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This study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.

This study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.

The performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.

The cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.

This study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.

Some similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

For over a decade, fintech has challenged traditional business models and processes in the financial services industry. The ongoing disruption has necessitated the digital transformation of financial institutions (FIs) to remain an integral part of the financial system. This paradigm shift is not merely a technological update. Still, it signifies a cultural and operational rebirth, compelling FIs to embrace innovation, adaptability, and a customer-centric approach in the digital era. Independent of the business model, FIs must become digitally ambidextrous, offer tailored and dynamic customer experiences, support financial inclusion, and promote an environmental, social, and governance (ESG) agenda while leveraging data and remaining compliant. From digitalization to fintegration, the financial services industry's future is deemed to be an exciting and productive one.

This study aims to identify the status of virtual library system development in university libraries. It also attempted to examine the availability of virtual library services and reveal the challenges being faced by university librarians of Punjab province, Pakistan in providing virtual library services.

The study used a quantitative research method by using a questionnaire to address the study’s objectives. In total, 62 university libraries in Punjab province, Pakistan were the population of the study. A purposive sampling technique was applied to gather the required data from the respondents.

Results showed that most of the study’s respondents are well aware of the potential benefits of virtual library systems in universities for the delivery of innovative smart services to library patrons. The libraries delivered different virtual library services to meet the diverse needs of the library patrons. The respondents faced the challenges of funding, expertise, technical support, leadership, strategic planning and training to adopt virtual library systems and services in university libraries.

The study has provided a framework based on empirical findings of the study to efficiently adopt virtual library systems and services in university libraries for the delivery of smart services to end users. It has provided pertinent theoretical and practical implications.