The talent acquisition function, especially in enterprises, is at a crossroads, caught between the pressure to hire faster and the challenge of finding the right talent. The global HR technology market is projected to grow from USD 43.66 billion in 2025 to USD 81.84 billion by 2032, reflecting a 9.2% CAGR (Fortune Business Insights). This surge reflects how enterprises are doubling down on automation, AI, and analytics to modernize their talent acquisition functions.
Yet, despite the rising investment, measurable efficiency gains are lagging. According to GoodTime, time-to-hire increased in 2024. 60% of companies reported an increase in time-to-hire, up sharply from 44% the previous year, while a mere 6% managed to reduce it.
Even as AI tools proliferate, organizations are struggling to accelerate hiring while attracting top talent. This paradox highlights a fundamental disconnect – technology is advancing faster than organizational hiring workflow.
The delay in time-to-hire has a cascading effect on the cost of vacancy, which rises as key positions remain unfilled. Every day a critical role sits vacant, organizations risk losing revenue, stalled projects, and declining team morale. In a competitive talent market, enterprises can’t afford a slow, fragmented hiring process.
In enterprise-scale hiring, the stakes are higher than in small- or medium-sized businesses. Large organizations often handle thousands of applications per role, balance specialized and niche hiring needs, and coordinate across time zones. Add in contingent and contractual staffing requirements, and the process becomes even more complex – making every delay costlier.
- Average TTH for enterprises with 5,001+ employees is approximately 35 days, though industry-specific roles can extend beyond 40 days. (Statista)
- Cost per hire averages $4,700 (SHRM, 2024), but extended vacancies for revenue-critical positions like software developers, engineers, or sales roles can multiply the cost of vacancy to 3-4 times the salary.
- A single delayed hire can stall a product launch, impact revenue projections, or create uneven workload distribution, affecting employee engagement.
The challenge is that enterprises must balance speed with quality, making every day a candidate spends in the pipeline count.
The paradox of rising time-to-hire despite more AI tools points to a deeper, human issue in the recruitment workflow – the “endless options” mindset, or what we call the Recruiter’s Dating App Trap.
Modern recruiting platforms and AI-generated resumes create a data deluge, where recruiters see hundreds or even thousands of candidates in a single talent pool. Like users on dating apps, recruiters often hesitate to commit, waiting for the “perfect match.”
This indecision is amplified by:
- High candidate volume, which overwhelms recruiters and hiring managers alike.
- Low-commitment workflows, where the sheer number of applicants discourages rapid engagement.
- Managerial indecision, with multiple stakeholders delaying feedback or approvals.
The result often leads to good candidates slipping away within the first two weeks of the process, often before a formal offer is extended.
A slow, inefficient hiring process creates a significant financial burden on an organization, extending far beyond simple recruitment expenses. The longer a position remains vacant, the greater the Cost of Vacancy, which severely impacts revenue, productivity, and employee morale. For revenue-generating roles, unfilled positions can result in lost deals or delayed project deliveries. A single unfilled sales role might cost millions in lost revenue during a quarter.
Teams carrying extra workloads experience burnout and lowered efficiency, while drawn-out processes signal organizational inefficiency to candidates, damaging the employer brand.
The sharp increase in time-to-hire is a result of chronic workflow inefficiencies. Enterprises must identify and dismantle these challenges to successfully compete for talent:
Recruiting teams are overwhelmed, with 27% of TA leaders reporting unmanageable workloads. This burnout is compounded by the fact that recruiters spend up to 35% of their time on interview scheduling alone. This administrative quicksand prevents them from focusing on the strategic, high-value work of closing a hire, leaving them stuck in the time-consuming loop of low-value tasks.
The ease of modern application and assessment tools has fueled a culture of endless options. Recruiters, faced with a large pipeline and the desire to avoid a costly “bad hire,” often hesitate, waiting for a perceived “better match.” This organizational indecision, often exacerbated by indecisive hiring managers, leads to delays in feedback and offer extension, causing high-quality candidates to lose interest after the first two weeks.
Traditional, manual, and distributed interview processes lack rigor. Different hiring managers ask different questions, making candidate comparison subjective and slow. This lack of standardization leads to prolonged internal debate and necessitates costly follow-up interviews, creating a feedback lag that adds days to the TTH.
Enterprises operate across time zones. A candidate in Asia may not be available during U.S. business hours, adding days to scheduling. Coordinating multiple stakeholders amplifies delays.
The only way to reverse the high time-to-hire trend is by moving from a sequential, manual process to a concurrent, data-driven one. An AI-powered video interviewing platform provides the necessary tools for this structural shift:
One of the biggest barriers in enterprise hiring is coordination – across stakeholders, departments, and time zones. Traditional scheduling alone consumes up to 35% of recruiters’ time. With asynchronous, on-demand interviews, candidates can record responses at their convenience, and recruiters can review them on their own schedule. This simple change removes the bottleneck, moving candidates from application to review in hours rather than days.
Decision-making delays, often caused by hesitation and a culture of endless options, are another major contributor to long time-to-hire. Modern platforms address this by analyzing responses for clarity, competence, and job fit, generating structured scores and transcripts for each candidate. This gives hiring managers clear, objective insights that cut through subjective debates and avoid the trap of waiting for a “better” candidate.
Enterprises need AI tools to drive efficiency without compromising fairness or compliance. Jobma’s ethical AI framework ensures all analyses remain transparent, auditable, and explainable. Instead of replacing human judgment, AI acts as a decision support layer, empowering recruiters with insights while preserving accountability. This approach ensures ethical alignment with evolving global standards for responsible AI in hiring.
