Recently, TTS’s best-of-breed and global award winning product partner, Hirevue, released their report on how job seekers and assessment candidates experience the influence of AI in the hiring process. In their survey of over 3 100 job seekers across the globe, they investigated not only how employers have been using AI in their recruitment and selection functions, but also how potential employees engage with the technology.
In this article, we highlight some of Hirevue’s key findings, and reveal how the modern workforce remains both hopeful and skeptical, increasingly reliant on AI in their own job searches, and yet cautious when organizations use it to evaluate them.
AI as a productivity driver: The candidate perspective
Today’s job market is unpredictable. As a result, for many job seekers, AI is not just a convenience but a necessity.
The survey found that large portions of candidates are already using AI in their job search:
- 52% use AI to update their résumés.
- 51% use AI to help write cover letters.
- 49% use AI to prepare for their interviews.
- 45% use AI to research prospective employers.
This is a reminder that AI adoption is not confined to recruiters or employers. Candidates themselves are leveraging its efficiency in planning their next career move.
There is a paradox however: While candidates trust AI when they control it, they grow more skeptical when employers introduce it into selection processes.
For instance, a cumbersome or AI-opaque hiring process signals disregard for candidates’ time and well-being, undermining engagement from the beginning of the recruitment process.
Perceptions of employer use of AI
Candidates’ perceptions of AI in hiring reveal a complex trust gap:
- 79% want to know when AI is used in hiring decisions.
- 66% oppose AI making final hiring decisions (though this statistic has been decreasing 10% year-on-year).
- 43% support AI reviewing applications, but 41% still oppose it.
- 30% fear AI could replace human judgment or introduce bias.
This data highlights an important nuance: Candidates are not rejecting the use of AI in recruitment and assessment wholesale. Instead, they are calling for clarity, transparency, and human oversight.
Of course, within IO Psychology it is well known that validity, fairness, and reliability underpin all good assessment design.
Yet, for candidates, these principles are invisible unless explicitly communicated. The report suggests that even small steps, such as personalized recruiter videos explaining how AI is used, or online hubs that demystify AI algorithm design, can dramatically increase candidate trust.
Case example: Schneider Electric
A case study illustrates this well. Schneider Electric, wanted to improve their candidates’ experience during the hiring process. They introduced personalized recruiter introduction and closing videos within Hirevue’s OnDemand interview platform. This seemingly minor intervention had significant results: For the company, using these tools resulted in their candidate Net Promoter Score (NPS) rising from 68.4 to 75.4, demonstrating how personalization can soften perceptions of AI-driven processes.
For talent professionals, this finding implies that the technology itself is not the barrier, but rather the candidate’s perception of fairness, respect, and human connection.
Skills-based hiring: A shared priority
One of the most promising insights from the report is the convergence between candidate expectations and organizational priorities in regard to skills-based hiring.
For instance, 90% of candidates believe they are more likely to land their dream job with skills-based hiring.
And while hiring organizations are increasingly turning away from traditional CV or education-based hiring practices, 50% of them cite frustration with the difficulty of validating skills as their top barrier to skills-based practices.
Nonetheless, when done correctly, skills-based approaches not only expand the talent pool but also address fairness concerns by focusing on validated competencies rather than less-than-ideal proxies like degrees or job titles.
However, candidates remain wary. The survey revealed that:
- 45% of employees see bias in hiring as a major issue.
- 30% worry AI cannot account for subtle, human qualities.
- 13% fear AI might screen out qualified candidates.
- 11% don’t trust AI at all.
This points to a central tension: Skills-based hiring has immense potential to reduce bias and open doors, but only if candidates trust the systems that assess those skills.
Case example: William Hill
The gaming company William Hill faced inefficiencies in screening over 30,000 applications annually for customer-facing roles.
By implementing a Hirevue 15-minute game-based assessment focused on validated skills and behaviours, they cut time-to-interview from 15 days to 1.8 days. Candidates responded positively, rating the experience 9.3/10, and neurodiverse applicants reported better accessibility.
This case demonstrates how well-designed assessments, built around job-relevant behaviours and delivered through engaging formats, can simultaneously improve efficiency and fairness.
