Few topics in talent acquisition today stir as much curiosity and debate as the role of artificial intelligence in the hiring process. Once confined to sourcing and screening, AI is now edging its way into the interview room itself. From transcription and note-taking to real-time coaching and even conducting structured interviews, the possibilities are expanding rapidly. But so too are the questions: Can AI truly augment human judgment without undermining trust? Where should the lines be drawn between automation and human oversight? And perhaps most importantly, what does this mean for candidate experience?
These were the questions posed during the most recent CXR Research Panel, co-facilitated by myself, @Chris Hoyt (he/him), president of CXR, and @Johnny Campbell, CEO of SocialTalent who volunteered to sponsor the administrative costs of this research topic. Each quarter, this panel convenes talent leaders across industries to examine a pressing challenge in the hiring space. In this session, panelists dug into the promise and the perils of AI in the interview process. Their responses revealed both optimism and hesitation, painting a nuanced picture of where the field is headed.
AI as an Efficiency Engine
The clearest consensus from the panel was that AI’s greatest near-term value lies in reducing administrative burden. Scheduling, transcription, and note-taking consistently surfaced as the most practical and impactful use cases. These tasks, while essential, can drain interviewers’ attention and leave little bandwidth for genuine engagement with candidates.
“Automatic transcription services provided by AI tools such as Brighthire or Micro1, even MS Teams or Co-Pilot, can capture every word spoken during an interview, creating a detailed record of the conversation. This feature eliminates the need for manual note-taking, allowing interviewers to concentrate on active listening and interaction with the candidate.” - @Tyler Green, Recruitment Operations, GALLO
Panelists echoed this point: when AI captures the details, interviewers are freed to listen more closely and evaluate more fairly. Beyond convenience, this can also improve consistency across interviews and provide stronger documentation for downstream decision-making.
The framing of AI as augmented intelligence rather than artificial intelligence resonated strongly. Several leaders argued that the real opportunity is not to replace recruiters or managers, but to relieve them of repetitive tasks so they can focus on candidate engagement and strategic decisions. As one panelist noted, interview prompts and notetaking tools are only effective if interviewers remain accountable to verify the output and apply critical thinking. Without that discipline, efficiency gains may simply shift the burden downstream in the form of poor hiring choices.
Beyond Note-Taking: AI as Interviewer
While efficiency is the obvious starting point, some panelists pointed to more ambitious applications already emerging in the marketplace. Tools that already show evidence of conducting structured interviews, asking competency-based questions, and generating draft evaluation forms for recruiters to review.
“We've been very impressed with the demos and how AI recruiter solutions pull from the candidate's CV and ask insightful and relevant questions related to the competencies being assessed. The human recruiter then reviews the evaluation form completed by the AI - with transcripts and video excerpts linked - before making a final decision.” - @Megan Goeltz, TA Futurist and Head of Transformation, EY
This vision represents a striking shift. Rather than simply assisting, AI is positioned as a co-interviewer, generating insights that recruiters confirm or override. Comparisons were drawn to long-standing video interview platforms, with the question raised: is this truly "new", or instead a complex evolution of older self-guided interview technology?
For high-volume hiring, some panelists saw clear potential. AI-led interviews could give candidates more opportunity to showcase their skills while providing hiring teams with consistent, structured input. Yet skepticism remained among our leaders. If these tools simply replicate old models with new branding, they may fail to deliver on the promise of meaningful transformation. And even if they do deliver efficiency, are executives prepared to wrestle with the thornier issues of bias, legality, and candidate trust?
The Governance Challenge: Guardrails and Compliance
If efficiency is the “carrot” of AI adoption, then risk is clearly the stick. Nearly every participant highlighted the need for governance, compliance, and clear guardrails. Without them, innovation can quickly cross into dangerous territory.