Consistency in evaluation is equally crucial. Varied questions and evaluation styles can create uneven assessments and slow feedback loops. Standardized video interview ensures that every candidate responds to the same set of questions. It then evaluates responses, tone, and communication style to produce a standardized, defensible score. This consistency shortens the internal review cycle, helping strong candidates progress quickly through the funnel.
For enterprise teams managing thousands of applications or balancing diverse hiring needs – from permanent to contingent roles – scalability is essential. Jobma enables large-scale recruitment with automated screening, structured evaluations, and global accessibility. By eliminating repetitive tasks, standardizing assessments, and centralizing candidate data, it accelerates hiring cycles. Recruiters spend more time engaging with top candidates, leading to measurable gains in productivity and hiring ROI.
The candidate experience is central to achieving faster, more reliable hires. Modern talent expects a mobile-first, intuitive, and transparent hiring process. Video interviewing platform delivers an interface that is both user-friendly and responsive, providing rapid feedback and clear instructions throughout the process. By signaling that the organization values candidates’ time and operates efficiently, enterprises reduce drop-off rates and improve engagement, directly supporting time-to-hire goals.
Enterprises must maintain compliance across geographies and jurisdictions. They require a legally defensible and fully traceable process. Video interviewing platform like Jobma is built to meet global standards, such as SOC 2 Type II, GDPR, CCPA, EEOC, and ISO/IEC certification, ensuring every interview and data point is stored, processed, and accessed securely. Built-in audit trails and structured documentation make the entire process traceable, transparent, and audit-ready.
Structured interviews and AI scoring help reduce unconscious bias, ensuring that hiring decisions are based on relevant skills and experience rather than subjective impressions. By focusing evaluation on objective, role-specific criteria, enterprises can maintain fairness and improve the overall quality of hires, all while reinforcing diversity, equity, and inclusion initiatives.
Time-to-hire can also be slowed by fragmented systems. Jobma integrates seamlessly with major ATS and HRIS platforms, eliminating manual data transfer and keeping candidate information up to date across all systems. This connectivity ensures that recruiters and hiring managers have real-time visibility into the process, reducing delays caused by system barriers and improving operational efficiency.
Enterprises implementing AI-powered video interviewing have reported:
- Reduction in Time-to-Hire: One client using Jobma AI video interviewing platform has seen an 86% reduction in time-to-hire.
- Faster Decisions: Screening hundreds of candidates in days instead of weeks.
- Higher Completion Rates: Asynchronous interviews reduce candidate drop-off.
- Better Talent Matches: Consistent evaluation across all applicants improves quality-of-hire metrics.
- Higher Interview Completion Rate: A global enterprise using Jobma has seen a 94% increase in interview completion rate.
Source: Jobma Case Studies
The recruitment landscape has transformed dramatically over the past few years. Video interviewing has evolved from a pandemic necessity to an enterprise-grade strategic advantage. Today, global leaders such as Unilever, Deloitte, Nestlé, Wargaming, Lionsgate, and more have integrated video interviewing into their hiring workflows to improve consistency and scale. This shift is permanent, driven by both candidate preference and the undeniable need for efficiency.
- 82% of companies conduct video interviews regularly (Monster Employment Report).
- 50% reduction in time-to-fill and 70% decrease in scheduling time (Gartner, Deloitte).
- 70% of organizations now use AI-driven tools to screen and assess candidates (Global Growth Insights).
- 46% of candidates are more likely to consider jobs that incorporate video content in the hiring process (Lighthouse Research & Advisory).
Video interviewing has become a core part of modern talent acquisition, driven by candidate preferences and organizational need for efficiency.
AI is a tool, not a replacement. To maximize the efficiency gains offered by AI-powered video interviewing platforms and achieve the promised reduction in time-to-hire, enterprises must adopt new organizational practices:
- Mandate Time-Bound Feedback: Implement a strict Service Level Agreement (SLA) for hiring managers: Feedback on a video must be submitted within 12 or 24 hours of sharing the link. The speed of the AI process must be matched by the speed of the human decision.
- Train Recruiters for Strategy: Upskill recruiters to use the AI-generated data (scores, transcripts) as leverage in their conversations with hiring managers. Their role shifts from “scheduler” to “consultant,” driving the manager toward a swift, informed choice.
- Define the “Good Match” Threshold: Establish clear, data-driven thresholds based on the scoring rubric. If a candidate meets or exceeds the required threshold, the organization must be committed to moving them to the next stage immediately, avoiding the temptation of the “better match” waiting game.
- Audit the Pipeline Weekly: Use analytics to identify where candidates are stalling. If candidates are sitting in the “Hiring Manager Review” stage for too long, it’s a clear indication of a workflow or commitment failure that needs immediate human intervention.
AI in hiring is powerful, but it must be used responsibly:
- Bias Mitigation: The platform undergoes regular audits by its developers to detect and minimize unintended bias.
- Data Privacy: Platforms should comply with regulations such as GDPR, CCPA, and SOC 2 standards.
- Human Oversight: Critical decisions should always involve human judgment alongside AI insights.
When implemented thoughtfully, AI hiring platforms enhance efficiency and reduce the time-to-hire without compromising fairness and compliance.
Time-to-hire remains one of the most telling measures of hiring efficiency. Every delay increases recruitment cost and the likelihood of losing top candidates to faster competitors. Video interviewing tech has proven to be a practical way for enterprises to shorten hiring cycles, streamline coordination, and enable quicker, data-informed decisions.
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