The interview has long been the least examined stage of the recruiting workflow. Organizations have invested heavily in sourcing technology and applicant tracking systems, yet the core human conversation at the center of every hiring decision has largely remained undocumented, inconsistent, and unmeasurable. That gap is narrowing. Gartner identified interview intelligence tools among the technologies with the potential to fundamentally reshape recruiting in 2026, and data from RPOA's 2026 RPO Buyer Trends study shows that 44% of employers are already capturing time savings of two to five hours per recruiter per week as a result of AI-assisted workflows, with 32% saving more than five hours weekly.
This post is based on an edited version of a recorded interview with Nick Livingston, CEO and Co-Founder of Honeit, a Silver Member of the Recruitment Process Outsourcing Association (RPOA). The interview was conducted by Lamees Abourahma, CEO at the RPOA, as part of the Talent Leader Council interview series.
Key Takeaways for Talent Acquisition Leaders
- The basic phone screen is no longer a sufficient use of recruiter capacity. Intelligent interviewing enables recruiters to conduct skills-based, req-specific first and second round interviews that deliver measurable value to hiring managers and clients.
- Time savings from AI-assisted workflows are most valuable when reinvested in higher-quality candidate engagement and deeper hiring manager relationships, not in headcount reduction.
- Interview data is a searchable, structured asset. Organizations that capture and archive interview intelligence create a talent database that extends well beyond the resume.
- Pilots and phased adoption lower the barrier to entry. A single requisition test with three candidates is sufficient to generate evidence for a broader business case.
- Keeping humans in the decision loop is both a legal and strategic imperative. AI should support and inform hiring decisions, not automate or replace them.
The Gap in the Middle of the Recruiting Workflow
For decades, the recruiting technology stack has been built around two anchors: sourcing tools to find candidates and applicant tracking systems to manage them through the pipeline. The conversation in between, the screening call, the skills interview, the hiring manager debrief, has remained largely unstructured and invisible to recruiting leaders.
RPOA: What problem does intelligent interviewing solve that existing recruiting technology does not?
Livingston: Whether you are an internal recruiter or an external recruiting partner, the most important parts of the recruiting process are missing from the ATS. Your kickoff calls with clients, your screening calls with candidates, your interviews: all of those meaningful conversations were typically offline, outside the system, over the telephone or a video call. And each component before, during, and after those calls was also being pieced together by recruiters individually. There has been a lot of investment in sourcing technologies and in ATS systems, but there was a big gap in the middle: what are recruiters and candidates actually talking about, what data is being captured, what is being sent to the hiring team, and how are decisions being made? That was all a black box.
This observation is supported by broader market data. According to Aptitude Research, 38% of organizations report irregular interview structures, and 32% struggle to use objective data to make hiring decisions[1]. The consequence is a delivery model that is difficult to measure, harder to scale, and inconsistent across recruiting teams. Teams using structured, AI-supported interviews see 24 to 30% higher consistency in assessments, according to Harvard Business Review research from 2024[2].
"There has been a lot of investment in sourcing technologies and in ATS systems, but there was a big gap in the middle: what data is captured, what is the recruiter sending to the hiring team, and how are decisions being made? That was all a black box." -- Nick Livingston, CEO and Co-Founder, Honeit
From Time Savings to Strategic Delivery
The ROI conversation in talent acquisition has often centered on speed: time-to-fill, cost-per-hire, and recruiter capacity. Intelligent interviewing reframes that conversation around quality of output and strategic value to the client.
RPOA: How should RPO leaders and talent acquisition teams think about the return on investment from interview intelligence beyond time savings?
Livingston: We work with RPO partners who are using AI to automate what bots can do well, so that humans can focus on what humans do well: authenticity, building relationships, rapport. They do not see AI as a way to reduce recruiting headcount. They see it as a way to empower their teams to talk to more clients and more candidates. From a capacity standpoint, recruiters can manage more requisitions because they are no longer spending time on scheduling, note-taking, and the write-ups that follow every interview. That time can be redirected toward sourcing, client relationship management, or more candidate conversations. We also have a client placing automotive technicians at scale who has literally doubled their close rate on a monthly basis over the last several months. That is not just time savings to the recruiter. That is jobs filled faster, at scale, with more consistency, which is what RPO delivery is ultimately about.
RPOA's 2026 RPO Buyer Trends report substantiates this trajectory. Employer adoption of AI-assisted workflows has accelerated, with time savings now translating into measurable output gains rather than simply reduced administrative burden. Deloitte's 2025 talent acquisition research confirms that AI is enabling recruiting functions to shift from reactive to proactive, with recruiters increasingly focused on relationship management and high-value candidate engagement rather than transactional coordination.
Elevating the Recruiter Through Skills-Based Interviewing
One of the more significant structural changes emerging from interview intelligence adoption is the elevation of the recruiter's role within the hiring process. Rather than conducting basic screening calls and handing candidates off to hiring managers, recruiting teams are increasingly leading structured, skills-based first and second round interviews that deliver substantive value.
RPOA: How is intelligent interviewing changing the scope of what recruiters are actually doing in the hiring process?
