Capability Over Convenience: What AI Cannot Replace in TIC
In an interview with the BBC, Shakuntala Devi was asked a question that feels even more relevant today:
In a world of machines and calculators, why should anyone develop such extraordinary mental abilities?
Her response was simple and enduring. If we have lifts to go upstairs or cars to travel, does that mean we no longer need legs? That would be absurd.
Human ability should not be replaced by convenience. It should be strengthened alongside it.Today, we are asking the same question again—this time it is AI.
If AI can analyse data, generate insights, and recommend actions, why should we invest in deep technical understanding?
Because in the Testing, Inspection and Certification (TIC) industry, the difference between knowing and knowing well is the difference between competence and judgement.
The Illusion of Knowing in the Age of AI
AI is transforming how we work. It can process vast datasets, summarise standards, assist in reporting, and even flag anomalies faster than most engineers. But it also introduces a subtle risk—the illusion of knowing.
When professionals begin to rely on AI outputs without understanding underlying principles, they shift from information to imitation, not insight. And in TIC, that distinction matters.
Because TIC is not built on how efficiently you execute a test. It is built on how confidently you can stand by the result.
AI can provide information. But insight still needs to be earned.
A Case in Point: Vibration Testing Under IEC 60068-2-6
Consider sinusoidal vibration testing of an electronic control unit. At first glance, the process is structured and well-defined. Frequency ranges, acceleration levels, sweep rates, and durations are specified. Modern systems can automate these profiles, monitor responses, and generate clean reports with minimal manual intervention.
Now imagine this scenario; An electronic module undergoes testing. The system completes the test cycle. No catastrophic failure is observed. The report is generated. From a purely procedural standpoint, the unit passes.
However, during the test, there are intermittent disturbances—minor signal fluctuations at certain frequencies. They are not outright failures, but they are not entirely normal either. An AI-enabled system may detect and flag these anomalies. It may correlate them with specific frequency bands or resonant peaks.
But the real questions begin where automation stops:
- Is this behaviour functionally significant?
- Does it indicate a design weakness that could manifest in the field?
- Is this a product issue—or a test setup artefact?
- Should the acceptance criteria be re-evaluated in context of application?
These are not questions of execution. They are questions of judgement.
Where Competence Ends and Judgement Begins
A competent engineer can run the test correctly. A trusted professional knows when the test is not telling the full story. This is where depth matters.
An experienced TIC professional will look beyond the output. They will assess fixture design, mounting conditions, cable interactions, and boundary constraints. They will question whether the observed resonance is inherent to the product or induced by the setup. They may choose to modify the approach:
- Introduce dwell testing at critical frequencies
- Adjust sweep rates to better capture resonance behaviour
- Reinterpret acceptance criteria based on real-world use
- Engage design teams to understand system-level implications
None of these actions are dictated purely by the standard. And none of them can be fully automated.
Because this is where execution transitions into ownership.
AI Can Execute. It Cannot Take Ownership.
AI is a powerful enabler. It enhances consistency, reduces manual errors, and improves efficiency in data handling and reporting. But AI operates within defined logic. It does not understand consequences in the way humans do.
It cannot fully evaluate what a failure means in a defence system, an automotive safety component, or a mission-critical application. It cannot stand in front of a customer and defend a decision when stakes are high. AI can execute processes. But it cannot take ownership of outcomes.
And in TIC, ownership is everything.
The Real Risk: Substituting Thinking with Convenience
The real challenge is not the rise of AI—it is how we respond to it. If we start substituting thinking with tools, we risk creating professionals who can operate systems but cannot interpret reality.
This is where the industry must be careful. Because TIC is built on unbiased, defensible knowledge.
Every report carries credibility. Every conclusion has implications. Every certification decision can influence safety, performance, and trust.
If that foundation is weakened by shallow understanding, the consequences are not immediate—but they are inevitable.
Leadership in the AI-Driven TIC Ecosystem
For leaders, this is not a technology decision. It is a capability decision.The goal is not to reduce human involvement—it is to elevate it.
That means building teams who:
- Move from information to insight
- Move from competence to judgement
- Move from execution to ownership
It means encouraging engineers to question outputs, not just accept them. To understand intent behind standards, not just follow procedures. To engage with ambiguity, not avoid it.
Because the future of TIC will not be defined by who uses AI the most.
It will be defined by who can think independently while using it effectively.
Returning to First Principles
The insight from Shakuntala Devi still holds.
Technology should enhance human ability—not replace it. Just as having a car does not eliminate the need to walk, having AI does not eliminate the need to think. In fact, it increases the responsibility to think clearly.
Because when answers become easier to generate, the risk of accepting the wrong answer without questioning it also increases.
The Real Question
- Are we building professionals who can run tests… or professionals who can stand by outcomes?
- Are we creating competence… or cultivating judgement?
Because that distinction is what separates a service provider from a trusted TIC partner like Envitest.
And in an industry built on trust, that difference defines everything.