Impact Of Artificial Intelligence Research Articles

The Impact of Artificial Intelligence on the Financial Sector

Abstract: Artificial Intelligence (AI) has revolutionized various sectors, with the financial industry being a prominent beneficiary. This review paper explores the multifaceted impact of AI on the financial sector, examining its influence on banking, investment management, fraud detection, customer service, and risk management. It highlights the transformative capabilities of AI technologies such as machine learning, natural language processing, and robotic process automation, while also addressing the associated challenges and future prospects

The Impact of Artificial Intelligence (AI) on Midwifery Education: A Scoping Review

The Impact of Artificial Intelligence (AI) on Midwifery Education: A Scoping Review

The Role and Impact of Artificial Intelligence on Project Management

Artificial intelligence (AI) has arisen as an extraordinary power in project management, changing customary practices and enlarging human capacities. This research investigates the diverse jobs played by (AI) artificial intelligence in project management and surveys its effect on project achievement rates. Through an extensive survey of writing and research of exact information, this study uncovers that artificial intelligence reception in project management has prompted a critical improvement in project achievement rates. Overall, artificial intelligence execution has brought about a wonderful increment of roughly 20% in project achievement rates across different businesses. Via mechanizing monotonous errands, upgrading asset allotment, and improving dynamic cycles, artificial intelligence has exhibited its capability to smooth out project work processes and moderate dangers. Nonetheless, close by its promising advantages, artificial intelligence execution presents difficulties, for example, information protection concerns, moral contemplations, and labor force reskilling necessities. This abstracts the basic significance of embracing artificial intelligence advancements in project management to accomplish higher proficiency, adequacy, and development. Looking forward, further research is expected to investigate arising patterns and address the developing difficulties in bridling artificial intelligence for project achievement.

The Impact of Artificial Intelligence on Microbial Diagnosis

Traditional microbial diagnostic methods face many obstacles such as sample handling, culture difficulties, misidentification, and delays in determining susceptibility. The advent of artificial intelligence (AI) has markedly transformed microbial diagnostics with rapid and precise analyses. Nonetheless, ethical considerations accompany AI adoption, necessitating measures to uphold patient privacy, mitigate biases, and ensure data integrity. This review examines conventional diagnostic hurdles, stressing the significance of standardized procedures in sample processing. It underscores AI’s significant impact, particularly through machine learning (ML), in microbial diagnostics. Recent progressions in AI, particularly ML methodologies, are explored, showcasing their influence on microbial categorization, comprehension of microorganism interactions, and augmentation of microscopy capabilities. This review furnishes a comprehensive evaluation of AI’s utility in microbial diagnostics, addressing both advantages and challenges. A few case studies including SARS-CoV-2, malaria, and mycobacteria serve to illustrate AI’s potential for swift and precise diagnosis. Utilization of convolutional neural networks (CNNs) in digital pathology, automated bacterial classification, and colony counting further underscores AI’s versatility. Additionally, AI improves antimicrobial susceptibility assessment and contributes to disease surveillance, outbreak forecasting, and real-time monitoring. Despite a few limitations, integration of AI in diagnostic microbiology presents robust solutions, user-friendly algorithms, and comprehensive training, promising paradigm-shifting advancements in healthcare.

Impact of Artificial Intelligence on Marketing strategies with reference to MNCs

Artificial intelligence (AI) is rapidly transforming the marketing landscape. This literature-based study explores the diverse applications of AI in marketing functions, drawing insights from academic journals, industry reports, and marketing publications. The study examines how AI personalizes marketing efforts through targeted advertising and content marketing, while also investigating its role in customer relationship management (CRM). It delves deeper into AI's influence on market research and marketing ROI (Return on Investment) optimization. By analyzing these applications, the study aims to provide a comprehensive understanding of how AI is shaping the future of marketing. Keywords: Artificial intelligence (AI), machine learning, customer segmentation, targeted advertising, content personalization, CRM, market research, marketing ROI, chatbots, recommendation engines, customer churn prediction.

