Sep 2026· International Journal of Computer Science and Mathematical Theory· 0 citations
Explainable Artificial Intelligence (XAI)
TL;DR
The review combines recent research findings with guidance on new investigation tracks for developing all-encompassing AI systems which both spread far-reaching outcomes and follow sustainability requirements.
Abstract
The current trends in Artificial Intelligence technologies continually transform multiple business
sectors while changing how humans connect with machines. Contemporary technology views AI
as its essential component instead of remaining as a separate specialized study field. A review of
primary AI trends coupled with applications and obstacles in modern AI research served as the
focus of this academic paper. Healthcare decision transparency integrates with financial needs to
enable smart infrastructure deployment by connecting Explainable AI (XAI) with Federated
Learning under Edge Computing framework. The barriers to progress include major issues with
scalability together with interoperability standards and ethical needs for organizational
governance. Interdisciplinary teamwork constitutes an absolute requirement to construct
responsible AI systems together with dependable deployment frameworks as demonstrated through
the term paper. The review combines recent research findings with guidance on new investigation
tracks for developing all-encompassing AI systems which both spread far-reaching outcomes and
follow sustainability requirements.
This study proposes an integrative analytical architecture grounded in three interlocking layers: enabling technological foundations, intelligent sense-making processes, and context-sensitive deployment pathways that provide a holistic, implementation-ready framework for building intelligent systems that are not only h...
Artificial Intelligence (AI) is emerging as a defining technological force reshaping industries, governance, and society at an unprecedented pace. While domain-specific AI applications have demonstrated remarkable success, a holistic understanding of AI's cross-domain transformation patterns, shared challenges, and tra...
Kuldeep Singh V. Revathy, David Lalrochunga, Nirmala Choudhary· International Journal of Adv...· 0 citations
This review examines Green AI as an emerging paradigm for developing energy-efficient machine learning systems and explores its intersection with the principles of responsible AI, providing a roadmap for researchers and practitioners seeking to develop AI systems that balance computational performance with environmenta...
Krishnaveni C. V.· International Journal of App...· 0 citations
This article investigates the current state and foreseeable trajectory of artificial intelligence, focusing on its principal application domains and the governance challenges they raise, and proposes targeted policy recommendations at international, national, and organisational levels.
Artificial Intelligence has moved very quickly from experimental innovation to a foundational driver of transformation across industries including healthcare, banking, insurance and logistics, helping companies automate decision-making, enhance user experiences and discover the latest efficiencies. Still, the road from...
Madhurima Kommuru· International Journal of Art...· 0 citations
A comprehensive research framework for AI capabilities is integrated and constructs, clarifies the field’s consensus and research gaps, and not only enriches the theoretical research landscape in the field of AI capabilities but also provides practical guidance for organizations of various types to systematically build...
Hao Jiang· International Journal of Edu...· 0 citations
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