Sai Buddhavarapu on the power of generative AI in supply chains

Sai Buddhavarapu on the power of generative AI in supply chains

Generative artificial intelligence solutions are helping manufacturers cope with supply chain pressures, says Blue Yonder’s vice president of product management  

Amber Hickman |

For supply chain professionals, success is reliant on good planning. But volatile market conditions and a proliferation of data are making this increasingly difficult. 

“With supply chain solutions spanning vast networks with diverse data silos, it often becomes a daily struggle to navigate the massive amounts of data across various systems and make real-time, context-aware plan adjustments,” says Sai Buddhavarapu, vice president of product management at Blue Yonder. “Furthermore, the past few years of extreme ebbs and flows have placed unprecedented pressure on supply chain planners, resulting in a record-high burnout among supply chain professionals.” 

To overcome these issues, many manufacturing organisations are looking to implement technology-based solutions, with many also beginning to realise the value of deploying bots powered by generative AI into supply chain operations. 

“With proper training and with the right guardrails, generative AI can be a trusted navigator to augment decision-making and guide staff through complex processes, quickly collating information from the organisations and sorting it into data-driven insights,” says Buddhavarapu. 

“Blue Yonder Orchestrator combines the power of generative AI, the natural language capabilities of LLMs, and the depth of Blue Yonder’s supply chain solvers to address these challenges, delivering dynamic decision-making and orchestration.” 

Integrated within Blue Yonder’s Luminate Cognitive Platform, Blue Yonder Orchestrator pulls data from all relevant sources before determining correlations and delivering easy-to-read insights and recommendations for the user. The solution can then execute the decisions using a range of execution microservices. 

The number of case studies for generative AI may be growing, but there are still risk factors involved that organisations should be aware of, including concerns surrounding data and security. 

“Securing generative AI necessitates a multi-layered approach encompassing data, model training and fine-tuning, infrastructure, access control and diligence when evaluating vendors,” says Buddhavarapu. “Moreover, implementing comprehensive governance, rigorous access control, input and output controls, monitoring, sandboxing and well-thought-out development is imperative.” 

Security features in Blue Yonder’s solutions are developed upon foundations laid by Microsoft. 

“We rely on Microsoft’s deep expertise in enterprise-grade security and its leadership in the generative AI space to provide a robust security layer upon which we can build and add more controls,” says Buddhavarapu. “We are leveraging the enterprise-grade security of the Azure OpenAI service which guarantees data is not shared outside of the organisation or with OpenAI.” 

One commonly cited drawback to generative AI are ‘hallucinations’, where the AI delivers misleading or incorrect information as fact. 

“Addressing hallucinations is a natural part of working with large language models (LLMs) and to tackle these we use a form of templates called playbooks, which guide precise responses,” explains Buddhavarapu. “We are also combining retrieval augmented generation and LLM fine-tuning using Blue Yonder-specific data, documents and model constructs.” 

So how might generative AI provide added support for the supply chain professional in the future? 

Buddhavarapu says: “Granting autonomy to generative AI is the logical next step. Time-sensitive problem-solving could be an excellent first use case for granting agency to generative AI for recurring or predictable events.” 

For example, if a logistics planner is troubleshooting a delayed shipment, they can turn to a generative AI assistant that can rapidly evaluate shipment options and discover a viable alternative based on current market conditions. 

“The generative AI conducts all the upfront work, and all that’s required from the planner is a final sign-off,” says Buddhavarapu. “Given the magnitude of disruptions in today’s supply chains, this technology makes an ideal tool to address these challenges at scale.” 

This article was originally published in the Winter 2023 issue of Technology Record. To get future issues delivered directly to your inbox, sign up for a free subscription

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