The impact of artificial intelligence on academic work and research papers

This research seeks to present the production of academic and scientific papers using artificial intelligence for Chat GPT language modeling in different areas of higher education. To obtain the results, the quantitative approach was followed, the type of research is descriptive with a non-experimental design at the field level. The size of the population were the teachers of various careers at the Machala Metropolitan University. For the sample, a probabilistic sampling with simple random selection was used, calculating the sample size with a margin of error of 5% and a confidence level of 95%. The main results in the application of the instrument are, among others, the fact that none of the teachers could detect that the document they reviewed was created by artificial intelligence and they gave it an average score of 8.88/10 and that the platform anti plagiarism Compilatio also generated an average of 1% similarity, demonstrating that academic and research papers are currently indistinguishable from human-made work, neither in human review nor on anti-plagiarism platforms. plagiarism.

The Impact of Artificial Intelligence on Social Media

The Impact of Artificial Intelligence on Social Media

Artificial Intelligence Impact on Human Translation: Legal Texts as a Case Study

The recent paper highlights the impact of artificial intelligence on Machine Translation without the interaction of Humans. The use of Google Translator, Bing, Microsoft Translator, Systran Translate and Amazon Translate has become widely spread (CAT Tools). This study aims to reveal the contrast between Artificial Intelligence and Human Translation in the legal field. A hypothesis of the difference between Artificial Translation and Human Translation was raised. The concerns about the lack of a translator increased, and machine translation was selected as the most selected option. Local and foreign contracts were selected and subjected to Human and Machine translation. Strengths and weaknesses points were selected and analyzed. The previous studies in the legal translation field were considered. The results revealed the gap between human translation and machine translation, and human translation is dominant in the light of accuracy and the existence of legal language. The findings also focused on the Translators' experience and knowledge in the translation field.

The impact of Artificial Intelligence on E-commerce supply chain sector in achieving cost efficiency and economic growth: A business and economics perspective

The study aims to find how much cost effectiveness is achieved when e-commerce supply chain operations use automation and AI technologies. therefore,ing technology of AI and its models have essentially proved to be impactful in making data driven decisions by the organisations gaining leverage in productivity and profit sustainability in a way that the companies achieve competitive advantage therefore creating sustainable value propositions from business and economics perspective. Aim/Purpose The aim of the paper is to explore the positive relationship between AI technologies and productivity levels in the e-commerce supply chain sector through achieving cost effectiveness and economic growth. Methodology/Approach The study focussed on reviewing literature on how Artificial Intelligence driven technology can optimise various supply chain functions within e-commerce sector. Solow-Swan growth model has been applied to investigate the value AI creates in utilising capital, labour input to achieve output growth. Positivist approach that allowed for objective observation and independent conclusions has been adopted. For primary data, quantitative methodology is used through survey questionnaires to gather data from a sample of 206 employees, managers, data analysts in e-commerce supply chain sectors. Findings The findings from the secondary sources inform that the use of AI and automation in the e-commerce industry leads to a high rate of productivity in terms of reducing costs and promoting economic growth. The primary research methods, through survey questionnaires collects real-time data that helps achieve quantifiable and measurable values to conclude that AI-led technology can increase productivity and competitive advantage as it saves cost while increasing productivity and overall economic input. Descriptive statistics of measures of central tendency were used to present findings in simpler, presentable way followed by interpretations of the data in percentages. Practical implications Managers and decision-making directorial board members have important lessons to learn from these findings as the quantifiable values may give them an insight into how much capital investment should be allocated for AI technologies and how predictive analytics and data analysis can accelerate their service towards becoming customer centric. Significant strategic planning and implementation of resource management can lead to higher rates of productivity profitability and eventually higher economic growth.

