Insights
Supply chain and logistics organisations have spent several years responding to one disruption after another. What was once treated as exceptional has become part of the everyday operating environment: geopolitical tension, climate-related disruption, changing trade requirements, rising customer expectations and persistent pressure on costs and margins.
AI ambition is growing quickly in higher education, but skills gaps, governance questions, legacy systems and unclear ROI are making it harder to move from pilots to everyday use. Technology leaders need to focus on the foundations that make AI safe, useful and easier to scale across the institution.
Artificial intelligence promises huge opportunities for supply chain and logistics organisations, from demand forecasting and warehouse optimisation to route planning and customer service. Yet while investment continues to rise, many technology leaders are discovering that moving from AI pilot to production is far more difficult than launching a proof of concept. Our latest research found that 87% of supply chain and logistics organisations expect to increase their use of AI within the next two years, while 71% believe AI will have a high impact on their software development strategy. However, AI execution is becoming a problem. This article explores just some of the reasons AI initiatives stall in supply chain organisations and explains how technology leaders can build the foundations needed to move beyond experimentation and into measurable business value.
Are you moving fast, but your systems can't keep up? AI adoption is moving from experimentation to expectation. Consumer organisations are investing heavily in personalisation, intelligent customer experiences and real-time decision-making to stay competitive. However, many are discovering that scaling these capabilities is more difficult than launching them.
