Insights: Embracing the full potential of the AI-powered supply chain
In a region like the UAE, where logistics and transport have been named top-priority sectors for AI adoption by both government and industry stakeholders, building AI resilience into supply chains is especially critical, says Bowes
10 November, 2025
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Artificial Intelligence (AI) has emerged as a transformative force that is revolutionising the way supply chains operate. In the UAE, this transformation is particularly pronounced, with the country aiming to become a global leader in AI by 2031.
These ambitions are reinforced by the UAE’s AI market, which is projected to grow at a CAGR of 43.9 per cent from 2024 through 2030 to reach $46.33bn by the end of the decade.
Yet, until now, AI has primarily been used to improve the accuracy of demand forecasting. But this is just the starting point. As the adoption of AI and machine learning (ML) models becomes more widespread, new applications are emerging; enabling organisations to engage in next-generation demand planning practices that can truly elevate how they operate.
Supply chain disruptions remain the single most challenging issue impacting the operations of organisations today. Given the complexity of modern marketplaces, manual scenario planning is a tedious and time-consuming task that often results in suboptimal decisions.
In a region like the UAE, where logistics and transport have been named top-priority sectors for AI adoption by both government and industry stakeholders, building AI resilience into supply chains is especially critical. Why? With so many data points and potential variables to consider, planners can easily overlook the key influencing factors that matter the most when forecast accuracy is a concern.
For example, Middle East-based planners often face high volatility during global events like Ramadan or geopolitical shifts. AI tools allow for dynamic re-planning that accounts for local nuances and seasonal consumer behaviours.
Far faster and more accurate than manual methods, today’s ML models are capable of both autonomously and dynamically configuring the best combination of variables to use in demand models. Powered by deep meta learning, these models enable planners to capture the complete value of unlimited data and unlock the speed of integrated ML.
Alongside eliminating guesswork and human bias from the process, this algorithmic approach ensures that variables can be rapidly reconfigured as market and business realities change.
Unlocking improved productivity and performance
Innovations such as generative AI now deliver fast access to data driven insights, as well as assisted decision-making and process automation. All of which dramatically improves the productivity and performance of planning teams.
A 2024 KPMG report found that 96 per cent of UAE tech leaders plan to increase investments in AI and cloud in the next 12 months, and 100 per cent say data analytics is essential for staying competitive.
This is because these generative AI models enable planners to ask clarifying questions, request data, visualise influencing factors and assess the effectiveness of past decisions. They can also be trained on enterprise standard operating procedures, business processes and workflows to provide highly contextualised and relevant responses to planner queries. There is no longer any need for planners to dig through multiple text-based resources to find answers to basic queries.
This capability for swift, data-driven decision-making is reinforced by insights from the Supply Chain Compass Report.
The survey polled nearly 700 global supply chain leaders, with 74 per cent of this group affirming that AI is already significantly transforming their operations and further validating why investing in AI-driven productivity tools is essential for maintaining competitive advantage.
In essence, today’s AI-based training programmes can significantly reduce the time and effort required to cross-train planners and onboard new hires – something that will significantly benefit organisations as they look to prepare the next generation of demand planners.
Read: How artificial intelligence is helping deliver smarter supply chains
Gaining the competitive edge
As we’ve seen, recent AI developments are enabling companies to go beyond improving their forecasting accuracy to initiate agile and responsive supply chains capable of meeting the demands of today’s modern and extremely active marketplaces. This is especially relevant in the Middle East, given the investments being made to accelerate AI adoption.
With large-scale government initiatives such as MGX Fund Management (a $100bn AI-focused investment fund) and the NextGen FDI programme, the UAE is creating fertile ground for AI-driven innovation in logistics and supply chain.
This commitment is further demonstrated by the launch of the 5GW AI campus in Abu Dhabi, the largest such facility outside the US. Developed by G42, in partnership with US hyperscalers and approved cloud service providers, it provides advanced compute infrastructure to support regional and global AI application.
By giving demand planners the integrated demand and supply planning (IDSP) capabilities they need to model and optimise a 360-degree planning view in seconds rather than days, companies are now able to rapidly capitalise on new opportunities and resolve disruptions before cost and service outcomes are affected.
The UAE has also signalled its intent to secure large-scale AI compute resources – including an estimated 500,000 Nvidia AI chips annually as part of a broader effort to bolster sovereign data infrastructure and accelerate AI innovation. Echoing this strategic direction, the aforementioned highlights that 61 per cent of global supply chain leaders intend to invest between $1–$10m in supply chain technologies over the next five years, clearly demonstrating a widespread commitment to harnessing AI to build resilient, responsive, and agile supply chains.
Chain Compass Report highlights that 61 per cent of global supply chain leaders intend to invest between $1–$10m in supply chain technologies over the next five years, clearly demonstrating a widespread commitment to harnessing AI to build resilient, responsive, and agile supply chains.
AI developments for supply chain are especially well-timed given this acceleration. And for organisations that want to not only thrive but also distinguish themselves in today’s ever-evolving global commerce landscape, harnessing AI in the supply chain is fast becoming a necessity rather than a nice-to-have.
