Supply chains are under enormous stress. As supply chain leaders, we’ve seen unprecedented levels of disruption, challenges with our ecosystem trading partner networks, tariff wars, real wars and tremendous turnover in human capital. Senior supply chain leaders are retiring in record numbers. Welcome or not, large scale change is afoot in our profession. And just when we thought things were on their way back to a new “hybrid” normal, a curious new technology in generative AI seems poised to upend the world of operations yet again.

Across media headlines, we see dark warnings about the existential risk of generative AI technologies to our culture and society. Yet as supply chain innovators, we know there is a rich history of applying technologies to continuously optimize operations. Is generative AI likely to drive an “extinction event” for supply chains as we know them? We think not. The fundamental nature of supply chain is evolutionary, and it has been that way since our craft was born out of the Toyota Production System in the 1950s. In supply chain, we take intentional but measured risks; we don’t swing for the fence.

As our profession looks to apply generative AI, we will undoubtedly take the same approach. With that mindset, we see the potential for step change improvements in efficiency, human productivity and quality. Generative AI holds all the potential to innovate beyond today’s process, technology and people constraints to a future where supply chains are foundational to delivering operational outcomes and a richer customer experience. But we must choose to embrace this new technology and make it part of the fabric of everything that we do.

A new and exciting wave of disruption

Let’s get one thing clear right from the start: generative AI is unlike any technology we’ve ever seen before in supply chain. It’s a game changer. Do not be tempted to discount generative AI as another Radio Frequency Identification (RFID), Blockchain or other “hype cycle” technology. Over the next five years, generative AI will fundamentally change the way we work in supply chain. It will automate out the dull, menial and transactional work that consumes an enormous amount of low value add time for our professionals. Far from eliminating human value, it will elevate the role of our people and empower them to run the business on a predictive, proactive and forward-looking basis.

Despite the tremendous investment our supply chains have received over the last several decades, today they still demonstrate the need for significant reinvention. Many supply chain structures remain functionally siloed and struggle to execute predictably end-to-end. Applications and data are often trapped within departmental boundaries. Multiple ERP instances create challenges with fragmentation of orders and commitments across disparate systems. These combine to create unnecessary costs, increased execution latency and a suboptimal customer experience. There simply isn’t enough time or investment to uplift or replace these legacy investments. It is here where generative AI solutions (built in the cloud and connecting data end-to-end) will unlock tremendous new value while leveraging and extending the life of legacy technology investments. Generative AI creates a strategic inflection point for supply chain innovators and the first true opportunity to innovate beyond traditional supply chain constraints.

Pivoting from ideation to action

A leading supply chain needs to be orchestrated across the value chain. Internal and external stakeholders need fast and accurate information at their fingertips to plan, manage and direct supply chains. To drive personalized actions, insights and visibility, large volumes of data (ERP, WMS, RFID and visual analytics) need to be ingested, normalized and analyzed at high speeds. The need for agile, resilient and competitive supply chains has never been greater than today.

Addressing these challenges requires a platform that enterprises can own, shape and scale per the business needs. At IBM we have embraced a hybrid cloud, component-based architecture that is built on open technologies. Ingesting high volumes of data at speed and contextualizing them to each persona is a given. The “machine” learns, thinks and executes repetitive tasks while allowing supply chain professionals to focus on high impact business events.

The advent of generative AI will transform the ways we think and work. Traditional solutions constrain users in how to engage, utilize and investigate the large volumes of enterprise data. Frequently, the data is hard to even access. While chat bots have attempted to make it easier to get information, they rely on extensive model training and are frequently limited to “how to” questions. Generative AI brings the force of machine learning to everyday tasks by leveraging foundation models that allow users to interact with structured and unstructured data like never before. What took months of training takes just days now. Our supply chain digital assistant allows users to interact with data conversationally to interrogate vast transaction data, such as hundreds of thousands of documents and visual images. Users can go from getting an overall picture of the health of the supply chain to understanding a specific transaction by just asking. They get contextual information as well as factual data (PDFs, visual images, RFID tags information). A question from a supply chain manager (“Where do I have excess inventory?”) or a buyer (“How is my vendor performing?”) becomes a simple question rather than a complex exercise in bringing disparate reports together.

By establishing a common platform for all stakeholders, orchestrating the supply chain becomes intrinsic to everyday tasks and processes. Building on the core foundation, enterprises can deploy generative AI-powered use cases, allowing enterprises to scale quickly and be agile in a fast-paced marketplace.

IBM’s supply chain AI journey

A few years ago, in IBM’s own infrastructure supply chain, we decided that conversational AI could help overcome boundaries between different supply chain domains and provide a collaboration platform with our sales teams, suppliers and partners. On this platform, any authorized user could access critical information in an intuitive way, using natural language. We were able to achieve an easy-to-access, real-time, single view of truth with immediate insights to manage the client experience, operate with resilience and react to market disruptions. Despite major disruptions and dislocations in the COVID and post-COVID worlds, IBM’s supply chain fulfilled 100% of its orders and delivered on its promises.

Integrated generative AI accelerates intuitive conversations between supply chain decision makers and virtual assistants, enabling fast and fact-based actions. These innovations empower supply chain professionals to focus on complex problem resolution, the continuous improvement of our workflow designs and augmenting AI models. Adding generative AI and the power of foundational models to the existing solution is a natural step in the evolution of our supply chain capabilities.

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