The ascent of generative AI, such as Chat GPT, has propelled the interest of business leaders in AI’s potential. Studies show a significant uptick in organizations delving into AI and machine learning, with many actively exploring or implementing these technologies in their operations. Projections indicate a substantial surge in AI spending, with the Middle East and Africa slated to invest around US$6.4 billion in AI by 2026.
Yet, as businesses seek to harness AI for profitability and growth, it’s crucial to acknowledge its broader impact, especially concerning the imminent United Nations Sustainable Development Goals.
Exploring AI’s impact across economic, social, and environmental domains reveals numerous significant use cases across various industries.
Economic Impact: Transportation and logistics showcase AI’s influence through Smart City initiatives. Automakers are spearheading semi-autonomous vehicles, some countries even integrating fully autonomous buses and taxis into daily life. Initiatives like the Sino-Singapore Tianjin Eco-City project display the deployment of autonomous transportation and smarter traffic control systems.
Innovative initiatives like the TXAI in Abu Dhabi’s Yas Island highlight how the UAE is pioneering autonomous vehicles, reshaping the transportation landscape.
Oil and gas industries are harnessing AI to address the climate crisis. Efforts are directed toward transforming into diversified, net-zero energy companies. Predictive AI is projected to aid in simulating technologies to estimate and curb emissions significantly by 2026. Furthermore, genAI assists in downstream operations by analyzing geological data to identify potential oil and gas deposits.
Societal and Environmental Impact: The healthcare sector, post-pandemic, is leveraging AI to enhance patient care, from diagnosis and drug efficacy studies to improving overall hospital processes. The industry is projected to rely significantly on digital-first strategies and interoperable workflows, aiming to enhance patient experiences and build trust.
In sports, AI-driven big data and analytics are transforming viewer experiences, offering immersive opportunities for fans. Advanced analytics, player tracking, and injury detection technologies enhance the sports-viewing experience, fostering community engagement and support.
These instances only scratch the surface of AI’s potential to revolutionize industries. However, fostering a transformative AI-driven world necessitates industry-wide collaboration, transcending siloed approaches to data, applications, and expertise. Collective efforts can surmount challenges, steering us toward a brighter future.
