As 2025 unfolds, the impact of artificial intelligence (AI) on supply chain management is becoming increasingly evident. While discussions about AI’s broader societal implications continue, businesses must focus on its practical applications. Below is an exploration of how AI is and maybe reshaping supply chains.
The State of AI in 2024: Self-Diagnostics
AI’s presence in supply chains is not new, though it gained significant attention with tools like OpenAI’s ChatGPT in 2022. Beyond conversational AI, specialised systems powered by machine learning and optimisation algorithms have long been transforming supply chain management, replacing spreadsheets and outdated planning systems.
A key advancement in 2024 has been self-diagnostic AI. These systems analyse operational data to identify inefficiencies and opportunities for improvement. For instance, generative AI (Gen AI) can now answer nuanced operational queries such as, “What were the top five causes of stock-outs last week?” Such tools empower businesses with precise insights, enhancing decision-making.
Preemptive Diagnostics in 2025: Mitigating Risks
In 2025, preemptive diagnostics are a game-changer for supply chain resilience. AI tools like Rebot proactively identify risks, allowing businesses to address vulnerabilities before they escalate. By analysing forecasts, business rules, and historical data, AI highlights critical areas, such as potential mismatches between inventory and demand, enabling corrective action.
This approach not only reduces disruptions but also optimises resource allocation, ensuring consistent performance and enhanced productivity. Businesses can focus efforts where they matter most, improving key performance indicators (KPIs) through timely interventions.
Proactive Recommendations in 2026: Enhancing Agility
By 2026, AI’s ability to offer proactive recommendations may be redefining how supply chains adapt to change. These systems could enable businesses to continuously refine configurations in response to evolving market conditions.
Effective application of AI requires high-quality data and appropriate configurations. AI itself can assist in these areas—using machine learning to generate synthetic data or improving configuration setups to maximise system potential. This adaptability ensures businesses remain agile in the face of disruption, driving significant improvements in operational KPIs.
Autonomous Agents in 2027: The Next Frontier
The ultimate promise of AI in supply chains lies in autonomous agents. These advanced systems go beyond diagnostics and recommendations by executing actions independently to optimise operations.
Envision an AI agent capable of autonomously adjusting supply chain setups to align with dynamic business needs and external factors. With continuous model upgrades and access to diverse datasets, these agents represent the future of automation, potentially eliminating traditional silos that hinder efficiency today.
While significant progress has been made in autonomous AI, widespread adoption will likely require a few more years due to the need for robust guardrails and risk mitigation strategies. Transparency and trust will be critical to unlocking these systems’ full potential.
Conclusion: Embracing AI for Supply Chain Success
AI-powered tools are revolutionising supply chain management, offering unprecedented opportunities for efficiency, resilience, and innovation. Businesses must embrace these advancements and partner with experts proficient in various AI applications to stay competitive. Opting out is not an option—AI is the key to thriving in the evolving landscape of supply chain operations.
This article was written by Laurence Brenig-Jones, VP of Product Strategy and Marketing at RELEX Solutions.