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Artificial Intelligence in Everyday Life: Applications, Challenges, and Future Directions
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: https://doi.org/10.64388/IREV9I10-1716996
Abstract
Artificial intelligence (AI) has transitioned from a theoretical construct to a pervasive force embedded in modern daily life. This detailed report presents an expanded survey of AI applications across six critical domains: smartphones, virtual assistants, entertainment, healthcare, and transportation. By examining core architectures — machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision (CV) — this study evaluates both the transformative potential and the significant ethical challenges introduced by these technologies. Future trends including generative AI, edge AI, ambient intelligence, and Explainable AI (XAI) are also examined with projections through 2030.
Keywords
Artificial Intelligence, Machine Learning, Deep Learning, NLP, Computer Vision, Edge AI, Generative AI, Neural Processing Unit, Explainable AI, Smart Assistants, Autonomous Vehicles, Healthcare AI, Recommendation Systems.
References
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[5] McKinsey Global Institute. (2023). The state of AI in 2023: Generative AI's breakout year. McKinsey & Company. https://www.mckinsey.com/capabilities/quant umblack/our-insights/the-state-of-ai-in-2023- generative-ais-breakout -year
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How to cite this paper
@article{1716996,
author = {Parth Deshmukh, Neel Hirani},
title = {Artificial Intelligence in Everyday Life: Applications, Challenges, and Future Directions},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {3457-3461},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1716996.pdf},
abstract = {Artificial intelligence (AI) has transitioned from a theoretical construct to a pervasive force embedded in modern daily life. This detailed report presents an expanded survey of AI applications across six critical domains: smartphones, virtual assistants, entertainment, healthcare, and transportation. By examining core architectures — machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision (CV) — this study evaluates both the transformative potential and the significant ethical challenges introduced by these technologies. Future trends including generative AI, edge AI, ambient intelligence, and Explainable AI (XAI) are also examined with projections through 2030.},
keywords = {Artificial Intelligence, Machine Learning, Deep Learning, NLP, Computer Vision, Edge AI, Generative AI, Neural Processing Unit, Explainable AI, Smart Assistants, Autonomous Vehicles, Healthcare AI, Recommendation Systems.},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1716996}
}