Artificial Intelligence (AI) offers immediate insights to penetrate the overwhelming volume of everyday security warnings. The current body of research mostly examines the use of AI in the field of cyber security, but it does not adequately address the visual inspection of AI applications. The advent of AI has led to noticeable structural changes in the field of cyber security. This study facilitates the advancement of theory about artificial intelligence (AI) across several fields. It assists researchers in determining research paths and serves as a resource for corporations and governments to strategize the use of AI in areas such as cyber security, education, healthcare, and work-life balance. Numerous nations, organizations, and writers are intricately linked via cooperation and citation networks. Artificial intelligence is an academic discipline focused on the research and advancement of computer systems, robots, and other creations that possess human-like intelligence, which is defined by cognitive powers, learning capabilities, and adaptability. This research aimed to evaluate the present trajectory and influence of Artificial Intelligence (AI) on education, healthcare, cybersecurity, and work-life balance. Based on an initial examination, this research focused on evaluating the use and impact of AI in many domains, using a specific narrative and framework. The findings of this study will enable researchers to comprehend the prevailing pattern and the influence of people on the integration of AI into daily life.
References
[1]
Guzman, A.L. (2018) Beyond Extraordinary: Theorizing Artificial Intelligence and the Self in Daily Life. In: Papacharissi, Z., Ed., A Networked Self and Human Augmentics, Artificial Intelligence, Sentience, Routledge, 83-96. https://doi.org/10.4324/9781315202082-7
[2]
De Falco, I., De Pietro, G. and Sannino, G. (2019) Evaluation of Artificial Intelligence Techniques for the Classification of Different Activities of Daily Living and Falls. Neural Computing and Applications, 32, 747-758. https://doi.org/10.1007/s00521-018-03973-1
[3]
Rana, M.J., Hasan, M.R. and Sobuz, M.H.R. (2021) An Investigation on the Impact of Shading Devices on Energy Consumption of Commercial Buildings in the Contexts of Subtropical Climate. Smart and Sustainable Built Environment, 11, 661-691. https://doi.org/10.1108/sasbe-09-2020-0131
[4]
Rana, M.J., Hasan, M.R., Sobuz, M.H.R. and Sutan, N.M. (2020) Evaluation of Passive Design Strategies to Achieve NZEB in the Corporate Facilities: The Context of Bangladeshi Subtropical Monsoon Climate. International Journal of Building Pathology and Adaptation, 39, 619-654. https://doi.org/10.1108/ijbpa-05-2020-0037
[5]
Hasan, R., Al Mahmud, A., Farabi, S.F., Akter, J. and Johora, F.T. (2024) Unsheltered: Navigating California’s Homelessness Crisis. Sociology Study, 14, 143-156. https://doi.org/10.17265/2159-5526/2024.03.002
[6]
Akid, A.S.M., Shah, S.M.A., Sobuz, M.D.H.R., Tam, V.W.Y. and Anik, S.H. (2021) Combined Influence of Waste Steel Fibre and Fly Ash on Rheological and Mechanical Performance of Fibre-Reinforced Concrete. Australian Journal of Civil Engineering, 19, 208-224. https://doi.org/10.1080/14488353.2020.1857927
[7]
Meraz, M.M., Mim, N.J., Mehedi, M.T., Bhattacharya, B., Aftab, M.R., Billah, M.M., et al. (2023) Self-Healing Concrete: Fabrication, Advancement, and Effectiveness for Long-Term Integrity of Concrete Infrastructures. Alexandria Engineering Journal, 73, 665-694. https://doi.org/10.1016/j.aej.2023.05.008
[8]
Akid, A.S.M., Wasiew, Q.A., Sobuz, M.H.R., Rahman, T. and Tam, V.W. (2020) Flexural Behavior of Corroded Reinforced Concrete Beam Strengthened with Jute Fiber Reinforced Polymer. Advances in Structural Engineering, 24, 1269-1282. https://doi.org/10.1177/1369433220974783
[9]
