University of Delhi

Short-Duration

Certificate Course Certificate Programme in Applied FinTech & Artificial Intelligence (AFAI)

Build • Analyse • Automate • Innovate

The convergence of finance, Artificial Intelligence, and digital public infrastructure is transforming financial services worldwide, and India sits at the centre of this shift. In May 2026, the Unified Payments Interface (UPI) processed a record 23.2 billion transactions worth approximately ₹29.9 lakh crore in a single month (NPCI), and UPI now accounts for roughly 85% of India’s retail digital payments. India represents close to half of global real-time payment volumes, and the IMF has recognised UPI as the world’s largest real-time payment system by transaction volume. India also ranks third globally in fintech market activity and funding (Global Fintech Index).

As a global FinTech leader, India requires future-ready professionals with practical expertise in digital finance, AI applications, data analytics, and technology-enabled financial innovation. Although students possess strong theoretical foundations in finance and management, a substantial gap persists between academic curricula and the rapidly evolving, AI-era skill requirements of the financial services industry. This programme is designed to close that gap.

Vision:

To develop future-ready finance professionals capable of leveraging Artificial Intelligence and emerging financial technologies to create innovative, ethical, and sustainable financial solutions.

 Mission:

• To provide experiential learning in FinTech and AI.

• To bridge the gap between academic learning and industry expectations.

• To promote innovation and entrepreneurship.

• To develop globally competitive financial professionals.

Objectives:

The programme seeks to:

• Develop a comprehensive understanding of the contemporary FinTech ecosystem.

• Equip learners with practical knowledge of digital financial technologies.

• Introduce AI applications — discriminative, generative and agentic — in financial services.

• Develop analytical and problem-solving skills using modern analytics and visualisation tools.

• Familiarise participants with digital payments and banking technologies.

• Enable learners to understand blockchain, digital assets and tokenisation.

• Promote responsible AI and ethical financial innovation.

• Encourage FinTech entrepreneurship and develop industry-ready professionals.

Career Opportunities: 

Participants can pursue roles across: digital banking; payments & transaction banking; FinTech product & business analysis; wealth management & WealthTech; credit & risk analytics; digital lending; InsurTech; financial data analytics; RegTech & compliance; product management; AI-enabled financial services; and FinTech entrepreneurship.

Programme Highlights: 

• Industry-oriented curriculum with hands-on practical sessions and live case studies.

• AI-enabled finance applications, including a generative & agentic AI lab.

• Industry experts as guest faculty; financial analytics laboratories.

• Capstone project culminating in a Demo Day before an industry jury.

• Incubation / start-up mentoring at SIIF; internship assistance.

• Portfolio development and certificate upon successful completion.

Target Participants, Eligibility & Admission:

Target participants: Undergraduate & postgraduate students (any discipline), research scholars, young professionals, and working executives.

Eligibility: Open to the above categories. No prior AI or programming knowledge is required; basic familiarity with Excel and general awareness of financial services are recommended. Participants must bring their own laptop for classes and practice.

Admission process: Online application with a brief statement of purpose. Seats are offered on a firstcome basis subject to screening; if applications exceed capacity, selection will be based on the statement of purpose and profile diversity (balancing finance-background and technology-background learners).

Intake: Target batch of 40 participants (minimum 25 to commence a batch).

Resource Persons:

Sessions will be delivered by academicians, industry professionals, FinTech practitioners, promoters and venture capitalists, and representatives of regulatory and professional bodies.

Programme Governance & Quality Assurance:

• Course Coordinator: Prof. Kumar Bijoy, responsible for academic delivery, scheduling and coordination.

• Programme Advisory Committee: Two to three SSCBS faculty members and at least two industry members, advising on curriculum currency and industry linkages.

• Feedback mechanism: Structured participant feedback at mid-course and end-course; batchwise review of results and feedback.

• Curriculum refresh: Given the pace of change in AI, Module 4 and the tools list are reviewed and refreshed before every batch; a batch report is submitted to the college after each cycle.

