AI and the Inspector’s Eye

Imagine an inspector on an offshore platform. The year is 2030, and a drone navigates a structure called the flare boom to detect structural anomalies. The drone utilizes sensors that process terabytes of data, which are sent to a small console. Within seconds, the onboard artificial intelligence (AI) flags a faint irregularity in the main structure — an anomaly pattern in an attachment supporting tons of steel and positioning the flare outboard and safely away from crew quarters and processing equipment. The inspector leans forward to study the readout and smiles. It’s not a crack; it’s just surface reflection from moisture collecting in a weep hole caught in the early morning sunlight. The AI saw everything. The human understood what mattered.

This moment captures the essence of the future of inspections. AI will not replace inspectors — it will empower them to be even more effective than they might otherwise be. The beating heart of inspection has and will continue to be human judgment: the ability to weigh evidence, understand context, and protect people and infrastructure. In the coming decade, AI will serve as an aid, not a threat. AI will be the precision tool that magnifies the inspector’s reach, accuracy, and value.

Inspection Is Evolutionary

From the early days of inspection, the practice has evolved as new technologies allowed for better preparation and more effective inspections. In the early days of my journey, we used hand tools, flashlights, and experience. We kept notes in worn notebooks and carried an unsettling feeling about something called ultrasonic testing (UT) — an obvious scam that would never be generally accepted by industry.

Just as radiographic testing (RT) and UT didn’t end visual inspection, they redefined what seeing meant. Phased array ultrasonic testing (PAUT) and acoustic emission testing (AET) further expanded the inspector’s ability to see the internals of complex structures and focus on interpreting and assessing rather than simply locating. These innovations caused the inspector to learn new skills in waveform interpretation and validation.

AI is simply the next evolution of the same continuum. The cloud-based algorithms and machine learning systems now being introduced aren’t a new species of worker; they’re the next generation of tools. They expand the capabilities of experienced inspectors and increase their value to ownership.

Fear and Reality

Fear of replacement has been with us since the earliest development of automation. AI can now recognize weld defects in radiographs, identify corrosion from drone images, and even predict failure before it occurs in specific systems. The difference is that automation in inspection is not the same as autonomy. AI lacks a fundamental aspect: contextual understanding.

AI can detect an anomaly, but it cannot determine if that anomaly is relevant. It doesn’t understand the service environment, the design basis, or the consequences of failure. It doesn’t know when to shut down the process or when to request secondary verification. That kind of judgment — ethical, situational, and deeply human — remains the inspector’s responsibility.

In practical terms, AI is most powerful when it handles the tedious and repetitive aspects of the job, such as sifting through thousands of images, comparing signals, and identifying statistical outliers. By automating data collection and initial analysis, AI enables the inspector to focus on interpretation, decision-making, and communication. Within such a system, the inspector handles tasks that require experience, intuition, and accountability.

Imagine the fatigue of manually reviewing hundreds of radiographic images during a 10-hour shift. Now imagine having AI prescreen those images and highlighting just the 3% or so that may require closer examination. The inspector is still in charge but is now armed with time, clarity, and focus.

The Hybrid Inspection Team

Soon, we can imagine a seamless collaboration between humans and intelligent systems. A possible workflow is illustrated in Fig. 1.

In this model, the inspector isn’t just a technician. The inspector becomes the decision-maker, a risk manager, a data interpreter. The work becomes more analytical, less repetitive, and ultimately more impactful. The inspector’s role evolves from finding flaws to ensuring integrity. This partnership is already visible in industries ranging from aerospace to energy. AI systems are already assisting inspectors in visual inspections, corrosion mapping, pipeline integrity testing, and tank farm leak detection and mitigation. Yet even the most advanced models require continuous validation and oversight. When an algorithm flags a potential defect, it’s the certified inspector — trained and certified under standards such as AWS QC1, Specification for AWS Certification of Welding Inspectors, or ASNT Recommended Practice SNT-TC-1A, Personnel Qualification and Certification in Nondestructive Testing — who confirms the finding, interprets its significance, and signs the report.

Training and Certification in the AI Era

For the partnership to be effective, training must evolve in tandem with the technology. Tomorrow’s inspectors will need a blend of traditional nondestructive examination skills and new digital competencies. Understanding how AI works, its capabilities, and its limitations (not necessarily how to code) will become a core professional skill.

Future training programs will likely emphasize the following elements:

• Data literacy
• AI-assisted imaging
• System validation
• Cross-disciplinary collaboration

Standards organizations are already adapting. AWS, ASNT, ISO, and other standards-writing bodies have committees exploring frameworks to ensure that AI tools used in inspection meet rigorous reliability and traceability requirements. The subsequent revision cycles may include guidelines for AI-assisted inspection verification, clarifying that human oversight remains mandatory in all automated systems and processes.

Ethics and Trust

AI systems can be incredibly efficient, but they are only as ethical as the humans who guide them. In inspection, trust is everything. We like to say, “Your reputation is the most valuable thing you own, so don’t ever sell it.” What we really mean is that your ability to instill trust is your most important trait. Once lost, trust is almost impossible to recover.

Trust and integrity are traits that no machine can replicate. An inspector’s professional judgment is built not just on pattern recognition but on principles of safety, honesty, and accountability. These are what separate the trusted inspector from the tool.

The inspector’s ability to explain how AI produces its results to clients, regulators, and the public will rely on their understanding of both its capabilities and limitations. Transparency will become the key to confidence in AI-assisted inspections.

The Inspector as Guardian of Insight

The inspector of the 2030s and 2040s will be less about wielding measuring devices and more about wielding insight. Inspectors will become the integrity managers of the day, interpreting streams of data, verifying AI assessments, and advising maintenance and engineering teams on risk and reliability.

A field inspector may be accountable for a swarm of autonomous drones performing visual and ultrasonic scans, UV and IR data collection systems, and airborne vapor detectors, all sent to a data dashboard. The drones may make confined space entry a rare occurrence by entering and assessing internal equipment, materials, or hazards. It will be the inspector’s task to interpret the data, order further testing or repairs, and report these findings more safely, efficiently, and with greater informedness.

That’s not to say that hands-on inspections will disappear; instead, they will evolve. Manual verification, tactical inspection, and field judgment will remain vital elements of the inspector’s role. This suggests that as automation expands, the moments requiring direct human evaluation will become more significant, not less.

The Future Is Human and Intelligent

AI will change inspection as a profession — it won’t erase it. It will redefine what we consider excellence. Inspectors who embrace these new tools while upholding the ethical standards of AWS and ASNT certification programs will be more valuable to the industry than ever.

As AI handles the data, the inspector will handle the truth. Those of us who have toiled in inspection most of our professional lives understand that it was never about the tools — it was always about trust. AI delivers the data, but inspection, like craftsmanship, is human work. 

CALVIN E. PEPPER (cpepper1946@gmail.com) is an AWS CWI (past SCWI), ASNT VT Level II, CQA (ASQ), MS nuclear engineer, and Certified Galvanizing Inspector (AGA). He is an AWS Life Member, a CWI Lifetime Achievement Award recipient, past chair of the AWS Q&C and Welding Handbook Committees, and past District 9 director.