Leveraging Artificial Intelligence for Crime Detection and Prevention

This paper sheds light on how Artificial Intelligence (AI) is reshaping the landscape of crime detection and prevention, bringing about a significant change in traditional law enforcement methods. With society increasingly embracing AI-driven solutions, it's crucial to understand how they contribute to public safety. We'll dive into various aspects of AI, such as predictive policing, video surveillance analysis, forensic science, and criminal profiling, to see how they enhance law enforcement capabilities and streamline crime resolution processes.Starting with predictive policing, AI algorithms sift through massive datasets to identify patterns and predict future criminal activity, empowering law enforcement to take proactive measures. Similarly, AI-powered video surveillance systems enhance real-time monitoring and anomaly detection, allowing for quick identification of suspicious behavior in urban environments.Moving on, we'll explore AI's impact on forensic analysis, where it expedites processes like DNA sequencing, fingerprint recognition, and ballistics analysis, speeding up the resolution of cold cases. Additionally, we'll delve into AI's role in criminal profiling, highlighting its ability to decipher behavioral patterns and predict criminal motivations, though ethical considerations remain paramount.We'll also address ethical concerns surrounding AI deployment in law enforcement, including privacy issues and algorithmic biases. Emphasizing the need for transparency and accountability, we advocate for responsible use of AI-powered crime detection systems to uphold ethical standards and protect individual rights.

The Transformative Role of Artificial Intelligence in Pharmaceutical Healthcare: A Comprehensive Review

Artificial Intelligence (AI) has emerged as a disruptive force in pharmaceutical healthcare, offering innovative solutions to complex challenges and driving transformative advancements across various domains. This comprehensive review explores the multifaceted applications of AI in pharmaceutical healthcare as well as research, drawing insights from a diverse range of literature sources. By synthesizing findings from relevant studies and research articles, this review elucidates AI's pivotal role in drug discovery, disease diagnosis, personalized treatment, clinical trials, healthcare management, and patient care. Through proper referencing from reputable sources, including PubMed, Science Direct, Google Scholar, and others, this review provides a thorough examination of AI's impact, challenges, and future directions in shaping the future of pharmaceutical healthcare.

Artificial intelligence – talent acquisition in HEIs recruitments

PurposeThe current research study aims to examine the application feasibility and impact of artificial intelligence (AI) among higher educational institutions (HEIs) in talent acquisitions (TA).Design/methodology/approachA systematic sampling method was adopted to collect the responses from the 385 staff working across the various levels of management in HEIs in metropolitan cities in India. JAMOVI & SmartPLS 4 were applied to validate the hypothesis by performing the simple percentage analysis and structural equation modelling. The demographic and construct variables considered were adoption, actual usage, perceived usefulness, perceived ease of use and talent management.FindingsThe key indicators of perceived usefulness are productivity, perceived ease of use, adaptability, candidate experience with the adoption of AI, frequency in decision-making in its actual usage and career path of development in the HEIs. These are the most influential items impacting the application of AI in TA.Originality/valueAI has the potential to revolutionize TA in HEIs in the form of enhanced efficiency, improved candidate experience, more objective hiring decisions, talent analytics and risk automation. However, they facilitate resume screening, candidate sourcing, applicant tracking, interviewing and predictive analytics for attrition.

Development and Validation of Instruments for Assessing the Impact of Artificial Intelligence on Students in Higher Education

<p style="text-align:justify">The role of artificial intelligence (AI) in education remains incompletely understood, demanding further evaluation and the creation of robust assessment tools. Despite previous attempts to measure AI's impact in education, existing studies have limitations. This research aimed to develop and validate an assessment instrument for gauging AI effects in higher education. Employing various analytical methods, including Exploratory Factor Analysis, Confirmatory Factor Analysis, and Rasch Analysis, the initial 70-item instrument covered seven constructs. Administered to 635 students at Nueva Ecija University of Science and Technology – Gabaldon campus, content validity was assessed using the Lawshe method. After eliminating 19 items through EFA and CFA, Rasch analysis confirmed the construct validity and led to the removal of three more items. The final 48-item instrument, categorized into learning experiences, academic performance, career guidance, motivation, self-reliance, social interactions, and AI dependency, emerged as a valid and reliable tool for assessing AI's impact on higher education, especially among college students.</p>