Fee Structure & Financial Plan Proposed fee (per participant):

Category Fee (₹) Students & Alumni of SSCBS 22,000 Students & research scholars (Any College/University) 25,000 Working professionals/executives Taxes will be additional, if applicable, as per prevailing rules. 30,000

Contact Us for any query:

Prof. Kumar Bijoy

kumarbijoy@sscbsdu.ac.in

+91-9810452266

Registration Link: 

https://docs.google.com/forms/d/e/1FAIpQLSfPXF9SPiZgs1xbwI0wl-DWT1bDqwlx7YRr6g45m-2Z9_Jmw/viewform?usp=dialog

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A key development is the increasing prevalence of human and AI collaboration in which outputs are produced together through interactions between individuals and AI systems. This implies, to some degree, augmented integration, or a form of collaboration in which humans and AI systems jointly complete tasks (Raisch and Krakowski, 2021). However, such integration creates a fundamental challenge: when work is augmented by GenAI, it becomes difficult to attribute outcomes to human effort versus AI contributions. As a result, long-standing assumptions about productivity (e.g., how it is defined, measured, and compared) require reconsideration.

List of Topic Areas

• Conceptualizing productivity in AI work and careers
• Distinguishing between AI exposure, use, and augmentation
• Measuring human versus AI contributions to outputs and performance
• Changes in the distribution of performance (e.g., effects on high and lower performers)
• Implications of GenAI for skill development, career trajectories, and employability
• The role of HR practices, job design, and organizational context in shaping productivity related to AI
• Methodological approaches to studying AI and work (e.g., multi-source data, longitudinal designs, behavioral, other types of data)

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available at: https://mc.manuscriptcentral.com/prev

Author guidelines must be strictly followed. Please see: https://www.emeraldgrouppublishing.com/journal/pr

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q1, H-Index 104

Key Deadlines

Opening date for manuscripts submissions: 31/08/2026

Closing date for manuscripts submission: 31/01/2027

Email for submissions: Tony Fang, Canada, tfang@mun.ca

For more details refer here

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Events have long been associated with urban environments, celebrated for their regenerative potential and embedded within complex cultural and economic networks (Betz, Hitzler, & Pfadenhauer, 2011; Smith, Osborn, & Quinn, 2022). In contrast, rural events remain underexplored in event studies (Li, 2021), despite being recognised as a “critical aspect of rural experiences” (Richards et al. 2025: 771). When regarding the literature on rural, remote, peripheral or insular events (referred to further as rural events for purposes of simplicity), it is worth noting that studies investigating rural events are unlikely to question the rurality of the event. With exceptions of some interesting publications such as Browne (2011), George (2015) Fountain and Mackay (2017), Kwiatkowski et al. (2020), the rural is often used as a geographical denominator or description of a living condition. Guided by the cited authors’ interest in “place identity” (George, 2015), “sense of place” (Fountain & Mackay, 2017) or wider rural associations (Browne, 2011; Kwiatkowski et al., 2020), this call for papers is driven by the ambition to challenge conceptions of rural events beyond rural stigmatisations in order to explore how the rural is characterised, defined, discussed, challenged through events.

This special issue aims to advance critical understandings of rural events and festivals by moving beyond their treatment as merely geographically bounded phenomena to critically examine how rurality itself is constructed, negotiated, performed, and contested through event and festival spaces. This special issue seeks to reconceptualise rurality as a socially, culturally, and politically constructed and contested category, shaped through events and their associated practices. Addressing the persistent urban bias in event studies, the issue invites contributions that examine how rural events produce, negotiate, and challenge meanings of place, identity, and community.

Driven by research perspectives centring on event-based development, revitalisation and regeneration, research on rural events has long been shaped by deficit-based and often stigmatising narratives, dominated by selected topics, which reflect certain stigmatised or stereotypical conceptions of the rural. Hereby, the ‘lack of …’ takes prominence in the discussion (Frost & Laing, 2015; Ðurkin & Wise, 2017). Often in a comparative perspective with urban or other rural settings, rural events are studied in regard to their lack of infrastructure, management structures, funding and professionalisation (Koreman, 2023, Qu & Zollet, 2023, Gamble, 2022, Porfido, 2022). Such framings risk reproducing simplistic stereotypes of rurality and obscuring the diverse forms of agency, resilience, and innovation that rural communities demonstrate.

