of Explainable AI in Data Analytics: Making Complex Models Transparent for Business Insights

Author(s) Shafeeq Ur Rahaman
Country India
Abstract The Explainable AI-IDEA enables innovation in the field of Data Analytics by overcoming the challenges related to interpretability and transparency in complex machine learning models. This paper describes how XAI enhances trust in, usability of, and adoption of advanced analytics by making the decision-making process of AI systems comprehensible to the stakeholders. This article has underlined the role of XAI in mending the gap between model complexity and user comprehension to enable businesses to drive actionable insights with more confidence. Primary applications in finance, healthcare, marketing, and supply chain management have been reviewed for how XAI undergirds informed decision-making, accountability, and compliance with regulatory frameworks. This article also touches on emergent techniques and tools in XAI, like SHAP, LIME, and interpretable neural networks, said to promote transparency, ethics in AI use, and shareholder engagement. By demystifying AI-driven analytics, XAI opens the door to more trustworthy, effective, and inclusive business practices.
Keywords Explainable AI, XAI, interpretability, transparency, data analytics, business decision-making, SHAP, LIME, Ethical AI, machine learning models, stakeholder trust, actionable insight.
Field Computer > Data / Information
Published In Volume 15, Issue 2, April-June 2024
Published On 2024-04-03
Cite This The Rise of Explainable AI in Data Analytics: Making Complex Models Transparent for Business Insights - Shafeeq Ur Rahaman - IJSAT Volume 15, Issue 2, April-June 2024. DOI 10.5281/zenodo.14471879
DOI https://doi.org/10.5281/zenodo.14471879
Short DOI https://doi.org/g8vk8t
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