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How can consumers trust AI if they can’t trust the hardware it’s running on? As the AI supply chain expands, the threats posed by sophisticated counterfeits and cyberattacks grow. Protecting transportation and distribution channels is paramount. By creating a verifiable chain of custody to ensure chip integrity, a hardware root of trust replaces reactive strategies.
Need for a silicon-level foundation of trust
The explosive growth of AI has dramatically increased the demand for specialized, high-performance chips. While algorithm quality is still fundamental to the AI supercycle, industry professionals are overlooking a crucial aspect. The entire AI paradigm rests on the unverified assumption that the underlying hardware is authentic and secure.
Existing hardware hardening and software patching strategies do not align with the current state of AI. This technology needs protection as robust and advanced as itself, as compromised chips can subtly manipulate data during training or inference. Alternatively, they can facilitate the theft of a trained model’s intellectual property at the hardware level.
Although timely patching is critical, it is inherently reactive, which often leads to inevitable delays. One research group aggregated data from 132 delayed-patching tasks across multiple companies over four years. They found the standard patch management process takes roughly two months, from information retrieval to post-deployment patch verification.
By MRPeasy 04.01.2026
By Stefan Drouzas, Senior Application Marketing Manager at Rohm Semiconductor GmbH 03.31.2026
By DEEPX 03.27.2026
Electronics manufacturers cannot rely on time-consuming strategies to address security gaps. They need a solution, such as a hardware root of trust, to secure the AI lifecycle by validating boot firmware and managing cryptographic keys. By anchoring cryptographic identities in the silicon at the fab level, engineers create an immutable chain of custody that neutralizes backdoors.
Counterfeiting on the rise
Once AI is embedded across every sector, intelligence won’t be the only thing that connects industries. According to a 2025 report from the Organization for Economic Co-operation and Development, approximately $467 billion in global trade in 2021 alone was driven by counterfeit goods. Electronics accounted for about 10% of the total value. Given that many forged products are never seized, the real figure could be considerably higher.
The market for specialized chips, graphics processing units, and memory is tight, with tech giants fighting over the first shipments. As demand continues to outpace supply, AI chip counterfeits will become increasingly common. Recalls, product failures, and security breaches put pressure on an already strained supply chain, exacerbating the issue.
While specialized electronics are incredibly complex, sophisticated counterfeits match that complexity, making it difficult to tell genuine products from fakes. While they may look legitimate, forgeries are of low quality. They may misbehave or fail prematurely under the strain of resource-intensive training and inferencing, hurting electronics manufacturers’ reputations.
Hardware root of trust prevents malicious or counterfeit chips from running, as they lack the correct cryptographic identity. It also stops rootkits before they even have a chance to start by ensuring only the manufacturer’s authentic, signed firmware can ever be loaded onto the device.
Hardware root of trust secures the AI lifecycle
A hardware root of trust is a small, dedicated, and secure component built directly into an AI processor. Since it is immutable, it cannot be altered or tampered with after it has been manufactured. By baking security into the chip itself, manufacturers could eliminate AI chip counterfeits from supply chains.
This approach establishes a secure chain of trust during the boot sequence. When the device turns on, it is the very first thing to run. It uses the master cryptographic key to check the firmware’s digital signature. Once it ensures the signature is valid, it passes control. The firmware then repeats the process, verifying the operating system’s signature before loading it.
If a signature is invalid at any point, whether due to tampering or counterfeiting, the process halts entirely, and the device refuses to boot. This creates an unforgeable, unbroken chain of verification.
Rather than relying on complex software to check other complex software, a hardware root of trust provides a single small anchor physically baked into the silicon. It establishes a secure state from the very first moment hardware is powered on, making it highly effective. Since it is inherently trustworthy, it provides a foundation for all other security measures.
Securing components supports the AI supercycle
To secure the entire AI device lifecycle in preparation for the AI supercycle, companies must move from reactive patching strategies to chip-level security. Hardware hardening is foundational to root-of-trust schemes.
In addition to implementing hardware root of trust at scale, they must consider broader supply chain concerns. Even if they have complete confidence in this strategy, a comprehensive solution should consider and address every possible risk. As such, the entire component journey must be verifiable, from fabrication to last-mile delivery.
After components are manufactured, they can be tampered with during transit or replaced with low-quality fakes. A physical-digital verification system pairs a chip’s digital cryptographic identity with anticounterfeit solutions.
Tamper-proof labels deter theft and tampering by making any product disturbance immediately clear to shippers and retailers. Many of these labels can double as barcodes, so manufacturers can enhance end-to-end product tracking and streamline inventory management without retrofitting operations.
Hardware root of trust facilitates innovation
Experts say innovating to improve performance is a key driver for chip advancements in U.S. markets. A chiplet architecture may be key for building scalable systems-on-a-chip. It enables the rapid integration of AI acceleration, compute, and memory controllers, thereby enhancing performance and interoperability without bloating budgets. However, security remains an issue.
Chiplets inherently increase the attack surface, increasing the likelihood of cyberattacks. This is especially true for analog and I/O versions, which tend to have weaker key management or less hardened firmware. While this poses a significant threat to component integrity, AI chip counterfeiting is a more pressing concern.
Parts sourced externally, integrated by a third party, or transported through distribution channels may be swapped for a malicious or fake die. The solution is to have one component that anchors them, while all others participate in trust enforcement. This provides a scalable way to secure AI chips without dramatically increasing costs.
Alternatively, manufacturers could give each processor a small, efficient hardware root of trust. If each chiplet receives an unforgeable cryptographic identification, they can establish secure, encrypted communication channels. The primary chiplet—the main processor—can challenge the rest to prove they are authentic and unmodified, establishing a system-wide web of trust.
Hardware root of trust should be nonnegotiable
Should a hardware root of trust be mandatory? While questions related to compulsory specifications can be controversial, they are an essential part of the AI supercycle conversation. Either way, electronics manufacturers should shift their mindset from “trust but verify” to “never trust, always verify.” Combining cryptographic and physical validation checks is crucial.
See also:
Embedded World 2026 Confronts Mounting Integration Complexity