Next to such ‘lacking’ perspectives, the relevance of rural events as a form of social, cultural and political infrastructure is widely discussed. With attention to community perspectives, rural events are championed as key fabrics of rural living and hereby considered to be a necessary institution to keep rural community vital (Chiya, 2024; Dalla Torre et al., 2025; Lee, et al., 2024). Furthermore, the political, strategic interest in events in rural settings for touristic purposes increasingly raises interests in scholarly debate. Events based on local culture, identity, and heritage are discussed as powerful “pull factors,” drawing tourists to remote, peripheral, or insular destinations. By doing so, they are assumed to not only generate direct revenue and economic impact, but also play a critical role in place identity transforming the rural setting into a distinctive and authentic cultural experience. Henceforth, rural events are embedded in wider tourism geographies, shaping and being shaped by flows of visitors, mobility patterns, place marketing, and destination planning and development (Quan-Baffour, 2023; Mair & Duffy, 2021; Eversole & Martin, 2005).

List of Topic Areas

We welcome contributions that offer theoretical advancements, empirical research, case studies, and critical commentary on, but not limited to, the following themes in the context of rural events and festivals:

• Rural events as catalysts for social inclusion/exclusion.
• Rural events as sites for intergenerational exchange.
• Events as a marker of belonging and revitalisation of rural locations.
• Rural events as a mechanism for reclaiming or resisting urban dominance.
• The symbolic and material role of events in sustaining local distinctiveness and reimagining place identity.
• Rural events and the negotiation of social change (e.g. tourism mobilities, migration and demographic shifts).
• Power dynamics between local actors and external stakeholders.
• Indigenous and traditional events as sites of cultural continuity and contestation.
• Methodological and theoretical innovations on researching “with” rural communities rather “on” rural communities.
• The role of rural events in shaping people, place and the geographies of rural life.
• Philosophical and ethical dilemmas with rural festivals and events.

Guest Editors

Dr Barbara Grabher, University of Brighton, UK, B.Grabher@brighton.ac.uk

Dr Willem Coetzee, Western Sydney University, Australia, w.coetzee@westernsydney.edu.au

Dr Vasiliki Georgoula,  University of the Aegean, Greece, v.georgoula@aegean.gr

Submissions Information

Submissions are made using ScholarOne Manuscripts. Author guidelines must be strictly followed.

Submit via ScholarOne

Author Guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q2, H-Index 41

Key Deadlines

Opening date for manuscripts submissions: 30th October 2026

Closing date for manuscripts submission: 14th February 2027

Closing date for abstract submission: 30th September 2026

Email for submissions: B.Grabher@brighton.ac.uk

For more details refer here

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This special issue focuses on how agentic artificial intelligence reshapes entrepreneurship across the main stages of the entrepreneurial process, including opportunity recognition, venture creation, business model development, scaling, growth, internationalisation, and exit. Agentic AI is different from earlier forms of digital technology because it can perceive context, plan tasks, use tools, coordinate actions, and learn from feedback with limited human supervision (Dwivedi et al., 2026; Islam et al., 2026). Therefore, it does not only support entrepreneurs as a passive technology. It may also become an active co-agent in entrepreneurial decision-making and venture development. The debate on agentic AI and entrepreneurship is still emerging. Previous studies have shown that AI and big data are transforming entrepreneurship by influencing opportunity recognition, entrepreneurial decision-making, innovation, and venture performance (Obschonka & Audretsch, 2020; Shepherd & Majchrzak, 2022; Giuggioli & Pellegrini, 2023). More recent studies have started to explain how agentic AI, generative AI, and meta-entrepreneurship may create new forms of entrepreneurial action, co-agency, and ecosystem transformation (Al-Bashrawi et al., 2026; Elgendy et al., 2025; Zhang & Siau, 2024).

On the bright side, agentic AI may support entrepreneurs by improving opportunity recognition, market analysis, customer discovery, resource mobilisation, financial planning, product development, and strategic decision-making. It may also reduce information gaps, support small firms with limited resources, and enable new forms of AI-native ventures. In this view, agentic AI can strengthen entrepreneurial capability and allow entrepreneurs to act faster and more effectively in uncertain markets (Al-Bashrawi et al., 2026; Lambert et al., 2026). However, the dark side of agentic AI is equally important. Agentic AI may create overdependence on automated systems, weaken entrepreneurial judgment, increase algorithmic bias, raise accountability problems, and produce new forms of digital inequality between entrepreneurs who can access advanced AI systems and those who cannot. It may also affect entrepreneurial identity, creativity, autonomy, and ethical responsibility. In addition, the use of autonomous AI agents in venture creation and scaling may create new governance problems related to data privacy, transparency, trust, and responsibility for AI-driven decisions (Shepherd & Majchrzak, 2022; Mariani & Dwivedi, 2024; Ojong, 2025).

