Artificial intelligence is not a buzzword anymore! It has become an everyday reality across businesses and industries. Operations management is all about how organisations plan, produce, and deliver goods and services to consumers, and AI is quietly but powerfully changing this transformation process. As someone who teaches Operations Management, I found this change to be quite fascinating and intriguing because it blends new technology, trends, and innovation with the analytical side of management – something which our students will learn and work through in their professional careers.
From Data to Decisions
Formerly, decision-making in operations was based on experience, intuition, and historical trends, where bounded-rationality would have a profound impact on decisions taken because of the availability of limited data and its processing. Now, AI tools help managers to make decisions having a broader perspective, as data patterns which may be overlooked by a human are easily detected by AI engines. With real-time data analysis, AI tools are better equipped to optimise schedules, forecast demand accurately, and detect potential bottlenecks in operations even before they occur.
For example, when predictive maintenance is integrated with AI systems, firms are able to schedule repair and maintenance before a particular defect has even occurred, which might have caused the machine to break down, thereby halting the entire operation. In this way, precious resources such as time and cost can be saved. In current dynamics, where such breakdowns or delays can cause the entire supply chain to be disrupted, such proactive measures are invaluable. The main objective here is to make the managerial judgment more informed rather than to replace it.
Automation that Enhances Human Work
AI is sometimes feared to take over jobs. However, in operational settings, AI does the opposite of this said concern. It replaces repetitive tasks so that people can be more focused on tasks which actually require human input.
AI-driven robots now perform sorting, scanning, and packaging duties in warehouses, freeing up human workers to concentrate on process improvement, safety oversight, and quality control. AI chatbots effectively handle standard customer service queries, freeing up human agents to handle intricate client issues that call for empathy and problem-solving skills. Similarly, AI algorithms in logistics examine weather patterns, traffic patterns, and delivery routes to suggest quicker and more economical solutions, freeing up managers to focus on strategic choices like contingency planning and supplier coordination. The result is an operational environment where people and intelligent systems collaborate, each contributing their own special strengths, rather than just increased efficiency.
Challenges along the way
Like any innovation, AI comes with challenges. The first is trust, trusting data, algorithms, and the insights they produce. Then comes training, employees need to understand and work comfortably with new systems. And finally, data quality, poor data can lead to poor predictions, so organisations must invest in clean, reliable, and secure data management practices.
These challenges are not roadblocks but part of the learning curve for firms aiming to stay competitive in an AI-driven world.
Key Takeaways
AI is transforming the field of Operations Management from reactive to predictive, from manual to intelligent. It allows organisations to make faster, smarter, and more informed decisions but its real power lies in collaboration between humans and machines. As educators and professionals, we must prepare the next generation not just to use AI, but to lead with it.
By: Kanza Azhar
Junior Lecturer
Business Administration
Iqra University
