Every year, millions of people walk through Garrett walk-through metal detectors and get scanned with our hand-held detectors at airports, schools, stadiums, and courthouses. Each of those screenings depends on one thing: the detector has to work the same way every time.
As an industry leader in security metal detection, we take that responsibility seriously, because the safety of our customers and the public depends on it. AI creates a real tension for security teams. It promises more powerful detection, but AI that goes unchecked can make a system less predictable. Not every manufacturer handles that tension the same way.
At Garrett, our position is clear: we use AI to build better detectors, and we use strict AI quality control so AI never makes them less reliable. We’ll walk you through how we use AI in design, why we lock down our software, how human oversight and testing work, and how we protect data.
Key Takeaways
- At Garrett, we use AI only during product development, never as an unsupervised decision maker inside finished detectors.
- Detector software is locked after design and testing, so performance never drifts after installation.
- Locked software keeps a site’s own application testing meaningful for the life of the detector.
- Experienced engineers review and approve every AI output before it reaches a product.
- AI-assisted designs are tested against standards for safety, detection performance, security, and operational effectiveness.
- Encryption, on-premises development, and consent-first data practices keep algorithms and customer data protected.
Why Reliability Matters More Than Novelty in Security Screening
In security screening, new is not always better. A feature that sounds impressive means nothing if it makes a detector harder to trust, which is why reliability guides every design choice we make. Lives can depend on equipment that performs the same way every day, and we never forget that.
What Security Teams Need From a Metal Detector
After decades of building detectors for the world’s most demanding checkpoints, we know what security professionals value most. They want steady, proven performance far more than flashy features. Their needs come down to a few basics:
- The same detection performance on day one and day one thousand
- Results they can verify through their own application testing
- Confidence that the equipment won’t change behavior without their knowledge
- Predictable operation that supports staff training and procedures
When a detector meets all four needs, teams can plan staffing and procedures with confidence. If any one of them fails, the whole screening process and the people it protects are at risk.
The Hidden Risk of “Smart” Detectors That Keep Learning
Some AI-driven systems keep learning and adjusting on their own after they leave the factory. Engineers sometimes call this adaptive or self-adjusting behavior. The system watches what happens around it and changes how it works based on what it sees. That might sound like progress, but it can create serious problems.
A self-learning detector could perform well at installation, then slowly drift because of outside factors the end user never asked for, such as threat trends and mistaken associations. That drift is unacceptable at airports, schools, stadiums, courthouses, and other high-stakes checkpoints, where a missed threat or a wave of false alarms has real consequences. This is where Garrett draws a firm line.
How Garrett Uses AI to Build Better Walk-Through and Hand-Held Detectors
AI helps our engineers explore more design options and solve hard problems faster. The key is that we use it during product development, never as an unsupervised decision maker inside the finished detector.
AI as a Design Tool, Not an Autopilot
AI extends what our engineers can do, helping them build more power and usefulness into each product. Think of it like a powerful calculator for complex design work, not a pilot that takes over the controls. AI’s role is focused on the development phase. During this stage, every AI output can be studied, tested, and refined long before a product reaches a customer.
This gives our engineers time to catch weak spots, compare results, and make improvements in a controlled setting. Nothing AI suggests goes out the door until our team understands and approves it.
What This Means for Walk-Through and Hand-Held Detectors
For our walk-through detectors, AI-assisted design can help improve discrimination between threats and harmless personal items, throughput at busy checkpoints, and accuracy in pinpointing where an object is on the body. Better discrimination means fewer nuisance alarms from keys, belt buckles, and phones, which keeps lines moving.
For hand-held detectors used in secondary screening, AI-assisted design can help refine sensitivity and responsiveness so officers resolve alarms faster. In both cases, improvements are built in during development, then fixed in place. The performance a customer sees on day one is the performance they get for the life of the product. With Garrett, enhanced capability never comes at the cost of consistent behavior.
Ready to upgrade your screening? Explore our walk-through and hand-held metal detectors, built with responsible AI and strict quality control. Each one delivers the reliable performance your team and the public can count on.
The “Locked-Down” Approach: Our Core Quality Control Safeguard
Our most important safeguard is simple. After a product is designed and tested, its software is locked down, so customers never have to wonder whether their detector has changed on its own. Where others may treat AI itself as the selling point, we treat proven, unchanging reliability as the selling point.
Designed With AI, Then Never Open Loop
Once development is complete, product software is locked so it performs at a consistent level. Performance always traces back to initial development, never to changes made after installation. An open-loop AI system, by contrast, can change itself based on new inputs without a person checking those changes first.
We refuse to use open-loop AI in our security products because it removes the predictability security teams depend on. AI increases capability, but the system stays closed and controlled. The table below shows how the two approaches compare.
| Feature | Open-Loop AI System | Garrett Locked-Down Approach |
| When AI is used | During development and after installation | During development only |
| Changes after installation | Can adjust itself without user input | Software stays fixed |
| Source of performance | May shift based on outside factors | Traces back to initial development |
| Human review of changes | Not always required | Required for every AI output |
| Value of customer testing | Can lose meaning over time or require continual monitoring | Stays meaningful for the product’s life |
Performance You Can Verify
End users learn how a detector behaves through their own application testing. They walk test items through the detector, check alarm responses, and confirm the settings fit their site. Many sites repeat these tests on a regular schedule to confirm everything is working as expected.