Importantly, it underscores the role of IO Psychologists in ensuring these tools remain psychometrically sound while enhancing candidate experience.
Candidate perceptions of bias
Bias remains a defining theme in candidate perceptions. While human decision-making is often seen as subjective, many candidates still doubt AI’s ability to overcome such biases that may have been inherited from its human creators.
Results from the report show perceptions about AI’s possible impact on unfair practices and bias in hiring:
- 57% of respondents believed AI would decrease biased decision-making.
- 21% feared that AI would make matters worse.
- 23% thought AI would make little to no impact on unfairness and bias.
This split view reveals two key points. First, candidates recognize the potential of AI to reduce bias.
Second, skepticism persists because most lack understanding of how algorithms are built and validated, and how such algorithms would assist hiring managers in making talent decisions.
Case example: Children’s Hospital of Philadelphia
The Children’s Hospital of Philadelphia (CHOP) faced inefficiencies and candidate dissatisfaction with its manual hiring process.
By integrating HireVue with Workday and introducing conversational AI for prescreening, on-demand interviews, and self-scheduling, CHOP saved 1 695 hours annually (also saving 6 743 hours in replaced telephone interviews), reduced costs by $667 000, and improved candidate satisfaction to an Net Promoter Score of 92.
The CHOP example illustrates the dual advantage of well-implemented AI: operational efficiency for employers and enhanced experience for candidates.
Also, automation did not depersonalize the process but freed up talent professionals to focus on higher-value tasks.
Candidates split but curious about AI
Despite the concerns mentioned above, candidates are increasingly open to the use of AI in hiring processes. The survey found that:
- 41% said AI would not affect their willingness to apply for a job.
- 39% would be less likely to apply if AI were involved.
- 20% would be more likely to apply, knowing that AI was being used.
This ambivalence underscores that candidates are not anti-AI. Instead, they are more likely to be anti-ambiguity.
They want reassurance that AI will support, not replace, human judgment.
Broader perceptions of AI’s transformational impact on the workplace reinforce this interpretation:
- 74% anticipate major workforce impacts once AI is used in hiring.
- 67% expect significant economic implications.
- 50% foresee substantial personal impact with wide-spread AI adoption.
- 43% believe AI will both help and hurt workers equally.
Perhaps, these statistics point to a cautious optimism. For employers, the implication is that education, transparency, and candidate-centred design are essential to winning trust.
Strategic implications for talent professionals
The findings of the Hirevue’s Candidate Experience Report converge on three central imperatives for talent and IO Psychology professionals:
1. Temper efficiency with humanity
AI can accelerate processes, but candidate satisfaction depends on respect, empathy, and communication. Technology should enhance candidate experience, not add friction or distrust to the equation.
2. Build trust with transparency
Candidates want to know when AI is used, how it is applied, and where human oversight is being employed. Clear explanations, personalized messaging, and accessible educational resources can transform skepticism into confidence (or at least greater trust).
3. Skills-based hiring
The shift to skills is an opportunity. Validated assessments, game-based tasks, and structured interviews can unlock overlooked talent pools. But to succeed, they must be framed and delivered in ways that feel fair and inclusive.
For IO Psychologists, this is fertile ground. The profession’s expertise in psychometrics, fairness, and evidence-based assessment design is precisely what organizations need to ensure AI-enabled hiring is not only effective but also ethical and predictive of performance.
Final thoughts
The Hirevue Candidate Experience Report paints a clear picture: AI in hiring is no longer a question of if but how. Candidates already embrace AI in their own job searches, but they demand clarity and reassurance when employers deploy it.
The path forward requires improving candidate trust in AI-enabled hiring. That requires hiring processes that:
- Save candidates time and reduce admin.
- Provide transparent, personalized communication.
- Validate skills through rigorous, accessible assessment.
- Balance automation with consistent and persistent human connection.
If you are interested in how TTS can help you unlock the potential of AI-enabled hiring, drop us a line at info@tts-talent.com.
Source
Hirevue (2025). The Candidate Experience Report.