Sunil David, Digital Technology Consultant, Ex-Regional Director – IOT, AT&T India, delves into AI’s transformative influence on logistics, underscoring improved efficiency and transparency, addressing evolving regulations for privacy and employment, and stressing upskilling and ethical AI development for seamless workforce integration.
AI-powered systems revolutionise real-time tracking in logistics, impacting visibility and customer satisfaction
AI-based technologies, including predictive analytics and machine learning, have brought sweeping changes to the global logistics industry, with India showcasing notable applications and trends. In a country with intricate road networks and traffic fluctuations like India, machine learning plays a pivotal role in optimising delivery routes. Predictive analytics anticipates traffic patterns, ensuring efficient planning. Warehouse automation witnesses AI integration, streamlining inventory management, and enhancing packing processes, reducing manual labour and errors while significantly boosting efficiency.
AI’s impact
AI-powered systems revolutionise real-time tracking in logistics, impacting visibility and customer satisfaction. Predictive analytics, like estimating arrival times (ETA), utilises historical data and current conditions for accurate predictions, addressing variables such as traffic and weather. Integration with IoT devices enables real-time data, which is crucial in pharmaceutical logistics for monitoring temperature-sensitive shipments. This transparency fosters trust and proactive issue resolution, optimising operational efficiency.
Automation
AI-based technologies are pivotal in driving automation across global industries, transforming warehouse operations and logistics management. Notable instances include:
- Automated Sorting and Handling:
- AI and robotics streamline goods sorting, reducing manual labour.
- Robotic arms and AGVs organise goods efficiently in warehouses.
- Predictive Analytics for Inventory Management:
- AI algorithms predict future inventory needs, minimising overstocking or stockouts.
- Ensures optimal resource allocation, reducing operational costs.
- Safety and Compliance:
- AI systems monitor safety compliance, predicting potential hazards.
- Improves overall workplace safety in warehouse environments.
Regulatory evolution
AI’s integration into logistics triggers a regulatory evolution. Governments address safety, privacy, and fairness challenges. Key aspects include:
- Data Privacy and Security:
- Updating regulations to safeguard AI-dependent data.
- Similar laws to GDPR are considered globally, like India’s Digital Personal Data Protection Act.
- AI in Employment:
- Regulations adapting to AI-driven labour changes.
- Ensuring fair labour practices amid the impact of automation.
- International Trade and AI:
- Crucial global regulations for AI in cross-border logistics.
- Establishing standards and agreements for AI usage in international trade.
Human-AI synergy
AI adoption impacts logistics employment by automating repetitive tasks, reducing basic labour needs, and creating new roles demanding technical expertise. Job satisfaction improves as AI augments human capabilities, shifting the focus to higher-skilled tasks. To address concerns, collaboration between governments and academia is crucial, as is updating curricula and offering industry-aligned training programs. Emphasising human-centric AI development ensures more sustainable integration with systems that complement human skills rather than replace them.
