As supply chains continue to face complex global challenges, businesses are increasingly turning to artificial intelligence (AI) to stay resilient. Drawing on insights from Deloitte’s 2024/5 Global Third-Party Risk Management (TPRM) Survey, we explore how AI is transforming supply chain management and risk mitigation.
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How does AI contribute to building a more resilient supply chain?
The 2024/5 Global Third-Party Risk Management (TPRM) Survey from Deloitte shows the definition and use of AI in supply chain resilience is broadening. It not only includes Generative AI (Gen AI) but also encompasses an interconnected array of technologies that now go beyond machine learning, deep learning, and generative pre-trained transformers (referred to as GPTs), to enable intelligent automation in building resilient supply chains.
With strategic investment, these powerful AI-driven analytical capabilities can empower businesses to move beyond reactive measures to adopt a proactive, anticipatory approach to supply chain disruption. For example, by leveraging machine learning on historical datasets, AI can predict fluctuations in demand and supply and identify emerging risks based on historical environmental patterns and trends. AI-powered risk sensing leverages the aggregation of diverse data sources, including open-source intelligence and commercial data, to identify and prioritise risks. By analysing this comprehensive data pool, AI could more effectively screen for both actual and projected risks across categories and commodities, enhancing transparency and visibility across the supply chain. This could provide early warning indicators that enable agile responses to unforeseen events, ultimately allowing businesses to make informed decisions at scale and speed to minimise impact.
However, it is important to acknowledge the limitations of AI. For example, AI’s predictive capabilities are limited by the data it is trained on, which is often publicly available and may not capture all potential risks. This is particularly true for unprecedented events, such as “black swan” events, which are low likelihood but high impact. Similarly, AI implementation must balance the opportunities with the new ‘dual-risk landscape’, recognising the convergence of internal and external AI risks. Deloitte’s 2024/5 Global TPRM Survey reports that the top concerns for organisational use of AI for third party management relate to inaccuracy / “hallucination”, confidentiality and privacy, and misuse. This underscores the need for a responsible and considered approach to AI implementation, ensuring its benefits are realised while mitigating potential risks.
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How does AI help businesses to respond more effectively to unexpected disruptions?
AI can empower businesses to respond to disruptions with agility and precision. By leveraging AI for inventory management and re-routing, companies can dynamically adjust to real-time changes, supporting business continuity and customer satisfaction. This agility is further enhanced by AI-powered simulations and digital twins, which allow for stress testing and scenario planning. This enables businesses to identify and remediate vulnerabilities, ultimately enhancing overall preparedness.
During disruption, AI has the potential to analyse impacts, for example by identifying which customer bases are affected. Furthermore, as highlighted in Deloitte’s TPRM 2023 Survey, AI-powered tools can shorten procurement and incident response times. They achieve this by rapidly informing risk-related decisions with intelligence from various sources, offering quicker options that consider dynamic scenario impacts against organisational appetite. This capability can improve both the speed and accuracy of a company’s response to an unexpected event.
Additionally, if deployed correctly, AI can enhance the customer experience. For example, AI can alert customers about product delivery delays and offer alternative delivery options via AI chatbots, as well as personalised assistance and communications. In this sense, investment in AI is not only a commercial and strategic decision, but also reputational, with the potential to decrease customer complaints and improve customer retention rates.
While AI tools offer valuable data-driven insights, it should not be relied on in isolation. Human oversight remains crucial, as relying solely on AI can amplify biases, overlook nuances, and lead to unintended consequences, especially for decisions with ethical or strategic implications. As demonstrated in Deloitte’s and Maersk’s recent article on supply chain resilience, a balanced approach combining AI’s analytical power with human judgement and experience yields the most effective outcomes.
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Have you seen a trend of UK businesses increasingly investing in AI for supply chain management and resilience?
Regulations are pushing businesses to be more transparent and accountable in their supply chains. AI-powered supply chain visibility and illumination tools can enable businesses to address these regulatory demands more effectively.
The EU’s Corporate Sustainability Due Diligence Directive exemplifies this shift. In-scope companies are now obligated to demonstrate comprehensive understanding and reporting on ESG impacts across their entire value chain. This includes scrutinising the sourcing practices, human rights records, and environmental impacts of their suppliers. Similarly, the EU’s Deforestation-Free Regulation mandates companies to provide proof that their products are deforestation-free before entering the EU market. This necessitates meticulous supply chain traceability down to the origin of raw materials, compelling companies to gather extensive ESG data from their suppliers. While these examples are EU-centric, their impact is far-reaching. Any company operating within the EU market, including global entities, must comply with these regulations. This underscores that as regulations continue to evolve globally, organisations with international supply chains should prioritise investments in supply chain transparency, potentially leveraging AI tools to achieve this.
Additionally, the current macroeconomic climate is increasing pressure on organisations to demonstrate efficiency and a strong return on investment (ROI) for any new technology adoption, including AI. For many, the perceived benefits of AI must demonstrably outweigh the costs and hurdles, such as financial investment, integration with existing systems, and addressing knowledge and resource gaps. Deloitte’s 2024/5 Global TPRM Survey highlights the importance of securing buy-in from leadership for AI implementation. The survey found that a primary motivator for adopting AI is the potential for cost savings and process efficiencies.
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In which industries do you see AI having the biggest impact on supply chain resilience?
AI’s impact on supply chain resilience will be significant across industries. In essence, any organisation that relies on suppliers or third parties to support the delivery of their critical services could benefit from AI. For instance, AI can optimise sourcing strategies for critical minerals in the energy and technology sector, support the management of material outsourcing arrangements for financial services, enable timely delivery of life-saving medicines in healthcare, and track sustainability compliance for consumer businesses. By leveraging AI’s analytical power, businesses across sectors can proactively mitigate risks, adapt to disruptions, and build more resilient supply chains.
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What measurable improvements have UK businesses seen in terms of cost reduction, efficiency, and risk management after implementing AI solutions in their supply chains?
Deloitte AI Institute’s 2024 year-end Generative AI survey report, reveals a positive Return on Investment (ROI) trend for organisations at the forefront of GenAI adoption. The majority (74%) of respondents indicated that their most sophisticated GenAI initiatives are meeting or exceeding ROI projections. Specifically, to supply chain management, GenAI initiatives surpassing expected ROI for many organisations.
Deloitte’s 2024/5 Global TPRM Survey also highlights that respondents across industries believe that AI-enabled automation could reduce their financial exposure following third party disruption, with a significant proportion of respondents (42%) indicating that this exposure could be reduced by at least 20%.
Conclusion
From anticipating risks to streamlining operations and enhancing compliance, AI enables organisations to strengthen their supply chain resilience. However, the important thing to consider is to adopt AI responsibly, ensuring that human supervision and management remain essential before implementation and in critical decision-making.
