Skip to main navigation menu Skip to main content Skip to site footer

Peer Reviewed Article

Vol. 4 No. 1 (2024)

Harnessing Artificial Intelligence to Drive Global Sustainability: Insights Ahead of SAC 2024 in Kuala Lumpur

Submitted
27 February 2024
Published
01-05-2024

Abstract

In light of the Sustainable Asia Conference (SAC) 2024 in Kuala Lumpur, this paper examines how AI can alter global sustainability. The main goal is to evaluate how AI might improve sustainability in agriculture, energy, urban management, biodiversity protection, and climate action. The study synthesizes case studies and literature using secondary data to identify practical AI applications and their obstacles. According to major studies, AI can maximize resource utilization, improve decision-making, and drive innovation while tackling data privacy, algorithmic bias, and the digital divide. The research emphasizes strong governance structures to ensure ethical AI adoption and public trust. It also stresses the necessity for AI technology access policies, especially for underprivileged areas. The study indicates that collaboration between government, corporate, and civil society is necessary for using AI for sustainable development. This research focuses on responsible practices and inclusive policies to guide actionable AI strategies that promote a resilient and sustainable future for all, contributing to the UN Sustainable Development Goals.

References

  1. Ahmmed, S., Narsina, D., Addimulam, S., & Boinapalli, N. R. (2021). AI-Powered Financial Engineering: Optimizing Risk Management and Investment Strategies. Asian Accounting and Auditing Advancement, 12(1), 37–45. https://4ajournal.com/article/view/96
  2. Allam, A. R. (2020). Integrating Convolutional Neural Networks and Reinforcement Learning for Robotics Autonomy. NEXG AI Review of America, 1(1), 101-118.
  3. Boinapalli, N. R. (2020). Digital Transformation in U.S. Industries: AI as a Catalyst for Sustainable Growth. NEXG AI Review of America, 1(1), 70-84.
  4. Boinapalli, N. R. (2023). AI-Driven Predictive Analytics for Risk Management in Financial Markets. Silicon Valley Tech Review, 2(1), 41-53.
  5. Boinapalli, N. R., Farhan, K. A., Allam, A. R., Nizamuddin, M., & Sridharlakshmi, N. R. B. (2023). AI-Enhanced IMC: Leveraging Data Analytics for Targeted Marketing Campaigns. Asian Business Review, 13(3), 87-94. https://doi.org/10.18034/abr.v13i3.729
  6. Bruneckiene, J., Jucevicius, R., Zykiene, I., Rapsikevicius, J., Lukauskas, M. (2019). Assessment of Investment Attractiveness in European Countries by Artificial Neural Networks: What Competences are Needed to Make a Decision on Collective Well-Being?. Sustainability, 11(24), 6892. https://doi.org/10.3390/su11246892
  7. Chin, T., Li, G., Jiao, H., Addo, F., Jawahar, I. M. (2019). Career Sustainability During Manufacturing Innovation: A Review, a Conceptual Framework and Future Research Agenda. Career Development International, 24(6), 509-528. https://doi.org/10.1108/CDI-02-2019-0034
  8. Deming, C., Pasam, P., Allam, A. R., Mohammed, R., Venkata, S. G. N., & Kothapalli, K. R. V. (2021). Real-Time Scheduling for Energy Optimization: Smart Grid Integration with Renewable Energy. Asia Pacific Journal of Energy and Environment, 8(2), 77-88. https://doi.org/10.18034/apjee.v8i2.762
  9. Devarapu, K., Rahman, K., Kamisetty, A., & Narsina, D. (2019). MLOps-Driven Solutions for Real-Time Monitoring of Obesity and Its Impact on Heart Disease Risk: Enhancing Predictive Accuracy in Healthcare. International Journal of Reciprocal Symmetry and Theoretical Physics, 6, 43-55. https://upright.pub/index.php/ijrstp/article/view/160
  10. Gherhes, V., Obrad, C. (2018). Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI). Sustainability, 10(9), 3066. https://doi.org/10.3390/su10093066
  11. Gummadi, J. C. S., Narsina, D., Karanam, R. K., Kamisetty, A., Talla, R. R., & Rodriguez, M. (2020). Corporate Governance in the Age of Artificial Intelligence: Balancing Innovation with Ethical Responsibility. Technology & Management Review, 5, 66-79. https://upright.pub/index.php/tmr/article/view/157
  12. Gummadi, J. C. S., Thompson, C. R., Boinapalli, N. R., Talla, R. R., & Narsina, D. (2021). Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis. Global Disclosure of Economics and Business, 10(2), 129-140. https://doi.org/10.18034/gdeb.v10i2.769
  13. Karanam, R. K., Natakam, V. M., Boinapalli, N. R., Sridharlakshmi, N. R. B., Allam, A. R., Gade, P. K., Venkata, S. G. N., Kommineni, H. P., & Manikyala, A. (2018). Neural Networks in Algorithmic Trading for Financial Markets. Asian Accounting and Auditing Advancement, 9(1), 115–126. https://4ajournal.com/article/view/95