Locked software means those results stay meaningful over the life of the product. A test performed today still describes how the detector will perform next year. That gives security leaders solid ground for decisions about staffing, procedures, and audits.
Human Oversight and Rigorous Testing
AI is powerful, but it does not replace human judgment. At Garrett, no algorithm has the final say, and every improvement must prove itself before it ships. Our process combines expert review with careful testing so nothing is left to chance.
Skilled Engineers Keep Humans in the Loop
AI-enhanced design results are never put into products through automated or unsupervised methods. Experienced engineers review and approve every AI output used in product or service design, asking whether it makes sense, whether it is safe, and whether it meets our standards. If an output does not hold up to that review, it simply does not get used.
Human judgment catches problems AI may miss. An experienced engineer understands the physics behind the technology and the real-world setting of a school entrance or a courthouse lobby in ways an algorithm or checkpoint staffer cannot. Keeping highly-skilled humans in the loop also means accountability stays with people, not algorithms.
Testing Against Industry Standards
We apply extensive testing to any intellectual property or technique produced with AI, in the lab and in real-world conditions. AI work products must prove they are effective and suitable before we use them. Our products are then assessed under appropriate standards in four key areas:
- Health and safety
- Detection performance
- Security
- Operational effectiveness
Meeting these standards confirms that AI-assisted design has improved our products without creating new risks. It also gives security buyers a clear, shared way to compare equipment.
Protecting Detection Algorithms and Customer Data
Detection algorithms and customer data are valuable, and in the wrong hands, they could be used to defeat security screening. That is why we treat data protection as part of public safety, not an afterthought. The table below summarizes our key protections.
| Safeguard | What It Protects | How It Works |
| No off-premises AI exposure | Customer data and sensitive security information | Sensitive data is kept off outside AI platforms |
| On-premises development | Private development work | In-house resources are used when privacy requires it |
| Encrypted software | Proprietary detection technology | Product code is encrypted in every deployment |
| NDAA-compliant cameras | Visual data that algorithms may interpret | All cameras in Garrett products meet NDAA requirements |
| Consent-first practices | Potentially sensitive client data | Data is collected for development only with express consent |
Keeping Sensitive Security Information Away From Bad Actors
Customer data and sensitive security information are never exposed to off-premises AI platforms. Outside AI tools may store or reuse the information they receive, and we will not take that risk with security data. Detection-related algorithms and capabilities are also never exposed to the public or to bad actors.
When privacy requires it, we use on-premises development resources so sensitive work stays within systems we control. This keeps the details of how our detectors find threats out of reach of anyone trying to get around them.
Encrypted Code, NDAA-Compliant Cameras, and Consent
Our product software is encrypted to protect our most advanced technology in every deployment. Encryption makes it very difficult for anyone to read, copy, or tamper with the code, and it helps ensure the software running in the field is exactly what we designed and tested.
In addition, all cameras in Garrett products are NDAA compliant. The National Defense Authorization Act sets rules about which camera components can be used in certain settings, and following it protects the visual data that AI-built algorithms may interpret.
We also do not collect potentially sensitive data for our own development without express client consent. Our customers own their information, and we respect that. Security teams can work with us knowing their data will not be used in ways they didn’t approve. It is one more way we hold ourselves to a higher standard.
Why This Approach Makes Garrett an Industry Leader
Many manufacturers are racing to add AI to their products. At Garrett, we lead a different way: carefully, responsibly, and always with public safety first. We believe the companies that use AI responsibly will be the ones security professionals trust most.
Trust and Compliance as the Foundation
Our standard is to earn the confidence of security professionals and the crowds they protect. Our AI policy and its implementation align with relevant legal, regulatory, and industry requirements. Every customer can count on these commitments:
- Products designed with AI and approved by experienced engineers
- Software that stays locked after installation
- Data and algorithms that stay protected and private
- Practices that follow applicable laws, regulations, and standards
Responsible AI is what sets us apart, not something that holds us back. Customers choose equipment they can depend on, and strict control lets us deliver products that are both more capable and more dependable.
Responsible AI Across the Whole Company
Our principles don’t stop at product design. AI used in non-product business functions follows the same rules for privacy, risk management, and compliance.
Whether AI is helping with internal operations or customer service, the same values apply. That consistency means customers get the same level of care at every point of contact. As AI rules continue to change, we review our practices to keep them current.
A Quick Note on Garrett Sport Detectors
The same principles of human oversight, testing, and data protection guide how we use AI in our detectors for treasure hunters and hobbyists. These products face different challenges than security equipment, but they deserve the same care. Whether you are screening visitors or searching for coins at the beach, you can count on the same commitment to quality.
Conclusion: Smarter Design, Unchanging Reliability
AI makes our walk-through and hand-held metal detectors more capable, while locked-down software, human review, and rigorous testing keep them dependable. Each part of our process supports the others, so no single step carries the full weight of reliability.
That balance is how AI quality control is making security metal detectors more reliable, not less, and it is why security professionals around the world choose Garrett. The safety of our customers and the public will always come first.
If you have any questions about how we use AI or which detector is right for your site, contact our team today. You can also request a demo or explore our full lines of walk-through and hand-held metal detectors.
Want to see exactly how we put these principles into practice? Read our full AI policy to learn how Garrett uses AI responsibly to protect your security, your data, and the people you serve.