The Role of Network Resilience in AI-Enabled Supply Chains

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Driven by global reach, today’s supply chains span continents and rely on the right coordination across countless stakeholders. These continent-spanning networks comprise many parties—including brokers, shippers, and warehouses—who must communicate effectively to ensure timely and accurate deliveries.

Like a house of cards, these supply chains are incredibly sensitive, with one minor disruption having cascading effects that put everything behind schedule. As such, an increasing number of organizations are turning to artificial intelligence tools and applications to overcome these challenges and better manage their global supply chains.

The Transformative Impact of AI on Supply Chains

AI has transformed logistics and supply chains in several notable ways, from reducing costs and enhancing efficiency to eliminating manual processes. AI’s transformative power lies in its ability to organize, analyze, and compare vast amounts of data from various sources, including real-time insights from Internet of Things (IoT) sensors and historical records. In addition to automating these tedious data-related processes, generative AI applications can produce curated suggestions for supply chain managers, allowing them to make quick decisions.

AI algorithms and machine learning (ML) can examine historical data, market trends, and other factors to provide accurate demand forecasts to supply chain managers. These precise demand forecasts help supply chain managers optimize inventory and production plans across multiple locations, reduce overstock and stockouts, and accurately predict transportation needs.

AI also supports route optimization, which is becoming increasingly important as enterprises come under scrutiny for the effects trucking and freight have on the environment. Like demand forecasting, AI tools can analyze traffic patterns, weather, and delivery constraints to generate route plans and schedules that are fuel- and time-efficient. Supply chain managers can likewise use AI to introduce greater transparency to shipment tracking for customers and other entities.

Network Outages: Why They Happen, and the Consequences

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While integrating AI into logistics and supply chain processes is essential for staying competitive and maintaining strong customer relationships, enterprises must also prioritize building a resilient network to support these AI-enabled applications and ensure business continuity, especially during inevitable disruptions and outages.
Network outages compromise AI performance and jeopardize the various logistics applications they support. A variety of reasons can cause an outage, with the most common culprits being ISP carrier issues, human error (like misconfigurations), and data breaches. Harsh environmental conditions and natural disasters can also cause outages.

But as AI systems grow more complex, they introduce new points of failure that go beyond traditional outage causes, with even the slightest misconfiguration being enough to cause a network-wide outage that impacts access to critical applications. AI traffic also places a considerable strain on network infrastructure. Unlike traditional enterprise workloads, AI workloads involve high-volume data transfers, burst traffic patterns, and frequent synchronization. These all contribute to greater network congestion and delay management traffic, ultimately impeding administrators’ ability to troubleshoot issues.

Whatever problem causes a network outage, the consequences are equally devastating financially and reputationally. Critical AI tools and applications become inaccessible during outages, causing everything from reporting errors and reduced productivity to financial losses and late shipments. In particular, AI clusters can become unavailable during outages, impeding vital model training and development.

How Out of Band Management Can Make Networks More Resilient

Businesses must implement purpose-built infrastructure to increase network resiliency amidst disruptions so that their supply chain and logistics personnel can always access key AI applications. Out of band (OOB) management, for example, is a powerful network solution that can help administrative teams bolster network resilience and increase productivity.

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OOB management allows administrators to separate and containerize the functions of the management plane so that it can operate independently from the primary in-band network. Administrators can then use this independent network to remotely access, manage, and troubleshoot network infrastructure. Teams can still access infrastructure when the primary network goes down, safeguarding uptime for critical AI applications. If administrators don’t have an independent OOB network, they could get locked out during an outage, making remediation more difficult.

The benefits of an OOB management solution go beyond troubleshooting because it provides administrators with a full view of their infrastructure, giving them real-time, critical, and actionable insights into the health of their network. OOB management also helps administrators manage distributed networks more effectively via remote firmware updates, system resets, and security policy enforcement. Considering the massive and far-flung nature of today’s supply chains, the ability to update devices or install new firmware remotely is invaluable in terms of cost and time.

AI Investment and Network Resilience Go Hand-In-Hand

As organizations double down on AI to optimize their supply chains, the need for resilient, always-on network infrastructure becomes just as critical. Similarly, companies keep deploying other technologies like ML and IoT devices alongside AI to further augment and enhance their supply chains. These technologies are essential to streamlining operations, minimizing cost, and maximizing service. Yet all of these innovations require uninterrupted connectivity. To ensure modern supply chains are as efficient and robust as possible, businesses must simultaneously invest in AI and network resilience solutions like OOB management.

About the Author

Tracy Collins is VP of Sales, Americas at Opengear. Tracy has over 25 years of experience in leadership positions in the IT and Infrastructure industry. Prior to joining Opengear, Tracy led the Americas business for EkkoSense, the leading provider of AI/ML software that allows data center operators to operate more efficiently. Prior to joining EkkoSense, Tracy was the CEO of Alabama based Simple Helix, a regional colocation data center operator and MSP. Tracy spent over 21 years with Vertiv, in various leadership positions including leading the global channel organization. Tracy has an extensive background in sales leadership, and channel development with a strong track record of driving growth while improving profitability. Tracy holds both a Bachelors of Science, Business Administration, and a Masters of Science in Management from the University of Alabama – Huntsville.

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