Businesses looking to use artificial intelligence (AI) to improve their supply chains may not get the results they hope for unless they also address weaknesses in their data quality, workforce skills, and management practices. This is the key finding of a new study published in Benchmarking: An International Journal, led by the University of East London (UEL). The research highlights that while AI and other advanced technologies can help companies predict demand and respond faster to disruptions, they are not a guaranteed solution on their own. The study, conducted by researchers from the Royal Docks School of Business and Law and the University of Hertfordshire, analyzed more than 500 academic papers published over the last ten years. These studies focused on how big data and other technologies are used in supply chains and business operations. The researchers found that even the most advanced systems are of little use if the people using them don’t trust or understand the data they provide. Dr. Godfried Adaba, a lecturer in supply chain management, emphasized that simply purchasing the latest AI or data tools is not enough. “These technologies can help, but only if the groundwork is already in place,” he said. He explained that businesses need reliable data, employees with the right skills, clear decision-making processes, and managers who trust the information they receive. Without these elements, high-tech solutions can become costly without delivering real benefits. The study recommends that businesses focus on improving their data management, analytical capabilities, and decision-making structures before investing heavily in advanced analytics. It also stresses the importance of having teams that combine technical knowledge with operational experience. This approach ensures that technology is used effectively to support, rather than replace, human judgment in managing complex supply chains.