Agentic AI boosts speed and efficiency, but it also expands the attack surface in your extended supply chain. To reduce the threat, organizations must build in resilience from the ground up.
By: Dave Dimlich
President of SD3IT
Supply chains have always been about speed, efficiency and cost—getting the goods where they need to go as quickly and inexpensively as possible. Artificial intelligence, particularly agentic AI, is now poised to kick the supply chain into a higher gear, ramping up performance by making thousands of decisions faster than any human team could.
But there is a potential threat lurking outside most companies’ field of vision, down in the depths of the supply chain. Those lightning-quick decisions can involve downstream or upstream partners whose security may be lacking, resulting in compromises that can spread quickly throughout the chain. The damage from such attacks, including to business bottom lines, organizational reputation or the costs of paying ransoms and repairing systems, is significant.
The answer isn’t reducing automation or turning away from the immense potential benefits of agentic AI. The answer is in designing and implementing autonomous operations that are resilient from the beginning.
The Invisible Supply Chain
AI promises to improve even the most smooth-running operations. Orders can be rerouted automatically, inventory can be rebalanced in real time, and software updates can move continuously across interconnected platforms. AI-driven systems also can help organizations respond to disruptions faster than ever before, in some cases by anticipating them before they even happen.
Meanwhile, organizations are beginning to get smarter and more careful about implementing AI. As they move beyond pilots and begin to deploy autonomous, agentic AI capabilities at scale across logistics, procurement and operations, organizations are acknowledging the risks posed by AI, especially when deployment outpaces security. Many are now working to implement AI governance frameworks that include risk management, strategy and audit capabilities.
That’s well and good, even if most organizations have a lot of work ahead in making agentic AI safe and secure. But while taking care of in-house concerns, a blind spot persists in managing the risks in the vendor and third-party ecosystem. The growing expanse of supply chains, along with the fact that so many systems in the chain are interconnected, have made supply chains a prime target for cybercriminals and nation-state actors. Attacks have been surging in recent years. It’s not just notorious attacks like SolarWinds and Log4j, but attacks that are happening across the board. The rate of supply chain attacks doubled from 2024 to 2025, building on earlier increases, such as the oft-cited 431% surge from 2021 to 2023.
AI Puts Blind Spots Into Play
Most organizations have a solid understanding of their direct suppliers. They know who provides their software, cloud infrastructure and logistics services. But they may not have visibility into the additional layers behind those providers, which extend well beyond the vendors listed on procurement contracts.
The potential threats from those layers are accelerated by agentic AI systems, which, by design, don’t operate in isolation. They rely on open-source software, pretrained models, APIs, cloud platforms, orchestration tools and data services. Each dependency introduces another layer of implied trust, and each layer expands the operational environment—and the attack surface.
Threat actors have begun exploiting AI-enabled environments with increasingly sophisticated techniques. Some target the software supply chain by inserting malicious code into trusted repositories. Others compromise automated development pipelines or manipulate AI models before organizations deploy them.
Not every disruption is malicious, of course. Inaccurate inventory information, incomplete logistics data or unexpected changes within supplier networks can lead AI systems to make highly confident but incorrect decisions. Without proper oversight, those decisions can cascade through procurement, inventory management and distribution before anyone has an opportunity to intervene.
Meanwhile, shadow AI creates another layer of vulnerability, both within your organization and others in the supply chain.
Taken together, that hidden, vulnerable ecosystem creates risks that traditional supplier management programs weren’t designed to address. A vulnerability in an AI model repository, an outage at a cloud provider or a compromised software dependency can quickly ripple through automated workflows before anyone realizes there’s a problem.
Building Trust Into Autonomous Operations
Applying supply chain security can seem like an intimidating prospect, but it starts with several clear steps you can take to build resilience into the enterprise, in addition to a strong governance framework that applies to all of an organization’s uses of AI.
Zero Trust Principles: Organizations should start by extending zero trust principles beyond users and devices to include AI agents, models and automated workflows. Every automated action should operate within clearly defined identity, authorization and monitoring controls. Taking steps such as implementing multi-factor authentication (MFA), least privilege policies and network segmentation can help build a zero trust environment. At SD3IT, we take a data-centric approach to giving cross-domain and multi-tenant environments a zero trust foundation, protecting data at rest or in transit regardless of its location.
Visibility: Software Bills of Materials (SBOMs) have become an important tool for understanding software dependencies. As AI becomes more deeply integrated into enterprise operations, organizations should also seek greater transparency into AI models, training data, third-party APIs and external services that influence automated decisions. AI Bills of Materials (AIBOMs) are becoming essential for AI supply chain security and regulatory compliance.
Continuous Monitoring: Periodic assessments just won’t cut it anymore. Autonomous environments change too quickly for annual reviews or occasional audits to provide meaningful protection. Organizations need real-time awareness of system behavior, supplier changes and emerging risks across their technology ecosystem. AI-enabled threat detection and threat hunting can bolster overall security.
Humans in the Loop: Finally, human judgment still matters. The most resilient organizations establish human-in-the-loop governance for any decisions involving mission outcomes, financial commitments, compliance requirements or customer impact. AI should accelerate decision-making, not eliminate accountability. It can’t be trusted without human oversight.
Turning Trust Into an Operational Advantage
Autonomous supply chains have become a clear competitive advantage. AI, in fact, makes supply chains more resilient. But it also introduces risks that, when exploited, can impact hundreds or even thousands of companies, the threat of which can give ransomware operators leverage while making their demands.
Organizations that successfully combine AI, automation and resilient architectures will respond to disruptions faster, optimize resources more effectively and adapt to changing conditions with greater confidence.
At SD3IT, we help organizations integrate AI into existing identity, access management and zero trust architectures (ZTAs) rather than treating AI as an exception. By building visibility across systems, securing collaboration among partners and embedding governance into operations, we help organizations deploy AI with confidence while maintaining control over their data and missions.
The organizations that succeed will not necessarily be the ones that automate the fastest. They will be the ones that build trust, accountability and resilience into every layer of the supply chain before autonomous systems begin making decisions at scale. Because autonomous supply chains don’t fail simply because they automate decisions. They fail when organizations automate trust without understanding where that trust begins, where it ends and what happens when it breaks.
At SD3IT (Solution Driven, Designed and Delivered Technology), we help government and commercial organizations deploy emerging technologies that improve mission performance without sacrificing security, resilience or operational control. Our experts integrate AI, zero trust, cybersecurity and modern infrastructure into practical solutions that enable organizations to innovate with confidence. Learn more at SD3IT.com.