Over the past few weeks, a few candidates we introduced into major SAP and Data consultancy hiring processes were flagged for using AI tools live during their client interviews.
Not afterwards. During the interview itself.
All three were removed from the process immediately.
The feedback from clients was remarkably consistent.
Conversations felt unnatural. Answers were technically correct but overly keyword-heavy and lacking real context. Responses arrived with noticeable delays that suggested something was being typed or processed elsewhere. And when interviewers pushed deeper into practical delivery scenarios, the answers quickly lost coherence.
In SAP, Data and Cloud contracting, interviews are closely observed and documented. Patterns like this rarely go unnoticed.
The Practical Consequence
This isn’t simply about losing one opportunity.
When a client believes an interview has been assisted by AI, the candidate is typically removed from the process immediately. At Brabers, we also won’t represent that candidate for future opportunities.
In specialist markets like SAP, Cloud and Data, reputation travels quickly. What might feel like a small shortcut can carry long-term consequences.
The Bigger Problem
Even setting ethics aside, there’s a fundamental logic problem.
If a candidate optimises their way through a multi-million-euro SAP or Cloud transformation interview, what happens when the real work begins?
You cannot prompt-engineer your way through a production incident.
You cannot paste a critical system failure into an AI tool and wait thirty seconds for a structured answer while a client’s operations are down.
Senior contractors are hired because they bring tested, real-world expertise — the kind that holds up when systems fail at 11pm during a go-live weekend.
An AI-assisted interview answer doesn’t demonstrate that capability. In many cases, it actively obscures whether that capability exists at all.
Why Detection Isn’t So Simple
Some clients have asked whether AI detection tools should become part of interview processes.
In practice, it isn’t that straightforward.
Across Europe, emerging regulatory frameworks including the broader governance environment around AI, data protection and workplace monitoring make the use of automated detection tools far from simple. Questions around transparency, candidate consent, accuracy, and potential bias all sit within an evolving legal landscape.
Organisations cannot simply deploy “AI detection software” and treat the output as definitive.
For now, most clients rely on something far more reliable: experienced interviewers who know how to probe for real delivery depth.
How We’re Approaching It
Our approach is deliberately practical.
In SAP, Cloud and Data interview processes, we look carefully at response patterns and the depth behind answers. We move beyond polished surface explanations and stress-test candidates on real delivery scenarios.
What we are looking for is the kind of technical fluency and contextual thinking that comes from genuine project experience, the type that is difficult to simulate through assisted responses.
As hiring standards tighten across consultancies and enterprise clients, credibility is becoming the real differentiator.
Clients don’t just want someone who interviews well. They want someone they can trust in high-stakes environments.
And in this market, the two must align.
A Question Worth Sitting With
AI is rapidly becoming embedded in how work gets done across technology consulting. Used properly, it’s a powerful tool.
The contractors who integrate AI into their actual delivery work improving analysis, accelerating documentation and solving problems faster are clearly ahead of the curve.
But using it to misrepresent capability during an interview is something entirely different.
As the market adjusts, a bigger question is emerging:
What should interview integrity look like in the age of AI?
Because in senior contracting markets, credibility travels faster than capability claims.
