The Alignment Advantage Report: How Recruiters and Job Seekers Use AI – and Where Perceptions and Evaluations Diverge

I recently read The Alignment Advantage Report by Checkr, which surveyed 3,000 HR professionals and 3,000 job candidates about how AI is used and perceived in recruiting.

The report offers direct comparisons of expectations and values from both groups, identifying where perceptions align and diverge. These differences reveal actionable insights for recruiting teams using AI now or in the future.

The Study Base: 6,000 Perspectives on AI in Recruiting

The report explores, among other things, the following questions:

• Which AI tools are used by HR teams?

• Which AI tools are used by candidates?

• How are fairness, transparency, and the overall impact of AI perceived?

• Where do perspectives align – and where do apparent gaps emerge?

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The focus is therefore not on strategic models or future visions, but on a systematic comparison of two perspectives on the same process: recruiting from the company side and job searching from the candidate side.

AI Use in Recruiting: Process Support on the Employer Side

Today, HR teams primarily use AI, which makes processes more efficient, faster, and more consistent. The most frequently mentioned use cases include:

• resume screening

• interview summaries

• automated scheduling

• background checks

  
  

Only about one-quarter of HR teams have clear goals, KPIs, and management support for their AI use. This shows that although many organizations have adopted AI, most rely on operational needs rather than a strategic framework.

AI Use on the Candidate Side: Optimizing Personal Positioning

Job seekers, too, are now using AI on a broad scale. Around 61% of applicants report using AI during the application process, primarily for:

• optimizing their CV

• writing cover letters

• job matching

• interview preparation

  
  

While organizations primarily use AI for process control, organization, and selection, candidates mainly rely on it to optimize how they present themselves and how well they match a specific role. Both sides are therefore using similar technologies – but with clearly different functional objectives.

Shared Values: Strong Alignment on Ethics and Priorities

Despite different roles, the report shows that both sides share similar core values.

Both HR professionals and candidates identify the following as their most critical ethical priorities:

• data protection

• transparency in AI-driven decisions

• fairness across all demographic groups

  
  

This alignment matters. Both groups see AI as more than a tool for efficiency—ethics count for them.

Where Perception and Evaluation Clearly Diverge

Despite shared values, the report points out significant gaps in perception and evaluation that matter for recruiting teams.

Transparency: Being Informed vs. Feeling Informed

One of the report’s key findings:

• Around one-third of candidates say they were never informed that AI was used in the application process.

• At the same time, many HR teams believe they are transparent about the tools they use and about the division of responsibility between humans and AI.

  
  

This isn't a factual contradiction. It's a gap between official transparency and how it's perceived:

• HR teams often assess transparency based on whether information is available in principle.

• Candidates, on the other hand, evaluate transparency based on whether they can clearly recognize and understand the use of AI in the actual process.

Fairness: Different Levels of Trust in AI

There is also a clear divergence in how fairness is evaluated:

• More than half of HR managers believe that AI-supported decisions are at least as fair as human assessments.

• On the candidate side, only about one-third agree with this view.

• A similarly large share is generally skeptical about AI.

HR teams tend to evaluate AI primarily in terms of:

• consistency

• standardization

• reduction of individual bias

Candidates, however, tend to associate fairness more strongly with:

• transparency and comprehensibility

• individual evaluation

• and visible human responsibility
  

Impact on the Human Aspect of the Process

The most significant split comes with how people feel about the "human touch":

• 75% of applicants feel that AI-driven recruiting processes are more impersonal.

• Only a comparatively small share of HR leaders perceive this effect with similar intensity.

For HR, the focus is often on process quality (speed, structure, documentation).

For candidates, the focus is on relationship quality (feedback, accessibility, individual communication).

Automation increases efficiency but often creates a sense of distance.

AI on Both Sides – and Emerging Operational Grey Areas

The report also clearly shows that the parallel use of AI on both sides creates new areas of tension:

• Companies use AI for selection and evaluation.

• Candidates use AI to optimize application documents, answers, and preparation.

This raises new operational questions:

• What counts as legitimate support?

• Where does optimization become deception?

• How should organizations deal with AI-generated texts, tests, or even deepfake elements?

The report does not assess these developments normatively, but it makes one thing clear:

As AI use grows on both sides, clear rules, strong communication, and solid methods matter more.

What Recruiting Teams Can Do Now

The differences highlighted in the report translate into very tangible fields of action for recruiting teams:

1. Make Transparency Visible in Day-to-Day Operations

Transparency does not originate in privacy policies – it emerges in the lived experience of the process:

• clear signals in screening

• understandable explanations in interview evaluations

• visible responsibility in decision-making

2. Make Fairness Explainable

It is not enough to make decisions – they must also be communicated understandably:

• clearly explain the criteria

• structure feedback

• make human responsibility visible

3. Clearly Separate Automation from Decision-Making

• AI for organization, structure, and preparation

• humans for evaluation, contextualization, and final decisions

4. Deliberately Design Human Touchpoints

• individual feedback at key moments

• accessible contact persons

• personal communication during critical transitions

5. Actively Account for AI Use on the Candidate Side

• sensitize recruiters to AI-optimized applications

• develop clear internal guidelines

• realistically recalibrate expectations regarding the informational value of application documents

6. Systematically Measure Perception

In addition to processing KPIs, also track:

• perceived transparency

• perceived fairness

• experienced appreciation

7. Targeted Team Sensitization

The most significant leverage lies in day-to-day operations:

• training formats

• internal reflection sessions

• targeted workshops to analyze processes from both perspectives

Conclusion

The Alignment Advantage Report by Checkr clearly shows that both recruiting teams and job seekers use AI, but with different goals, views, and standards.

Both sides share:

• central ethical values

• a strong desire for efficiency

• and an expectation of fair processes
  

However, there are significant differences in perceptions of transparency, fairness, and the impact of AI on the human side of recruiting.

• In the perception of fairness,

• and how AI affects the human aspect of recruiting.
  

Recruiting teams gain the most leverage not from more technology, but from purposefully designing the interfaces between automation, communication, and human responsibility. Here, teams determine whether AI acts as professional support or as an impersonal filter.