OVI is the AI-native ATS where you chat to hire. Two AI agents — Sora for sourcing and Milo for screening — find candidates, score every CV, and run AI interviews, all controlled from a single chat.

What does "chat to hire" mean?

Chat to hire is OVI's AI-native hiring workflow: instead of clicking through a traditional ATS, you describe what you need in chat and OVI's AI agents source candidates, screen applicants, run AI interviews, and send outreach for you.

What is an AI-native ATS?

An AI-native ATS is an applicant tracking system built around AI agents rather than forms and pipelines. OVI's AI chat ATS lets recruiters source, screen, interview, and follow up through conversation — the agents do the work and surface only the candidates worth meeting.

Who are Sora and Milo?

Sora is OVI's AI sourcing agent — she scans LinkedIn, the open web, and your ATS history to find best-fit candidates and reach out in your name. Milo is OVI's AI screening agent — he scores every applicant against your rubric and surfaces a ranked shortlist.

How do OVI's AI interviews work?

OVI runs async AI interviews for every shortlisted candidate and returns scores, transcripts, and recordings — so your team only meets the people worth meeting.

Only 1 in 3 Recruiter Teams Has Mastered AI — And They're Making 9% Better Hires

2026-06-19

Nearly every talent acquisition team says it plans to use more AI this year. But LinkedIn's own data reveals an uncomfortable truth: the gap between AI ambition and AI mastery is widening — and only a minority of recruiter teams are capturing the performance gains.

According to LinkedIn's Future of Recruiting 2025 report, just 34% of talent acquisition teams qualify as AI "power users" — recruiters who strategically blend AI tools with human judgment across their workflows. These teams aren't just faster. Companies with the highest adoption of AI-Assisted Messaging — a hallmark power-user behavior — are 9% more likely to make a quality hire compared to the lowest-usage companies (LinkedIn Future of Recruiting 2025).

That 9% gap is the headline number every CHRO should be circling. In a labor market where a single bad hire can cost 30% or more of annual salary, a measurable quality-of-hire advantage isn't incremental — it's strategic.

The Bifurcation: Power Users vs. Practitioners

LinkedIn's Executive Confidence Index, cited in the Future of Recruiting 2025 report, segments TA teams into three tiers of AI maturity:

Power users (34%): These teams use AI not as a bolt-on but as an integrated layer across sourcing, outreach, screening, and candidate engagement. They pair AI outputs with recruiter expertise — editing AI-drafted messages, reviewing AI-surfaced shortlists, and using AI insights to refine job requirements.
Practitioners (47%): The largest group. These teams have adopted AI tools but use them in isolated, tactical ways — auto-generating job descriptions, for instance, without connecting AI outputs to downstream hiring decisions. They are still learning to deploy AI strategically.
The remaining ~19%: Early or minimal adopters who have yet to integrate AI into core recruiting workflows.

The takeaway: nearly half of all TA teams sit in a middle tier where AI is present but not yet productive. Closing the gap between practitioner and power user is where the ROI lives.

What AI Power Users Actually Do Differently

The "power user" label can sound abstract. LinkedIn's data points to specific behaviors that separate the 34% from the rest:

1. AI-Assisted Messaging at scale. Power-user teams use AI to draft, personalize, and optimize candidate outreach — then layer human judgment on tone, timing, and relationship context. This is the behavior most directly tied to the +9% quality-of-hire finding (LinkedIn Future of Recruiting 2025).

2. Pre-screening with AI support. Sixty-six percent of recruiters plan to increase AI use specifically for pre-screening interviews in 2026 (LinkedIn Future of Recruiting 2025). Power users are already there, using AI to handle initial qualification questions so recruiters can spend more time on high-signal conversations.

3. Skills-based hiring as the default. Seventy-five percent of recruiters say skills-based hiring is their top priority, and 25% of LinkedIn job postings already omit degree requirements (Future of Recruiting 2025). Power-user teams pair AI-driven skills matching with recruiter assessment to evaluate capability rather than credentials.

4. Investing in human-centric skills. Here's the counterintuitive finding: companies are now 54 times more likely to list "relationship development" as a required recruiter skill (Future of Recruiting 2025). As AI absorbs transactional tasks — scheduling, initial outreach, resume parsing — the recruiters who thrive are the ones who double down on empathy, negotiation, and candidate experience. Power users understand that AI handles volume; humans handle nuance.

The Macro Context: Why This Gap Will Widen

The pressure to close the power-user gap isn't theoretical. LinkedIn's Work Change Report (January 2026) projects that 70% of the skills used in most jobs will change by 2030. Since 2022, LinkedIn members adding new skills to their profiles has grown 140% — a signal that the workforce is already adapting, whether or not TA teams are keeping pace.

Meanwhile, AI is reshaping the labor market itself. According to LinkedIn Economic Graph data reported by the World Economic Forum, AI has already created 1.3 million new jobs globally — roles like AI engineers, data annotators, and forward-deployed engineers that didn't exist at scale five years ago. Job postings requiring AI literacy grew more than 70% year over year (LinkedIn Economic Graph 2026).

For TA teams, this creates a compounding challenge: you need AI fluency to hire for AI-fluent roles. The 34% who already operate as power users have a structural advantage in sourcing and evaluating candidates for the fastest-growing job categories.

What HR Leaders Should Do Now

The data makes the case. Here's how to act on it:

For TA Directors: Audit your team's AI maturity against LinkedIn's three-tier framework. Identify which workflows are AI-assisted (practitioner) versus AI-integrated (power user). The gap is almost always in how AI outputs connect to hiring decisions — not in whether tools are installed.

For L&D Leads: Build AI fluency programs specifically for recruiters, not generic "AI literacy" courses. Focus on the behaviors that drive outcomes: AI-assisted messaging, skills-based candidate evaluation, and interpreting AI-surfaced data. The 140% increase in skills additions across LinkedIn shows the workforce is hungry for upskilling — your recruiters should be, too.

For CHROs: Treat recruiter AI fluency as a quality-of-hire initiative, not a technology rollout. The 9% quality-of-hire advantage isn't about the tool — it's about the capability of the team using it. Budget accordingly: invest in training and workflow redesign, not just software licenses.

With 93% of TA professionals planning to expand AI use in 2026 (Future of Recruiting 2025), adoption isn't the bottleneck. Mastery is. The 34% of teams that have crossed that line are already making better hires. The question for the other 66% is how long they can afford to wait.