This special issue therefore aims to advance the debate by examining both the bright and dark sides of agentic AI in entrepreneurship. It welcomes studies that explain when agentic AI enables entrepreneurial value creation and when it creates new risks, tensions, and unintended consequences. The special issue also encourages theoretical development by connecting agentic AI with entrepreneurship theories such as entrepreneurial agency, opportunity creation and discovery, effectuation, resource orchestration, dynamic capabilities, institutional theory, entrepreneurial cognition, and entrepreneurial ecosystems. Although the journal has a clear interest in emerging economies, the special issue will not be limited only to these contexts. It welcomes papers from emerging economies, advanced economies, and comparative settings. This broader scope is important because research on agentic AI and entrepreneurship is still at an early stage. Comparative studies can show how institutional conditions, digital infrastructure, regulation, entrepreneurial ecosystems, and market maturity shape the adoption and consequences of agentic AI (Islam et al., 2026; Lambert et al., 2026). Sustainability, social innovation, and inclusive entrepreneurship may also be addressed, but as specific contexts rather than the central focus of the special issue (Duong, 2025; Ojong, 2025).

List of Topic Areas

• Agentic AI and opportunity recognition in entrepreneurship.
• Agentic AI and entrepreneurial decision-making under uncertainty.
• Human-AI co-agency and entrepreneurial judgment.
• Agentic AI and new venture creation.
• AI-native startups and autonomous venture development.
• Agentic AI and business model innovation.
• Agentic AI and venture scaling, growth, and internationalisation.
• Agentic AI and entrepreneurial exit decisions.
• The bright side of agentic AI in entrepreneurship, including speed, efficiency, creativity, resource mobilisation, and market intelligence.
• The dark side of agentic AI in entrepreneurship, including bias, dependency, loss of autonomy, accountability problems, digital inequality, and ethical risks.
• Agentic AI and entrepreneurial cognition, identity, and creativity.
• Trust, resistance, and adoption of agentic AI among entrepreneurs and SMEs.
• Agentic AI and entrepreneurial ecosystems.
• Agentic AI in emerging economies and resource-constrained contexts.
• Comparative studies of agentic AI and entrepreneurship across emerging and advanced econmies.
• Agentic AI in sustainable entrepreneurship, social innovation, and inclusive entrepreneurship.
• Governance, regulation, and responsible use of agentic AI in entrepreneurial settings.
• Methodological approaches for studying agentic AI and entrepreneurship, including experiments, longitudinal studies, qualitative research, mixed methods, fsQCA, SEM, ANN, and digital trace data.

Submission Information

Submissions of full manuscripts are made using ScholarOne Manuscripts. Registration and access are available here:

Submit via ScholarOne

Author guidelines must be strictly followed. Please see:

Author guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q1, H-Index 47

Key Dates

Opening date for manuscript submissions: 1 September 2026

Closing date for manuscript submissions: 1 December 2026

For more details refer here

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The proposed special issue seeks to promote research that examines communication phenomena at scale, tests causal relationships, measures the prevalence and impact of communication strategies, and generates findings that are replicable across organizational and national contexts. By bringing together studies that employ quantitative surveys, experiments, computational text analysis, longitudinal datasets and network analysis our issue aims to strengthen methodological diversity in the field while fostering greater integration between academic inquiry and the rich data resources increasingly available in professional practice. On this basis, the special issue seeks to build a more cumulative, evidence-based understanding of corporate communications and its effects on organizations and stakeholders.

Corporate communications research has built much of its impact traditionally through qualitative and interpretive traditions. This work has shaped how we understand, among others legitimacy, meaning-making, and stakeholder sense-making, and the field’s recent articles reflect its continued vitality, including work that the determinants of practitioners’ acceptance of artificial intelligence in corporate communications (Kelm and Johan, 2025). What this tradition gives us less information on, are questions of scale, prevalence, and cause. We rarely know how widespread a pattern documented in a single setting actually is across firms, sectors, or countries. We rarely test whether a communication strategy produces a stakeholder outcome rather than merely co-occurring with it. And because qualitative findings are difficult to generalize, compare or ‘pool’ across studies, the field accumulates insights much more slowly than other fields in business management and marketing. Indeed, adjacent disciplines have moved further on this front. Management scholarship has shown how topic modelling and large-scale text analysis can render new constructs and build theory from textual data rather than reducing it to a black box (Hannigan et al., 2019), and communication methodologists have begun mapping where computational text analysis succeeds and where its validity remains uncertain (Baden et al., 2022). Corporate communications, by comparison, has been slower to take up these methods at scale, even as the raw material for doing so has multiplied.