Impact of Artificial Intelligence on Indian Banking Sector- A Study of Banks

Artificial intelligence, or AI, is a cross-disciplinary approach to understanding, modeling, and creating intelligence of various forms. It is a critical branch of cognitive science, and its influence is increasingly being felt in other areas, including the humanities. Intelligence might be defined as the ability to learn and perform suitable techniques to solve problems and achieve goals, appropriate to the context in an uncertain, ever-varying world. A fully pre-programmed factory robot is flexible, accurate, and consistent but not intelligent. Artificial Intelligence (AI), a term coined by emeritus Stanford Professor John McCarthy in 1955, was define as “the science and engineering of making intelligent machines”. Much research has humans program machines to behave in a clever way, like playing chess, but, today, people emphasize machines that can learn, at least somewhat like human beings do. Autonomous systems can independently plan and decide sequences of steps to achieve a specified goal without micro-management. A hospital delivery robot must autonomously navigate busy corridors to succeed in its task. In AI, autonomy doesn’t have the sense of being self-governing common in politics or biology.

The impact of artificial intelligence on information audit usage: Evidence from developing countries

The present study aims to explore the factors influencing the utilization of Information audit in the context of Egypt and Jordan, with specific attention given to the role of artificial intelligence (AI). A sample of 443 respondents participated in the study, and data collection was carried out through a non-probability convenience and snowball sampling approach. The findings reveal that internal determinants are positively associated with the intention to adopt Information audit technologies, exhibiting a significant impact with a beta coefficient of +0.45 (P-value < 0.01), and the perceived benefits associated with their implementation. Moreover, the study underscores the critical influence of artificial intelligence, with dimensions such as cloud computing, data mining, and e-commerce enhancing the perceived advantages (β = 0.35, P-value < 0.01) and fostering the intent to use Information audit technologies (β = 0.22, P-value < 0.01). Additionally, there is a robust positive correlation between the intention to use Information audit technologies and their actual usage, where the presence of AI amplifies this association, indicated by a beta value of 0.48 (P-value < 0.01). This study significantly enriches the existing body of knowledge by delineating the determinants of Information audit usage, particularly within the Middle Eastern context, and highlights the pivotal role of artificial intelligence in shaping these dynamics. The study provides empirical evidence on the factors influencing the intention to use Information audit technologies, the perceived benefits associated with their usage, and the actual utilization of Information audit. Its originality lies in its focus on the underexplored Middle East region within the Information audit literature and its investigation of the influence of artificial intelligence on Information audit. The implications of this study are significant for practitioners, auditors, and policymakers operating within the Middle East region. The findings suggest that firms should allocate sufficient support and resources to encourage the adoption of Information audit technologies. Additionally, auditors need to have the necessary skills and knowledge to effectively use these technologies. Policymakers can use the study's findings to develop policies and regulations that promote the adoption of Information audit technologies.

The Impact of Artificial Intelligence in Employee Onboarding Programs

Problem Employee onboarding is one of the most important phases of an employee’s life cycle. Human resources (HR) is vital in setting employees up for success, particularly during this employment stage. Some organizations lose employees before they have had a chance to learn about and acclimate to the organization. An ineffective onboarding program may contribute to high turnover costs and low employee retention. Solution This article discusses emerging trends in the role of artificial intelligence (AI) in human resource development (HRD) and how AI is being used to develop more effective and efficient processes and programs. Recommendations for practitioners will include how AI may create an informative and engaging onboarding program that may increase employee retention. Stakeholders Organizational development (OD) and learning and development (LD) professionals who want a more effective employee onboarding program that will provide the knowledge employees need while creating an engaging learning experience.

In the Echoes of Tomorrow: The Intersection of Social Work and Artificial Intelligence Through the Eyes of Turkish Students

This study aimed to examine social work students’ perspectives on the impact of artificial intelligence (AI) on social work. This research was prepared with a qualitative design to explore the reflections of social work students in Türkiye and twelve focus groups were conducted. The data were analyzed using MAXQDA, and two main themes were created: opportunities and challenges. The opportunities include innovation, transformative dimensions, and work optimization, while challenges consist of competency for professional practice, ethical issues, and labor sub-themes. The results indicate that students think that AI will increase efficiency in terms of gaining speed and time, reducing bureaucracy, performing risk analysis, and reducing costs. In the research findings, students point out that AI may lead to ethical violations in terms of privacy concerns, the possibility of data misuse, etc. Students emphasize the risk of increased unemployment with the integration of AI into social work. Future research could investigate the long-term impact of integrating AI into social work practice, examining its evolving effect on client outcomes and professional roles.

