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Cotton soliton is a newly introduced notion in the field of Riemannian manifolds. The object of this article is to study the properties of this soliton on certain contact metric manifolds.

The authors consider the notion of Cotton soliton on almost Kenmotsu 3-manifolds. The authors use a local basis of the manifold that helps to study this notion in terms of partial differential equations.

First the authors consider that the potential vector field is pointwise collinear with the Reeb vector field and prove a non-existence of such Cotton soliton. Next the authors assume that the potential vector field is orthogonal to the Reeb vector field. It is proved that such a Cotton soliton on a non-Kenmotsu almost Kenmotsu 3-h-manifold such that the Reeb vector field is an eigen vector of the Ricci operator is steady and the manifold is locally isometric to.

The results of this paper are new and interesting. Also, the Proposition 3.2 will be helpful in further study of this space.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.