That raw material increasingly comes from practice. Organisations and their advisers now generate vast quantities of data about exactly the questions our field cares about: media monitoring and social listening platforms track user sentiment and share of voice in real time; brand tracking and reputation indices follow stakeholder perceptions longitudinally; employee engagement and internal communications analytics capture workforce response at scale, including during the disruptive episodes the field has long studied qualitatively (Park et al., 2025); and social, web, and behavioural trace data offer granular evidence of how stakeholders actually respond to corporate messaging (Zhao et al., 2024). Much of this practitioner-generated data rarely reaches academic journals, and much of the computational toolkit now standard in marketing, strategy, and information systems remains underused in our own field. This special issue makes the case that quantitative, computational, and practitioner-sourced data are not a narrower or more reductive way of studying corporate communications but a necessary complement to interpretive work, able to answer questions interpretive designs are not built to answer.

List of Topic Areas

• Survey-based and experimental studies in corporate communications research
• The use of big data in corporate communications
• Measurement and scale development for core corporate communication constructs
• Text analysis approaches such as NLP, sentiment analysis or topic modelling, applied to corporate communication
• Large-scale content analysis of annual reports, for example of CSR and ESG disclosures or press releases
• Longitudinal and panel data studies tracking communication effects over time
• Network analysis of information flow
• Cross-national and comparative quantitative studies of corporate communication practice
• The use of practitioner and commercially generated data such as media monitoring and listening data, employee engagement analytics or market research results in corporate communications

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available at: https://mc.manuscriptcentral.com/ccij?_gl

Author guidelines must be strictly followed. Please see: https://www.emeraldgrouppublishing.com/journal/ccij

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines

Opening date for manuscripts submissions: 31/12/2026

Closing date for manuscripts submission: 31/03/2027

For more details refer here

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The construction engineering and management sector is entering a new phase of digital transformation driven by rapid advances in artificial intelligence, large language models (LLMs), multimodal foundation models, and agentic decision-support systems. Construction projects generate vast amounts of fragmented textual, numerical, visual, and procedural information, including contracts, specifications, safety reports, cost records, schedules, inspection logs, regulatory documents, BIM data, financial disclosures, and sustainability reports. However, much of this information remains underused because it is dispersed across project stages, organisations, platforms, and professional domains.

LLMs create new opportunities to transform fragmented construction information into actionable knowledge. Unlike conventional machine learning approaches that mainly focus on prediction, classification, or optimisation, LLMs offer capabilities in natural language reasoning, semantic retrieval, document intelligence, knowledge synthesis, human-AI interaction, and decision support. These capabilities are particularly relevant to construction engineering and management, where many critical decisions depend on interpreting complex documents, coordinating multiple stakeholders, understanding regulatory and contractual requirements, identifying risks, and converting past project knowledge into practical guidance.

Despite their potential, the application of LLMs in construction engineering and management remains at an early stage. Existing studies have begun to explore LLMs for safety report analysis, project information retrieval, planning support, contract interpretation, design coordination, and infrastructure data enrichment. However, substantial research gaps remain in domain adaptation, benchmark development, hallucination control, explainability, privacy protection, multimodal integration, responsible implementation, and validation in real construction environments. There is also a need to move beyond general demonstrations of LLM capability and examine how these models can be embedded into construction workflows to support reliable, accountable, and value-adding decision-making.

This Special Issue aims to provide a focused international forum for research on LLMs for construction engineering and management, with particular attention to knowledge, risk, and decision intelligence in the built environment. It welcomes theoretical, methodological, empirical, review, case-based, and policy-oriented contributions that investigate how LLMs can support construction safety and health management, cost and schedule control, contracts and dispute resolution, construction finance and organisational resilience, BIM and digital twins, lifecycle knowledge management, sustainability, circular economy, and SDG implementation.

