Cities get smarter, businesses go greener: AI is fueling a sustainability surge

AI’s role in logistics and supply chain management has been particularly transformative. The article cites projections that by 2026, 60% of businesses will deploy AI-powered warehouse solutions, a sharp rise from 10% in 2020. Companies like Amazon have already deployed over 200,000 warehouse robots to streamline operations. These systems not only reduce labor costs and processing times but also lower carbon emissions by minimizing waste and inefficiency.

Artificial intelligence is redefining how businesses operate, with ripple effects extending beyond corporate walls into urban development and societal well-being, according to a recent opinion article on AI's operational and societal impacts. The research titled "AI in business operations: driving urban growth and societal sustainability", highlights how AI adoption in business operations is catalyzing smart city transformations, driving sustainability, and reshaping labor and environmental dynamics.

Authored by researchers from UNITAR International University and NOVA University Lisbon and published in Frontiers in Artificial Intelligence, the opinion piece outlines how AI integration into core business functions, such as supply chains, logistics, maintenance, and customer services, is contributing to economic growth while reducing environmental impact. It argues that AI is not just optimizing operations but also laying the groundwork for more livable, efficient, and resilient urban systems.

According to the authors, approximately 30% of smart city applications will be powered by AI by the end of 2025. The opinion piece notes that the global AI market was valued at $196.63 billion in 2023 and is projected to grow at an annual rate of 36.6% through 2030. This rapid expansion, driven by both public and private sectors, is shifting the boundaries between technological innovation and sustainable governance.

AI’s role in logistics and supply chain management has been particularly transformative. The article cites projections that by 2026, 60% of businesses will deploy AI-powered warehouse solutions, a sharp rise from 10% in 2020. Companies like Amazon have already deployed over 200,000 warehouse robots to streamline operations. These systems not only reduce labor costs and processing times but also lower carbon emissions by minimizing waste and inefficiency.

Advanced AI methods such as deep reinforcement learning (DRL) are now being used for adaptive routing and inventory management. These tools allow businesses to respond in real time to demand fluctuations, optimizing resource use and supporting broader sustainability goals.

In parallel, AI applications in smart grids and energy systems are improving urban resilience. AI-enabled grid sensors can detect failures with 80% greater accuracy than traditional tools, enhancing reliability and reducing energy loss. In Germany, utility provider Tennet TSO uses IBM Watson’s cognitive platform to predict renewable energy generation, enabling real-time grid adjustments that prioritize clean energy usage.

Urban mobility is also benefiting. AI-driven traffic management systems in cities like Singapore dynamically adjust to congestion patterns and monitor energy usage across transportation networks. These efforts help reduce emissions, improve commuter efficiency, and align urban development with sustainability benchmarks.

Beyond infrastructure, AI is shaping agriculture, healthcare, and manufacturing. In agriculture, AI and IoT systems are being used to predict crop yields, optimize irrigation, and automate harvesting, increasing efficiency while reducing environmental footprints. In healthcare, AI-assisted diagnostic tools like those used in Germany’s PRAIM mammography screening project have increased cancer detection rates by 17.6% over standard practices.

However, the opinion piece cautions that AI’s benefits come with significant societal challenges. Data privacy, algorithmic bias, and the digital divide were identified as major concerns, particularly in urban environments where unequal access to technology can exacerbate social disparities. The report calls for stronger regulatory frameworks, ethical AI design, and inclusive deployment strategies to ensure that the benefits of AI are equitably distributed.

The article also notes that AI’s impact on employment is two-fold: while automation is displacing certain jobs, it is simultaneously creating demand for AI-specialized skills. Policymakers are urged to implement reskilling programs and digital literacy initiatives to help workers transition into new roles within AI-enhanced economies.

Data integrity is another critical issue. The article cites findings that 30% of sustainability data is either incomplete or unreliable, undermining the effectiveness of AI in decision-making processes. Clean, high-quality data is essential for the successful deployment of AI in sustainability contexts, particularly when training complex models like those used in DRL.

Resistance to technological change remains a persistent barrier. Many organizations lack AI literacy or face internal opposition to adopting new systems, often due to concerns over cost, job security, or data governance. The study emphasizes the need for leadership buy-in and institutional support to facilitate smooth transitions to AI-driven operations.

Despite these limitations, the authors argue that the potential of AI to promote circular economies, green infrastructure, and energy-efficient production is too significant to ignore. AI can automate sustainability reporting, reduce resource consumption, and power real-time monitoring tools that track environmental impact.

To fully realize this potential, the opinion piece calls for stronger partnerships between governments and businesses. Regulatory support, cross-sector data sharing, and public investment in AI infrastructure are essential to accelerating sustainable innovation. The authors advocate for policies that promote transparency, safeguard privacy, and ensure inclusive access to AI technologies.

AI’s value extends beyond efficiency gains and economic output. When strategically aligned with sustainability targets, AI can serve as a critical enabler of social progress, environmental stewardship, and urban regeneration. The integration of AI into business operations offers not only a competitive edge for companies but also a systemic pathway to achieving long-term societal and environmental goals.