The New Question in Hiring: How Much Can We Trust Candidate Data?

As AI becomes widespread in hiring processes, new questions arise about the reliability of candidate data. Why are verification and trust becoming more important in hiring?

HiringCycle Ekibi

Yayınlanma:29.08.2026

Güncellenme:29.08.2026

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For a long time, hiring has operated on a fundamental assumption: the more information we have about a candidate, the better decisions we make.

A more detailed CV, a more comprehensive digital profile, more assessment results and more interview notes... As technology has entered hiring processes, the volume of this information has grown rapidly. But today a new problem has emerged: we can no longer always be sure how much of the information we hold reflects reality.

Deloitte's 2026 Global Human Capital Trends research shows how widespread this concern has become. 95% of executives participating in the study expressed concern about the accuracy of data on candidates' skills and competencies. More than a third of employees say they regularly use AI to make their personal profiles appear stronger.

This has an important consequence for hiring. It is no longer just about evaluating candidates — understanding how reliable the information we evaluate has become part of the process itself.

How is AI changing the candidate profile?

AI assisting candidates is not a new problem in itself. A candidate getting help to write a better CV, articulate their experience more clearly or prepare for an interview can be positive in many ways.

But as the use of AI has expanded, the boundaries have become blurred.

Today, a candidate can use AI to present their experience as more impressive than it is, frame a competency they don't have in language tailored to a job posting, or create a portfolio built from work that isn't theirs. In more extreme cases, entirely fabricated identities and fake images used in video interviews are also emerging.

The issue is not really the use of AI itself. The issue is that it is becoming increasingly difficult to distinguish between a candidate's actual competence and the profile created with technology support.

For example, a very well-crafted CV may not actually reflect an equally strong professional experience. A software project, design or writing sample may not be the candidate's own work. A successful result in an assessment process may not always represent a competency the candidate demonstrated on their own.

So the question facing hiring teams is beginning to change.

It is no longer enough to ask only: "Is this candidate suitable for this position?"

Before that, we also need to ask: "How reliable is the information we are using to make this evaluation?"

A new technology race between candidates and companies

Deloitte points to a striking picture in this new landscape. While candidates use AI to prepare their applications and get support during assessment processes, companies also use AI to screen and evaluate candidates.

In other words, on one side there are candidates making their applications as strong as possible with AI assistance, and on the other side there are AI systems trying to find the right people among these applications.

Deloitte describes this dynamic as "machine versus machine." As candidates use AI to generate large volumes of applications and companies use AI to screen them, there is a risk that signals showing genuine human experience and competence get lost.

The core problem that hiring technologies have long tried to solve was finding the right candidates faster. But in the period ahead, another problem will grow in importance: separating real information from the noise generated by technology.

More data doesn't always mean better decisions

For years, hiring technologies have been trying to increase the volume of data. We collect more information about candidates, bring in data from different sources and use this data in decision processes.

But as the volume of data grows, we can no longer assume that its quality and reliability increase at the same rate.

Thanks to AI, a large number of applications can be prepared in minutes. Digital profiles can be edited. Articles, designs and other work can be generated. Understanding which of these reflects the candidate's real experience and which reflects technology support is becoming more complex every day.

For this reason, the feature that will set successful hiring systems apart in the future will not only be their ability to process more data.

The real difference will emerge in the ability to evaluate the source, consistency and reliability of data.

Verification is becoming as important as assessment

These developments do not diminish the importance of assessment processes or other evaluation methods. On the contrary, the value of processes aimed at getting to know candidates more closely and understanding their real competencies is increasing.

But assessment alone may no longer be enough.

Whether the information provided by the candidate is consistent with different sources, whether the work presented is genuinely their own, and how much the assessment result reflects the candidate's true capacity are becoming increasingly important questions.

This brings a new area of responsibility for hiring technologies: not just scoring candidates, but providing a stronger framework for how reliable the information used in the decision process is.

This does not mean technology will automatically verify everything. Especially when it comes to human competencies, understanding context remains important.

It is not possible to understand a candidate's different career experiences, working style, problem-solving approach or actual contribution to a particular success from a single data point alone.

Therefore, technology can bring together more information, surface inconsistencies and provide decision-makers with a stronger evaluation foundation. But the quality of the final decision will remain closely tied to how this information is interpreted.

The importance of human judgment is not disappearing

As AI's role in hiring grows, it is easy to think that human judgment will become irrelevant. But the picture that emerges shows the opposite.

AI can process far more information in a short time. It can reveal similarities and differences between candidates. It can provide significant support to hiring teams during evaluation processes.

But if the information fed into a system is not reliable, the quality of decisions made based on that information will also be limited.

For this reason, the role of humans in the hiring technologies of the future will not disappear. In an environment where more and more data is generated and analysed, humans will continue to be the side that evaluates this information in context and carries the responsibility of the decision.

Perhaps the real change will happen here.

The goal of hiring technologies will not be to eliminate human decision-making entirely, but to enable people to access more reliable information and make healthier decisions based on that information.

The new question of hiring

Hiring technologies have long been trying to provide a better answer to the same question:

How can we find the most suitable candidate?

This question remains important.

But in the new era where AI is changing how both candidates and companies operate, another question needs to be added to this one:

How much can we trust the candidate information we have?

One of the most important areas of development for hiring technologies in the period ahead seems to revolve around this question.

Collecting more data is no longer enough on its own. More automation does not always mean a better decision either.

The real need is to better understand the information obtained about candidates, verify it when necessary, and use all this information in a way that supports human evaluation.

Because to reach the right decision in hiring, we first need to understand which information is truly reliable.

Source

Deloitte, 2026 Global Human Capital Trends — Deloitte 2026 Global Human Capital Trends

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Okuma Süresi 7 dk. - 29.08.2026

The New Question in Hiring: How Much Can We Trust Candidate Data?

How is AI changing the candidate profile?

A new technology race between candidates and companies

More data doesn't always mean better decisions

Verification is becoming as important as assessment

The importance of human judgment is not disappearing

The new question of hiring

Source

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