By bringing together cutting-edge research from construction management, civil engineering, artificial intelligence, informatics, design, and sustainability, this Special Issue seeks to advance both scholarly understanding and practical implementation of LLM-enabled construction intelligence. Collectively, the contributions are expected to clarify the opportunities, limitations, governance requirements, and real-world impacts of LLMs, while offering evidence-based insights for researchers, practitioners, policymakers, and technology developers working toward safer, more efficient, resilient, and sustainable built environments.

List of Topic Areas

• LLMs for construction safety and health management, including accident report analysis, near-miss mining, hazard identification, safety knowledge extraction, safety training, and safety regulation interpretation.
• LLMs for construction cost, schedule, and project performance control, including cost estimate review, cost overrun diagnosis, schedule delay analysis, progress report summarization, productivity assessment, and early warning of project performance risks.
• LLMs for construction contracts, claims, and dispute resolution, including contract clause interpretation, change order analysis, claim document review, delay claim reasoning, dispute case retrieval, regulatory compliance checking, and risk allocation analysis.
• LLMs for construction finance, credit risk, and organizational resilience, including financial disclosure analysis, contractor credit scoring, insolvency risk identification, market risk monitoring, green finance evaluation, and construction firm resilience assessment.
• LLMs for BIM, digital twins, and lifecycle knowledge management, including natural language querying of BIM models, automated rule checking, project document retrieval, digital twin interaction, knowledge graph construction, design coordination support, and lifecycle information management.
• LLMs for sustainability, circular economy, and SDG implementation in construction, including lifecycle assessment support, sustainable procurement analysis, material reuse and waste reduction, carbon documentation, circular design knowledge retrieval, and decision support for accelerating progress toward the 2030 SDG agenda.

Submission Information

Submissions of full manuscripts are made using ScholarOne Manuscripts. Registration and access are available here:

Submit via ScholarOne

Author guidelines must be strictly followed. Please see:

Author guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q1, H-Index 47

Key Dates

Opening date for manuscript submissions: 1 August 2026

Closing date for abstract submissions: 31 December 2026

For more details refer here

brochure

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Artificial intelligence (AI) is transforming the foundations of accounting, finance, and work by reshaping how organizations generate information, make decisions, allocate resources, and manage human capital. Advances in generative AI, machine learning, and automation create unprecedented opportunities for innovation and productivity, while also introducing critical challenges related to governance, accountability, ethics, and workforce transformation.

The impact of AI extends beyond task automation. It is redefining financial reporting, auditing, investment decisions, risk management, organizational design, and the relationship between firms and employees. As AI adoption accelerates, important questions emerge regarding job redesign, skill development, labor inequality, responsible technology use, and the role of organizations in ensuring a fair and sustainable transition.

This Special Issue, “Beyond Automation: Artificial Intelligence, Accounting, Finance, and the Future of Work,” seeks to advance interdisciplinary research on how AI is reshaping organizations, financial systems, and labor markets. It welcomes studies examining AI-driven innovation, financial decision-making, corporate governance, human capital, responsible AI, sustainability, and contemporary labor challenges.

By bringing together insights from accounting, finance, and related disciplines, this Special Issue aims to deepen understanding of how AI can be leveraged to create value while addressing the economic and societal implications of the future of work.

List of Topic Areas

Submissions may address, but are not limited to, the following topics:

• Artificial intelligence in accounting and corporate finance
• AI-enabled financial reporting and disclosures
• AI and corporate investment decisions
• AI, corporate governance, and organizational accountability
• AI, labor markets, employment, and job redesign
• Wage inequality, labor exploitation, and worker well-being in the AI era
• AI, diversity, equity, inclusion, and workplace fairness
• Public policy, AI regulation, and labor related governance issues
• The societal implications of AI for accounting, finance, and the future of work

Guest Editor

Dr. Mohammed Aminu Sualihu, Zayed University, United Arab Emirates, mohammed.sualihu@zu.ac.ae

Submissions Information

Submissions are made using ScholarOne Manuscripts. Author guidelines must be strictly followed.

Submit via ScholarOne

Author Guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Journal Information: Scopus Journal Q2, H-Index 47

Key Deadlines

Opening date for manuscripts submissions: 30th November 2026

Closing date for manuscripts submission: 31st March 2027

For more details refer here

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