Jakšič, M. and Marinč, M. (2018) Relationship Banking and Information Technology: The Role of Artificial Intelligence and Fintech. Risk Management, 21, 1-18. https://doi.org/10.1057/s41283-018-0039-y
[10]
Saha, S., Ghimire, A., Manik, M.M.T.G., Tiwari, A. and Imran, M.A.U. (2024) Exploring Benefits, Overcoming Challenges, and Shaping Future Trends of Artificial Intelligence Application in Agricultural Industry. The American Journal of Agriculture and Biomedical Engineering, 6, 11-27. https://doi.org/10.37547/tajabe/volume06issue07-03
[11]
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V. and Biancone, P. (2021) The Role of Artificial Intelligence in Healthcare: A Structured Literature Review. BMC Medical Informatics and Decision Making, 21, Article No. 125. https://doi.org/10.1186/s12911-021-01488-9
[12]
Mohammad, N., Imran, M.A.U., Prabha, M., Sharmin, S. and Khatoon, R. (2024) Combating Banking Fraud with It: Integrating Machine Learning and Data Analytics. The American Journal of Management and Economics Innovations, 6, 39-56. https://doi.org/10.37547/tajmei/volume06issue07-04
[13]
Hasan, R., Chy, M.A.R., Johora, F.T., Ullah, M.W. and Saju, M.A.B. (2024) Driving Growth: The Integral Role of Small Businesses in the U.S. Economic Landscape. American Journal of Industrial and Business Management, 14, 852-868. https://doi.org/10.4236/ajibm.2024.146043
[14]
Hasan, R., Farabi, S.F., Kamruzzaman, M., Bhuyan, M.K., Nilima, S.I. and Shahana, A. (2024) AI-Driven Strategies for Reducing Deforestation. The American Journal of Engineering and Technology, 6, 6-20. https://doi.org/10.37547/tajet/volume06issue06-02
[15]
Sobuz, M.H.R., Al-Imran Datta, S.D., Jabin, J.A., Aditto, F.S., Sadiqul Hasan, N.M., et al. (2024) Assessing the Influence of Sugarcane Bagasse Ash for the Production of Eco-Friendly Concrete: Experimental and Machine Learning Approaches. Case Studies in Construction Materials, 20, e02839. https://doi.org/10.1016/j.cscm.2023.e02839
[16]
Jabin, J.A., Khondoker, M.T.H., Sobuz, M.H.R. and Aditto, F.S. (2024) High-temperature Effect on the Mechanical Behavior of Recycled Fiber-Reinforced Concrete Containing Volcanic Pumice Powder: An Experimental Assessment Combined with Machine Learning (ML)-Based Prediction. Construction and Building Materials, 418, Article ID: 135362. https://doi.org/10.1016/j.conbuildmat.2024.135362
[17]
Habibur Rahman Sobuz, M., Khan, M.H., Kawsarul Islam Kabbo, M., Alhamami, A.H., Aditto, F.S., Saziduzzaman Sajib, M., et al. (2024) Assessment of Mechanical Properties with Machine Learning Modeling and Durability, and Microstructural Characteristics of a Biochar-Cement Mortar Composite. Construction and Building Materials, 411, Article ID: 134281. https://doi.org/10.1016/j.conbuildmat.2023.134281
[18]
Gao, P., Li, J. and Liu, S. (2021) An Introduction to Key Technology in Artificial Intelligence and Big Data Driven E-Learning and E-Education. Mobile Networks and Applications, 26, 2123-2126. https://doi.org/10.1007/s11036-021-01777-7
[19]
Ouyang, F., Zheng, L. and Jiao, P. (2022) Artificial Intelligence in Online Higher Education: A Systematic Review of Empirical Research from 2011 to 2020. Education and Information Technologies, 27, 7893-7925. https://doi.org/10.1007/s10639-022-10925-9
[20]
Johora, F.T., Hasan, R., Farabi, S.F., Akter, J. and Mahmud, M.A.A. (2024) AI-Powered Fraud Detection in Banking: Safeguarding Financial Transactions. The American Journal of Management and Economics Innovations, 6, 8-22. https://doi.org/10.37547/tajmei/volume06issue06-02
[21]
Al Mahmud, A., Hossain, A., Saju, A.B., Ul-lah, W., Hasan, R. and Suzer, G. (2024) Information Technology for the Next Future World: Adoption of It for Social and Economic Growth: Part II. International Journal of Innovative Research in Technology, 10, 742-747.
