PERSPECTIVE
Supply chain networks in the age of generative AI
Turning promise into performance
10-MINUTE READ
February 5, 2024
In brief
- The age of generative AI continues to drive radical change across industries — and the pace is accelerating.
- Across end-to-end supply chain networks, CSCOs can capitalize on this reinvention of the way people work, access data insights, and generate information.
- Our report explores the enormous potential in everything from design and planning, to sourcing and manufacturing to fulfilment and service.
Welcome to the generative AI supply chain
How can your end-to-end supply chain network capitalize on the promise of generative AI?
Generative AI has taken the world by storm. Its massive potential has captured the attention of business leaders across industries, with 95% of executives agreeing it will be transformative for their company. And 100% anticipating workforce changes as a result.
The implications for supply chain leaders? There are countless opportunities to apply generative AI across end-to-end supply chain networks. Performance gains are waiting to be tapped in everything from sourcing and planning, through manufacturing and fulfilment, to aftersales and service.
There’s also significant cross-functional value to be gained in areas like sustainability, customer-centricity, supply chain resilience and supply chain data analysis.
Supply chain leaders that recognize this can act quickly to capitalize on generative AI’s rapid acceleration — and turn today’s immense promise into resetting the performance frontiers of tomorrow.
According to Accenture research:
43%
of all working hours across end-to-end supply chain activities could be impacted by generative AI.
29%
of working hours across supply chains could be automated by generative AI.
14%
of working hours across supply chains could be significantly augmented by generative AI.
Why is generative AI so powerful?
Generative AI promises to be the ‘missing link’ that helps bridge the gap from the linear supply chains of the past to the truly interconnected, intelligent supply chain networks of the future. Building on previous advances in supply chain management artificial intelligence — in areas like control tower visibility — generative AI offers a range of new capabilities:
- Contextual understanding. Enhances forecasting and decision-making with contextualized insights from larger volumes of previously inaccessible unstructured data.
- Conversational capabilities. Streamlines access to insights and creates new automation opportunities through user-friendly interactions with AI agents in everyday language.
- Content generation. Capable of creating relevant and usable content for augmenting and automating tasks in areas like sourcing, procurement, customer service and more.
Generative AI is empowering supply chain talent to operate in smarter ways, think more strategically and drive even greater business value.
Generative AI’s impact
Opportunities across end-to-end supply chain network operations:
Generative AI can streamline design processes, using historical and external data sources to rapidly produce new designs to specification, reducing time and repetitive effort. Examples include generating new sustainable packaging designs.
Generative AI democratizes supply chain network insights, transforming the way people interact with planning tools and data. Examples include easier access to advanced data analytics tools and using new data sources to improve forecasting.
Generative AI can streamline sourcing and procurement processes, generate new insights and increase automation of routine tasks. Examples include user-friendly chatbots for simpler buying, auto-generating purchase orders and drafting RFx documents.
Generative AI offers new insights and automations to drive up operational excellence across manufacturing. Examples include faster and simpler access to technical manuals, auto-generating maintenance plans, and drafting compliance documents.
Generative AI elevates fulfilment operations, offering new insights that help create more personalized customer experiences. Examples include faster access to forecasting analytics, as well as streamlined shipping processes and documentation.
Generative AI helps customer support agents access contextualized information and resolve incidents faster. Examples include intelligent copilots that summarize customer incidents, detect issues, recommend resolutions and compose responses.