The evolving supply chain is becoming more integrated, extending into product use, regeneration, and insights that drive customer loyalty and responsiveness. Over time, this enables quicker reactions by shrinking the gap between sensing demand and adapting supply chains, whether through infrastructure changes or product flow.

This approach fosters a more connected, regenerative system, blending disciplines across supply chain operations, business strategy, and technology. This is a key driver of efficiency and cost reduction, especially under current economic pressures like inflation and supply chain disruptions.

The financial challenges seen during Covid-19 and beyond have accelerated investment in digitalisation – a critical pathway to cost savings and operational resilience, enhancing efficiency without sacrificing business potential. as sustainability, ethical sourcing, and operational transparency,” Acoba outlined.

“Companies increasingly need to trace their supply chains from end to end—understanding the origins of goods, their impacts, and every stage of their journey. Advanced technology can facilitate this by identifying data gaps and accelerating the process of collecting, analysing, and acting on this information.”

Greater connections 

“Achieving the next level of cost efficiency requires a step change. Companies can no longer rely solely on reducing working capital or pressuring suppliers without risking resilience. Instead, savings will emerge from stronger connections between functions,” Lauren Acoba, Vice President of Research at Zero100, stated.

“For example, customer service roles are being reimagined—not just as support but as integral to demand sensing, regulatory influence, and planning. AI and digital tools enable this transformation, helping businesses address challenges like natural disasters, geopolitical tensions, and trade wars Resilience has become a boardroom priority for many organisations.”

Green drive

Sustainability is another motivating factor, as companies are using tools like AI to improve inventory management and reduce waste, such as cutting water use or identifying bottlenecks in the supply chain before they occur. These efforts not only support sustainability but also improve operational efficiency by avoiding delays and minimising overhead costs. “Addressing Scope 3 emissions—often the largest sustainability challenge—requires visibility and compliance at granular levels. While this remains difficult, many companies are taking steps to reduce emissions tactically, like saving energy or water in plants, which offers both financial and environmental benefits,” Acoba explained.

“The next frontier is systemic redesign, as seen in Ocado’s success with reusable and refillable packaging, which has tripled demand for these products, demonstrating how sustainability can align with business growth.”

Analysis and compliance

AI and data analytics are also enabling better traceability across supply chains, addressing not only sustainability but ethical concerns. By identifying patterns and risks, businesses can act proactively, ensuring compliance, reducing waste, and building more responsible operations.

“The integration of AI in supply chains is proving to be a game-changer, not only for driving efficiencies but also for addressing key challenges such One trend is the growing connection between traditionally siloed functions. For instance, companies are beginning to align long-term demand forecasting with regulatory requirements and sustainability goals. This integrated approach allows businesses to evaluate whether they can meet their growth objectives while achieving sustainability commitments like reducing Scope 3 emissions. By linking demand forecasts with sustainability planning, organisations can make deliberate adjustments to product design and development, optimising for cost, resilience, and environmental impact.

“While many supply chain leaders have started exploring AI applications, only a small percentage have implemented end-to-end AI strategies. The gap often stems from uncertainty about how and where AI can deliver value, as well as concerns about cost and scalability.

“AI isn’t new, but its integration across the full supply chain is still evolving. To address this, frameworks have emerged, helping companies map out AI opportunities and identify areas where it could be a competitive differentiator.”

Varied adoption

Some companies prioritise safe or proven AI applications, while others cautiously experiment with emerging technologies through controlled proof-of-concept projects. The challenge lies in scaling these innovations. Success depends on building a robust data infrastructure—a foundation that enables optimisation systems and predictive tools to deliver actionable insights. Organisations focusing on data ownership and platforming are positioning themselves to capitalise on AI when the technology matures. “Ultimately, companies that invest in data readiness now will be better prepared to adopt transformative technologies at the right time,” Acoba declared.

“It takes significant investment to integrate data and manage it effectively. For some businesses, the trade-off between the time and effort required versus the value gained simply isn’t worth it—they feel they already have a sufficient understanding of their risks.

“Companies must carefully assess how much effort they’re willing to invest in developing and integrating software into their existing systems and processes relative to the value they expect to derive.

“By planning for AI’s potential and ensuring data systems are in place, businesses can navigate the balance between innovation and operational stability, positioning themselves for long-term success.”