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Artificial Intelligence in the Next Decade: Opportunities, Risks, and a Proposed Framework for Human-Centered AI Adoption
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: 10.64388/IREV10I4-1724023
Abstract
Artificial Intelligence (AI) has evolved from rule-based systems into technologies capable of learning from data, generating content, understanding natural language, recognizing patterns, and performing increasingly complex tasks. Machine learning, deep learning, generative AI, multimodal AI, and emerging agentic AI are transforming healthcare, education, finance, agriculture, manufacturing, transportation, cybersecurity, business, and scientific research. At the same time, AI creates concerns involving privacy, algorithmic bias, explainability, cybersecurity, employment disruption, misinformation, data dependency, environmental impact, and excessive dependence on automated systems. This paper reviews the opportunities, risks, and future development of AI and proposes a Human-Centered AI Adoption Framework. The framework places data quality, privacy, fairness, security, transparency, human oversight, continuous monitoring, and accountability throughout the AI lifecycle. The central argument is that future AI adoption should strengthen human capabilities rather than remove human responsibility.
Keywords
AI ethics; artificial intelligence; generative AI; human-AI collaboration; responsible AI
How to cite this paper
@article{1724023,
author = {Farzana, Anita, Bhumi, Dr. Amanjot Kaur},
title = {Artificial Intelligence in the Next Decade: Opportunities, Risks, and a Proposed Framework for Human-Centered AI Adoption},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {3070-3077},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724023.pdf},
abstract = {Artificial Intelligence (AI) has evolved from rule-based systems into technologies capable of learning from data, generating content, understanding natural language, recognizing patterns, and performing increasingly complex tasks. Machine learning, deep learning, generative AI, multimodal AI, and emerging agentic AI are transforming healthcare, education, finance, agriculture, manufacturing, transportation, cybersecurity, business, and scientific research. At the same time, AI creates concerns involving privacy, algorithmic bias, explainability, cybersecurity, employment disruption, misinformation, data dependency, environmental impact, and excessive dependence on automated systems. This paper reviews the opportunities, risks, and future development of AI and proposes a Human-Centered AI Adoption Framework. The framework places data quality, privacy, fairness, security, transparency, human oversight, continuous monitoring, and accountability throughout the AI lifecycle. The central argument is that future AI adoption should strengthen human capabilities rather than remove human responsibility.},
keywords = {AI ethics; artificial intelligence; generative AI; human-AI collaboration; responsible AI},
month = {October},
doi = {https://doi.org/10.64388/IREV10I4-1724023}
}