Version 1
: Received: 25 April 2024 / Approved: 26 April 2024 / Online: 26 April 2024 (11:42:00 CEST)
How to cite:
AINAH, N. Advancing AI Integration in Sabah Business Landscape: Opportunities and Challenges. Preprints2024, 2024041725. https://doi.org/10.20944/preprints202404.1725.v1
AINAH, N. Advancing AI Integration in Sabah Business Landscape: Opportunities and Challenges. Preprints 2024, 2024041725. https://doi.org/10.20944/preprints202404.1725.v1
AINAH, N. Advancing AI Integration in Sabah Business Landscape: Opportunities and Challenges. Preprints2024, 2024041725. https://doi.org/10.20944/preprints202404.1725.v1
APA Style
AINAH, N. (2024). Advancing AI Integration in Sabah Business Landscape: Opportunities and Challenges. Preprints. https://doi.org/10.20944/preprints202404.1725.v1
Chicago/Turabian Style
AINAH, N. 2024 "Advancing AI Integration in Sabah Business Landscape: Opportunities and Challenges" Preprints. https://doi.org/10.20944/preprints202404.1725.v1
Abstract
The integration of artificial intelligence (AI) technologies into business practices presents both opportunities and challenges for Sabah, Malaysia. This dynamic abstract explores the latest research problem at the intersection of AI and business in Sabah, focusing on optimizing resource allocation in agriculture and enhancing tourism experiences through AI-driven solutions.In Sabah's agricultural sector, AI holds immense potential to revolutionize traditional farming practices. With limited arable land and unpredictable weather patterns, farmers face significant challenges in maximizing crop yields while minimizing resource inputs. Through the application of machine learning, remote sensing, and IoT devices, researchers aim to develop precision farming techniques that can analyze soil health, monitor crop growth, and predict pest outbreaks with unprecedented accuracy. By optimizing resource allocation and enhancing decision-making processes, these AI-driven solutions have the potential to revolutionize Sabah's agriculture industry, promoting sustainability and resilience in the face of environmental uncertainties.Moreover, the tourism industry in Sabah stands to benefit from AI integration, particularly in enhancing visitor experiences and destination management. With its diverse natural landscapes and rich cultural heritage, Sabah attracts tourists from around the globe. AI-powered recommendation systems, tailored to individual preferences and behavior, have the potential to provide personalized travel itineraries, optimize resource allocation, and boost visitor satisfaction. Additionally, natural language processing (NLP) algorithms can analyze online reviews and social media sentiments, providing valuable insights for destination marketing and management strategies. By harnessing the power of AI, Sabah can elevate its tourism offerings, attract more visitors, and enhance its reputation as a premier travel destination.However, alongside these opportunities, challenges abound in the integration of AI into Sabah's business landscape. Concerns regarding data privacy, cybersecurity, and ethical implications must be carefully addressed to ensure the responsible and sustainable deployment of AI technologies. Furthermore, the digital divide and limited access to technology in rural areas pose barriers to widespread adoption, necessitating comprehensive strategies for capacity building and infrastructure development.In conclusion, the advancement of AI integration in Sabah's business landscape holds immense promise for driving innovation, economic growth, and sustainability. By addressing the research problems outlined in this abstract, researchers, policymakers, and industry stakeholders can collaboratively navigate the opportunities and challenges of AI integration, paving the way for a prosperous and inclusive future for Sabah, Malaysia.
Keywords
AI; Business; Malaysia; Sabah
Subject
Social Sciences, Education
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.