The most common use case of AI might currently be for customer service chatbots or content generation, but in the coming years AI agents could support a number of supply-chain management functions, like demand forecasting, estimating supplier risk or even analysing weather data.

Organisations of all sizes are already investing in their AI capabilities and, as more and more businesses leverage the technology, global supply-chain management is likely to be completely transformed.

For decades, supply chains were optimised primarily for cost efficiency, but recent world events have highlighted the risks of this approach. Long, complex chains can quickly fail under the stress of geopolitical or economic shocks.

To help prevent this, AI could be used to enhance human decision making and spot patterns and trends at scale that might otherwise be missed. AI agents could also help implement agile responses to minimise the worst effects of a supply chain failure.

Companies with established supply chains are leading the charge towards AI capability, with some already beginning to reap the rewards. In a recent survey of 1,148 companies, consulting firm Accenture found that businesses with mature supply chains were 23% more likely to use AI and generative AI across their entire operations.

And “Leaders” – the 10% of companies scoring highest on the maturity scale – achieved 23% higher margins than their peers (11.8% vs. 9.6%) between 2019 and 2023. At the same time, they delivered 15% better returns to shareholders (8.5% vs. 7.4%).

As the Accenture report says: “Leaders are investing in next generation capabilities at four times the rate of other companies. In doing so, they are poised to quickly pull ahead of all others. Given the business transformation speed facilitated by such capabilities the gap will only widen, making it imperative for all companies to act today to avoid being left behind.”

Another consulting firm, EY, also found a huge appetite for AI within supply chain businesses. Its own study reported that around 40% of supply chain organisations are currently investing in generative AI.

The Association for Supply Chain Management also identified AI as the number one supply chain trend in 2025 in its most recent report. It’s clear that the business case for exploring AI has never been stronger.

1. More accurate demand forecasting

Current forecasting methods rely on historical sales data and assumptions about market growth, but these models can fail when external shocks or quickly shifting consumer behaviour occurs. AI agents can integrate very large datasets and machine learning algorithms can analyse this data in real time to provide more accurate forecasts.

For example, a business could use AI to detect a surge in online searches for a particular product weeks before orders are placed, allowing it to adjust production schedules early and reduce the risk of selling out of stock or being left with excess inventory. This could improve the efficiency of working capital and allow for better cash flow management. 

2. Agile planning and sourcing

Supply chain planning is often a complex balancing act of matching production capacity to supplier availability, logistics routes and customer demand. AI could help generate scenario modelling at a scale not previously possible.

AI-driven planning tools can simulate thousands of potential scenarios – from a port closure in Asia to an energy price spike in Europe – and recommend immediate responses. This is especially valuable in industries where supply chains are global and disruptions can have a cascading effect.

AI can also combine supplier performance data with market intelligence to find the best sourcing partners for a business. AI could also measure a supplier’s reliability or ESG credentials as well as analysing cost. By combining financial and non-financial data, AI could help procurement teams make more balanced decisions over the long term.

3. Supplier management and risk monitoring

Supplier networks are often vast and intricate and many organisations lack visibility beyond their first-tier supplier network, leaving them exposed to risks buried deeper in the chain.

AI can help map and monitor supplier networks more accurately. Natural language processing (NLP) tools, for example, can scan millions of documents – from news reports to regulatory filings – and flag potential risks.

This could help businesses diversify supply chains or work with suppliers to help solve production issues, as well as providing early warning of issues that could affect cash flow.

4. Contracting and compliance

Supply chain contracts can be lengthy and written in dense legal jargon. AI can streamline both the creation and management of these documents.

Contract analytics tools use machine learning to assess compliance risks and compare contract terms against benchmarks. For example, an AI tool could identify that a new supplier contract lacks the agreed-upon delivery performance clause, or that payment terms don’t comply with the normal standards set by the business.

AI agents can also monitor live contract performance. By integrating logistics data, An AI-powered system could flag breaches in real time, so if a supplier’s delivery is consistently outside agreed lead times AI can help to resolve issues quickly and reduce disputes.

5. Finance, trade, and working capital optimisation

Supply chain strength is not only about operational efficiency, it can also help to optimise a business’ working capital. Businesses could use AI for trade finance management and invoice processing. For example, AI could:

• Detect inconsistencies in trade documentation, reducing fraud risk.
• Automate invoice reconciliation, cutting manual costs.
• Analyse supplier payment patterns to identify potential cash-flow pressures and allow finance directors to take action.

Although there is clear potential for AI, integrating the technology into supply chain operations could also present businesses with some challenges:

• Data quality and integration – AI is only as strong as the data it uses. Businesses could experience negative results if their AI is exposed to incomplete or incorrect supplier data.
• Knowledge gaps and training – Employees may need to acquire new skills in data analytics and AI strategy to ensure that the enhanced supply chain operates efficiently.
• Ethics and transparency – AI decision-making and logic can sometimes be hidden from the user. Ensuring there is a record of fairness in supplier selection could be essential for a business’ reputation.
• ROI considerations – Investing in AI must make financial sense for a business. Starting modestly with targeted projects can help build momentum without taking on unnecessary financial risks.

Despite these challenges, AI is becoming more accessible. With cloud-based tools now increasingly common, businesses no longer have to build their AI capability from scratch.

For businesses seeking to explore AI, three practical steps can help initiate the process:

1. Identify weaknesses: Explore where disruptions or inefficiencies impact your business the most. These will be the best areas to look for potential AI solutions. 
2. Make the right partnerships: Building a strong team of technology and financial partners could be key to the success of any supply-chain AI project. 
3. Invest in your data: Reliable, easily accessible data is essential for AI systems, so businesses should prioritise improving the quality of their data as an essential first step.

Some industry specialists have highlighted the potential for fully autonomous supply chains in the future. These would use AI agents to self-manage most of a business’ operations – monitoring demand, placing orders, and optimising logistics with little human intervention.

Fully autonomous supply chains might still be some years away, but some elements of these systems already exist. AI procurement agents and real-time logistics management tools are already in operation, and new, more sophisticated tools are being developed at pace.

Businesses exploring the supply chain capabilities of AI now, could experience a real market advantage as these tools become more mainstream.

At NatWest, we’re working with businesses across many sectors to explore how financial solutions and AI-enabled supply chain tools can work hand in hand. If you’d like to find out more about how AI could help your business, our supply chain specialists are here to help.