Livingston: We have a recruiter who spent 15 to 20 years in accounting and finance recruiting, and she found a role at an aerospace company. Now she is literally talking to rocket scientists. How do you have meaningful conversations with people in an industry you do not know well? That is where technology can help: enabling recruiters to ask domain-specific questions, capture the answers accurately, and share structured insights rather than scribbled notes and one person's interpretation. We are also seeing recruiters who used to conduct basic phone screens now leading high-quality, req-specific, skills-based interviews. In some cases, they are taking on first or second round interviews that used to sit with the hiring team, and that is a significant shift in how recruiting delivers value to the business.
This shift reflects a broader industry realignment. Gartner's 2025 research notes that as AI and automation take on more low-complexity work, recruiters' ability to deliver on high-complexity hiring becomes more critical, requiring them to advise on talent strategy, build long-term relationships with hard-to-access candidates, and assess fit for future organizational needs, not just current roles. The RPOA's own AI Impact and Innovation Task Force is tracking this transition under a framework it describes as the recruiter-plus-AI model: an operating approach in which technology handles administrative workflows while recruiters invest their capacity in the judgment-intensive, relationship-driven work that AI cannot replicate. Gartner
"Technology can actually help keep the process human. We are still going to be talking to candidates, asking great questions, and then the data we share with clients is going to be less biased and less subject to misinterpretation, because we can share answers and insights rather than scribbled notes and one person's opinion." -- Nick Livingston, CEO and Co-Founder, Honeit
Interview Intelligence as a Searchable Data Asset
Beyond the immediate workflow benefits, intelligent interviewing generates a structured data asset that most recruiting organizations have not yet recognized or leveraged. Thousands of captured conversations become a searchable repository of candidate aspiration, skill evidence, and career intent that no resume database can replicate.
RPOA: What does it mean for an RPO or recruiting organization to treat interview data as a structured, searchable asset?
Livingston: RPO partners we work with may have five to ten recruiters with a client and 7,000 captured interviews. Some clients have 10,000 to 20,000 interviews, all now searchable and documented. You can search your interviews the same way you search resumes. Resumes are historically oriented: what did someone do in the past? The interview and the conversation are forward-looking: what do you want to be doing, what are your aspirations, what are your career goals? None of that is on a resume. But if it is structured data, you can search the answers, the transcripts, the summaries, the skill tags. Sourcers can search who have we spoken with in the last two years who said they want to become a marketing director. They are not one yet, but you know who is ready. That is a data set recruiters and sourcers have never had before.
This reframes the value proposition of interview intelligence from a workflow tool to a strategic talent intelligence asset. For RPO providers in particular, the ability to surface previously interviewed candidates for new client requisitions represents a material competitive differentiator, one that compresses time-to-shortlist and reduces sourcing cost on repeat or high-volume engagements.
Change Management, Compliance, and the Human-in-the-Loop Imperative
Adopting intelligent interviewing at scale requires more than a technology decision. It requires deliberate change management, a clear position on the role of AI in hiring decisions, and an organizational willingness to examine how recruiting work is actually being done today.
RPOA: What should talent acquisition leaders understand about managing the transition to AI-assisted interviewing, particularly in organizations where recruiters are skeptical or hesitant?
Livingston: There is anxiety, fear, and confusion in the industry right now, and recruiters have a right to be somewhat skeptical. This is a people business. But recruiters cannot be complacent either. A lot of recruiters feel they are personally very good at what they do, and many managers have never actually listened to how their recruiters conduct themselves on a call with a candidate. If they did, there would be room for improvement, generally speaking. What we recommend for the individual recruiter is: test and try. Pick one requisition, talk to three candidates, share a couple of links with your hiring manager, and ask whether it helped them make a better decision faster. For recruiting organizations and RPOs, the ones leaning into this and seeing gains in delivery want consistency at scale, and if something is working, they have to implement it. The competition is fierce. Clients are asking what you are actually delivering for the fees they are paying.
On the question of compliance and AI governance, Livingston draws a clear line. AI should be used to assist and inform, not to score, rank, or decline candidates autonomously. Gartner's 2025 analysis of talent acquisition trends underscores this point, noting that recruiter judgment remains essential to high-complexity hiring, particularly as AI capabilities expand and regulatory scrutiny of automated hiring decisions increases. Livingston's framing is direct: organizations that remove the human from hiring decisions in pursuit of efficiency may find that their recruiter's involvement becomes less relevant over time, and that legal and reputational risk accumulates alongside it.
"I would much rather be on the side of: let us be cautious, let us be safe, let us treat this as data, but keep decision-making with the recruiters and the hiring managers. Those who want AI to auto-score, auto-rank, and auto-decline candidates may find their own relevance diminished in a year or two." -- Nick Livingston, CEO and Co-Founder, Honeit
Final Notes
Intelligent interviewing is not a marginal efficiency gain. It is a structural shift in how recruiting organizations capture, interpret, and act on the most important data point in the hiring process: the human conversation. For RPO providers and talent acquisition leaders, the opportunity is to reposition recruiting as a strategic delivery function: one that produces structured candidate intelligence, elevates the recruiter's role in the hiring process, and provides clients with more than a resume submission.
The path forward does not require wholesale transformation. As Livingston notes, a single requisition pilot is sufficient to generate meaningful evidence. What it does require is a willingness to examine current workflows honestly, invest in the recruiter's capacity to lead higher-quality conversations, and keep human judgment at the center of every hiring decision.
RPOA will continue to track the evolution of interview intelligence and recruiter enablement as part of its commitment to evidence-based leadership for the RPO and talent acquisition community.
References [1,2]: 100 AI recruitment statistics you need to know heading into 2026, Hirevue
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