[22]
Shahana, A., Hasan, R., Farabi, S.F., Akter, J., Mahmud, M.A.A., Johora, F.T., et al. (2024) AI-Driven Cybersecurity: Balancing Advancements and Safeguards. Journal of Computer Science and Technology Studies, 6, 76-85. https://doi.org/10.32996/jcsts.2024.6.2.9
[23]
Benbya, H., Davenport, T.H. and Pachidi, S. (2020) Artificial Intelligence in Organizations: Current State and Future Opportunities. SSRN Electronic Journal, volume, page. https://doi.org/10.2139/ssrn.3741983
[24]
Gwagwa, A., Kraemer-Mbula, E., Rizk, N., Rutenberg, I. and De Beer, J. (2020) Artificial Intelligence (AI) Deployments in Africa: Benefits, Challenges and Policy Dimensions. The African Journal of Information and Communication, 26, 1-28. https://doi.org/10.23962/10539/30361
[25]
Noy, S. and Zhang, W. (2023) Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence. Science, 381, 187-192. https://doi.org/10.1126/science.adh2586
[26]
Prasad Agrawal, K. (2023) Towards Adoption of Generative AI in Organizational Settings. Journal of Computer Information Systems. https://doi.org/10.1080/08874417.2023.2240744
[27]
Perrotta, C. and Selwyn, N. (2019) Deep Learning Goes to School: Toward a Relational Understanding of AI in Education. Learning, Media and Technology, 45, 251-269. https://doi.org/10.1080/17439884.2020.1686017
[28]
Ansari, M.F., Dash, B., Sharma, P. and Yathiraju, N. (2022) The Impact and Limitations of Artificial Intelligence in Cybersecurity: A Literature Review. International Journal of Advanced Research in Computer and Communication Engineering, 11, 81-90. https://doi.org/10.17148/ijarcce.2022.11912
[29]
Amann, J., Blasimme, A., Vayena, E., Frey, D. and Madai, V.I. (2020) Explainability for Artificial Intelligence in Healthcare: A Multidisciplinary Perspective. BMC Medical Informatics and Decision Making, 20, Article No. 310. https://doi.org/10.1186/s12911-020-01332-6
[30]
Chen, M. and Decary, M. (2019) Artificial Intelligence in Healthcare: An Essential Guide for Health Leaders. Healthcare Management Forum, 33, 10-18. https://doi.org/10.1177/0840470419873123
[31]
Aditto, F.S., Sobuz, M.H.R., Saha, A., Jabin, J.A., Kabbo, M.K.I., Hasan, N.M.S., et al. (2023) Fresh, Mechanical and Microstructural Behaviour of High-Strength Self-Compacting Concrete Using Supplementary Cementitious Materials. Case Studies in Construction Materials, 19, e02395. https://doi.org/10.1016/j.cscm.2023.e02395
[32]
Hasan, N.M.S., Sobuz, M.H.R., Shaurdho, N.M.N., Meraz, M.M., Datta, S.D., Aditto, F.S., et al. (2023) Eco-friendly Concrete Incorporating Palm Oil Fuel Ash: Fresh and Mechanical Properties with Machine Learning Prediction, and Sustainability Assessment. Heliyon, 9, e22296. https://doi.org/10.1016/j.heliyon.2023.e22296
Habibur Rahman Sobuz, M., Khan, M.H., Kawsarul Islam Kabbo, M., Alhamami, A.H., Aditto, F.S., Saziduzzaman Sajib, M., et al. (2024) Assessment of Mechanical Properties with Machine Learning Modeling and Durability, and Microstructural Characteristics of a Biochar-Cement Mortar Composite. Construction and Building Materials, 411, Article ID: 134281. https://doi.org/10.1016/j.conbuildmat.2023.134281
[35]
Fitria, T.N. (2021) Artificial Intelligence (AI) in Education: Using AI Tools for Teaching and Learning Process. Prosiding Seminar Nasional & Call for Paper STIE AAS, Surakarta, 134-147.
[36]
Innocenti, S. and Golin, M. (2022) Human Capital Investment and Perceived Automation Risks: Evidence from 16 Countries. Journal of Economic Behavior & Organization, 195, 27-41. https://doi.org/10.1016/j.jebo.2021.12.027