“With a large team of very smart recruiters, we had a number of folks experimenting with CoPilot in some very interesting and creative ways. And while some efforts were fantastically creative and ambitious, it also was a lightbulb moment for us to pull the team back and construct guardrails before any actions could be taken regarding hiring or interviewing decisions.” - @Kirk Keeney, Executive Director, Senior Lead Business Execution Consultant, Wells Fargo
This anecdote underscores a recurring theme: AI adoption is as much about people as it is about technology. Recruiters will experiment, sometimes in ways that could potentially be misaligned with compliance requirements or even organizational values. Companies must proactively define not just how AI can be used, but how it shouldn’t be used.
Our panelists also pointed to the patchwork of state and municipal laws evolving around AI in hiring, as well as the scrutiny of internal model committees. Keeping a human in the loop is no longer just best practice - in many jurisdictions, it’s a legal requirement. And even when compliant, AI must pass the test of fairness. As one panelist asked pointedly: why do we demand rigorous audits of AI-driven interviews when we have long tolerated biased human interviewers who hire only from their alma mater or prefer candidates “not from this area”?
The irony is difficult to ignore. Humans are often more biased than the tools being scrutinized, but organizations are more comfortable holding machines to account than themselves.
Candidate Experience and Trust
Perhaps the most sensitive question is how AI in the interview process affects candidates themselves. Leaders worried not only about legal exposure, but about the more intangible, and equally important, matter of trust.
For professional and executive roles, the bar is high. Candidates expect a “white glove” experience, and many of today’s AI tools fall short. And as a few of our leaders noted, no demo to date has convinced them that AI can deliver the level of care and nuance their organizations promise to candidates.
Others raised the question of transparency. Even if the process is explained, will candidates who are rejected still perceive bias? Will they feel unfairly judged by a “machine”? These perceptions matter and are important. They shape employer brand and candidate willingness to reapply or even recommend employers to friends, colleagues, and family.
Adding complexity, candidate use of AI is rising just as fast as recruiter adoption. Several of our participants in this research cohort noted that they regularly “catch” candidates relying on AI tools to generate interview responses in real time. This raises thorny questions that are hot topics of debate: if recruiters are empowered to use AI, why not candidates? Could mastery of personal AI assistants even become a desirable skill in its own right?
There are no easy answers. But as one organization's head of TA suggested, the line is clearly moving and companies will need to decide where to draw it sooner rather than later.
The Human Side of Change
While technology and compliance dominated much of the discussion, our group pointed out that the biggest barriers are cultural. Recruiters fear replacement or resist structured guides. Hiring managers balk at the idea that software could structure an interview better than they can. Local service offices value the personal touch and may see any automation as a threat to candidate relationships.
As one panelist put it bluntly, change management is the real hurdle. Without it, even the most compliant and efficient AI tools will fail to gain traction. And in some cases, the technology may surface uncomfortable truths organizations are not ready to confront. Tools that evaluate interviewer performance, for example, could reveal which managers are skilled and, of course, which are not. For serious consideration is whether companies are prepared to act on that data, or if they will quietly shelve it.
Ultimately, adoption will hinge not just on what the technology can do, but on how organizations manage the transition. Training, transparency, and a willingness to confront long-standing human biases will all be essential.
Conclusion: Augmentation, Not Automation
The CXR Research Panel’s exploration of AI in the interview process surfaced both promise and peril. On one hand, AI offers clear opportunities to relieve administrative burden, enhance consistency, and provide richer documentation. On the other, it raises profound questions about governance, bias, transparency, and trust.
Across the responses, one throughline was clear: AI should augment human decision-making, not replace it. Recruiters and interviewers must remain accountable, using AI to free time for more strategic and empathetic engagement. The future of interviewing may well involve AI “co-interviewers,” but only in a framework where humans retain authority and responsibility.
The challenge ahead is not simply technical. It is organizational, cultural, and ethical. How companies manage adoption, define guardrails, and preserve trust will determine whether AI becomes a force for fairness and efficiency—or a new source of risk and skepticism.
As the CXR community continues to explore this evolving frontier, one thing is certain: the debate is far from over. To dive deeper into this research and the broader themes we’re unpacking this quarter, visit cxr.works/research.