AI-Driven Cybersecurity: Balancing Advancements and Safeguards

As Artificial Intelligence (AI) continues its rapid evolution, its profound influence on cybersecurity becomes increasingly evident. This study delves into the pivotal role of AI in fortifying cybersecurity measures, emphasizing its capacity for enhanced threat detection, automated response mechanisms, and the development of resilient security frameworks. However, alongside its promise, recognition of AI's susceptibility to exploitation in sophisticated cyber-attacks exists, underscoring the imperative for continual advancements in AI-driven security solutions. This research offers a nuanced perspective on AI's impact on cybersecurity, advocating for the proactive integration of AI strategies, sustained research efforts, and formulating ethical guidelines. Adopting supervised machine learning (ML) algorithms like decision trees, support vector machines, and neural networks aims to harness AI's potential to bolster cybersecurity while concurrently addressing associated risks, paving the way for a secure digital landscape. Regarding accuracy, the neural network outperforms other models by 98%.

Knowledge, attitudes, and perceptions of healthcare students and professionals on the use of artificial intelligence in healthcare in Pakistan.

The advent of artificial intelligence (AI) technologies has emerged as a promising solution to enhance healthcare efficiency and improve patient outcomes. The objective of this study is to analyse the knowledge, attitudes, and perceptions of healthcare professionals in Pakistan about AI in healthcare. We conducted a cross-sectional study using a questionnaire distributed via Google Forms. This was distributed to healthcare professionals (e.g., doctors, nurses, medical students, and allied healthcare workers) working or studying in Pakistan. Consent was taken from all participants before initiating the questionnaire. The questions were related to participant demographics, basic understanding of AI, AI in education and practice, AI applications in healthcare systems, AI's impact on healthcare professions and the socio-ethical consequences of the use of AI. We analyzed the data using Statistical Package for Social Sciences (SPSS) statistical software, version 26.0. Overall, 616 individuals responded to the survey while n = 610 (99.0%) of respondents consented to participate. The mean age of participants was 32.2 ± 12.5 years. Most of the participants (78.7%, n = 480) had never received any formal sessions or training in AI during their studies/employment. A majority of participants, 70.3% (n = 429), believed that AI would raise more ethical challenges in healthcare. In all, 66.4% (n = 405) of participants believed that AI should be taught at the undergraduate level. The survey suggests that there is insufficient training about AI in healthcare in Pakistan despite the interest of many in this area. Future work in developing a tailored curriculum regarding AI in healthcare will help bridge the gap between the interest in use of AI and training.

The Impact of Artificial Intelligence on Job Loss: Risks for Governments

The rapid advancement of Artificial Intelligence (AI) technologies presents both opportunities and challenges for labor markets globally. By adopting a qualitative methodology, this study analyses the impact of AI integration in jobs on the labor market and the subsequent policy responses by governments. The study specifies the industries and jobs that are highly susceptible to AI-driven automation, particularly those characterized by routine and repetitive tasks. The study also acknowledges the potential for AI to create new job categories. Key findings suggest that while AI poses a significant risk of job displacement in several sectors, it also offers opportunities for economic growth, opening of new jobs and innovation. Moreover, the study highlights various government strategies employed globally, including up-skilling and re-skilling initiatives, strengthening social protection systems, and fostering AI-human collaboration. These strategies aim to mitigate the adverse impacts of AI on employment and ensure a balanced transition to AI-integrated economies. Based on these strategies, the paper suggests some recommendations for governments to address AI-driven job losses, emphasizing the importance of multidisciplinary education, ethical AI use, inclusive growth strategies, and international cooperation.