  14. Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., Zhang, W. (2018). The Rise of Artificial Intelligence under the Lens of Sustainability. Technologies, 6(4), 100. https://doi.org/10.3390/technologies6040100
  15. Khosravi, F., Izbirak, G., Adesina, K. A. (2019). An Exponentially Distributed Stochastic Model for Sustainability Measurement of a Healthcare System. Sustainability, 11(5), 1285. https://doi.org/10.3390/su11051285
  16. Khosravi, K., Panahi, M., Bui, D. T. (2018). Spatial Prediction of Groundwater Spring Potential Mapping Based on an Adaptive Neuro-fuzzy Inference System and Metaheuristic Optimization. Hydrology and Earth System Sciences, 22(9), 4771-4792. https://doi.org/10.5194/hess-22-4771-2018
  17. Kommineni, H. P., Fadziso, T., Gade, P. K., Venkata, S. S. M. G. N., & Manikyala, A. (2020). Quantifying Cybersecurity Investment Returns Using Risk Management Indicators. Asian Accounting and Auditing Advancement, 11(1), 117–128. https://4ajournal.com/article/view/97
  18. Kothapalli, S., Manikyala, A., Kommineni, H. P., Venkata, S. G. N., Gade, P. K., Allam, A. R., Sridharlakshmi, N. R. B., Boinapalli, N. R., Onteddu, A. R., & Kundavaram, R. R. (2019). Code Refactoring Strategies for DevOps: Improving Software Maintainability and Scalability. ABC Research Alert, 7(3), 193–204. https://doi.org/10.18034/ra.v7i3.663
  19. Kundavaram, R. R., Rahman, K., Devarapu, K., Narsina, D., Kamisetty, A., Gummadi, J. C. S., Talla, R. R., Onteddu, A. R., & Kothapalli, S. (2018). Predictive Analytics and Generative AI for Optimizing Cervical and Breast Cancer Outcomes: A Data-Centric Approach. ABC Research Alert, 6(3), 214-223. https://doi.org/10.18034/ra.v6i3.672
  20. Liyanage, S., Bagloee, S. A. (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability, 11(1), 189. https://doi.org/10.3390/su11010189
  21. McPhee, D. P. (2017). Urban Recreational Fisheries in the Australian Coastal Zone: The Sustainability Challenge. Sustainability, 9(3), 422. https://doi.org/10.3390/su9030422
  22. Mohammed, M. A., Allam, A. R., Sridharlakshmi, N. R. B., Boinapalli, N. R. (2023). Economic Modeling with Brain-Computer Interface Controlled Data Systems. American Digits: Journal of Computing and Digital Technologies, 1(1), 76-89.
  23. Rahman, K. (2017). Digital Platforms in Learning and Assessment: The Coming of Age of Artificial Intelligence in Medical Checkup. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 1-5. https://upright.pub/index.php/ijrstp/article/view/3
  24. Roberts, C., Kundavaram, R. R., Onteddu, A. R., Kothapalli, S., Tuli, F. A., Miah, M. S. (2020). Chatbots and Virtual Assistants in HRM: Exploring Their Role in Employee Engagement and Support. NEXG AI Review of America, 1(1), 16-31.
  25. Rodriguez, M., Sridharlakshmi, N. R. B., Boinapalli, N. R., Allam, A. R., & Devarapu, K. (2020). Applying Convolutional Neural Networks for IoT Image Recognition. International Journal of Reciprocal Symmetry and Theoretical Physics, 7, 32-43. https://upright.pub/index.php/ijrstp/article/view/158
  26. Sankaran, K. (2019). Carbon Emission and Plastic Pollution: How Circular Economy, Blockchain, and Artificial Intelligence Support Energy Transition?. Journal of Innovation Management, 7(4), 7-13. https://doi.org/10.24840/2183-0606_007.004_0002
  27. Talla, R. R., Addimulam, S., Karanam, R. K., Natakam, V. M., Narsina, D., Gummadi, J. C. S., Kamisetty, A. (2023). From Silicon Valley to the World: U.S. AI Innovations in Global Sustainability. Silicon Valley Tech Review, 2(1), 27-40.
  28. Thompson, C. R., Sridharlakshmi, N. R. B., Mohammed, R., Boinapalli, N. R., Allam, A. R. (2022). Vehicle-to-Everything (V2X) Communication: Enabling Technologies and Applications in Automotive Electronics. Asian Journal of Applied Science and Engineering, 11(1), 85-98.
  29. Thompson, C. R., Talla, R. R., Gummadi, J. C. S., Kamisetty, A (2019). Reinforcement Learning Techniques for Autonomous Robotics. Asian Journal of Applied Science and Engineering, 8(1), 85-96. https://ajase.net/article/view/94
  30. Venkata, S. S. M. G. N., Gade, P. K., Kommineni, H. P., Manikyala, A., & Boinapalli , N. R. (2022). Bridging UX and Robotics: Designing Intuitive Robotic Interfaces. Digitalization & Sustainability Review, 2(1), 43-56. https://upright.pub/index.php/dsr/article/view/159
  31. Yellapantula, K., Ayachit, M. (2019). Significance of Emotional Intelligence in the Era of Artificial Intelligence: A Study on the Application of Artificial Intelligence in Financial and Educational Services Sector. Ushus Journal of Business Management, 18(1), 35-48. https://doi.org/10.12725/ujbm.46.3

Similar Articles

1-10 of 18

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)