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.

SHRM: AI Adoption in HR Jumped 17 Points in a Year — But the Real Barrier Isn't Tech

2026-06-19

In just one year, the share of organizations using AI in HR functions surged from 26% to 43%, according to SHRM's State of AI in HR 2026 report, based on a December 2025 survey of 1,908 HR professionals. The efficiency gains are tangible. Yet adoption remains below the halfway mark — and the reason has less to do with technology than with something far harder to engineer: human preference.

For HR leaders weighing their next move on AI, this report delivers a clear message. The tools are working. The bottleneck is organizational readiness and, crucially, what employees actually want.

The Efficiency Case

Among organizations already using AI in HR, the productivity signal is strong — though it comes with caveats. Eighty-nine percent of AI-using organizations report greater operational efficiency, a figure that is self-reported and should be read as directionally informative rather than independently verified (SHRM Full Report).

The functional impact is concentrated in specific areas. Recruiting leads as the top use case at 27%, followed by HR technology management (21%), learning and development (17%), and employee experience (14%) (SHRM Press Release). On the cost side, 36% of adopters report lower hiring costs, while 24% say AI has improved candidate identification (SHRM Full Report).

These are meaningful numbers for talent acquisition leaders under pressure to hire faster with tighter budgets. But they describe the experience of adopters — not the full market.

Not Everyone's Moving at the Same Speed

The 26%-to-43% headline masks a significant gap between large enterprises and smaller organizations. Sixty percent of extra-large organizations report using AI in HR, compared to just 33% of small organizations and 35% of midsize ones (SHRM Full Report; HCAMag).

Among non-adopters, the barriers are more foundational than technical. Sixty-seven percent cite lack of awareness about available AI tools as their top obstacle, and 49% point to insufficient internal data to support AI implementation (SHRM Full Report). For small and midsize HR teams, the challenge is less about evaluating AI and more about knowing what exists in the first place.

This matters for vendors and internal champions alike: the adoption gap is partly an information gap.

The Real Barrier Is Human

Here is where the data gets most interesting. Even among those who understand AI's potential, enthusiasm has a ceiling. Seventy-two percent of HR professionals say that nontechnical barriers alone would prevent full automation of HR processes (SHRM Full Report).

The single largest nontechnical barrier? Employee preference for human interaction, cited by 87% of respondents as a primary concern (SHRM Full Report; SHRM CHRO Insights).

This is not a technical limitation to solve — it is a signal about what people value. Employees want human judgment and empathy in decisions that affect their careers, compensation, and wellbeing. HR leaders who treat this as mere resistance to change risk alienating the workforce they are trying to serve.

As SHRM's own analysis of AI hype cycles notes, the gap between what AI can theoretically do and what organizations should deploy it for remains a live strategic question.

What's Next for HR

Despite these barriers, the direction of travel is clear. Ninety-two percent of CHROs expect further AI workforce integration in 2026 (SHRM CHRO Insights). The skills demands are following: 83% of HR leaders and 76% of workers acknowledge the need for new competencies to work effectively alongside AI (SHRM Press Release).

One underexplored tension: who owns the AI rollout in HR? The SHRM data suggests ongoing ambiguity, with IT and legal departments often perceived as the primary leaders of AI governance, even when the most impacted processes sit squarely within HR (HCAMag). For CHROs, asserting a seat at the AI strategy table is no longer optional.

Conclusion

The SHRM data paints a nuanced picture. AI in HR is no longer experimental — 43% adoption, real efficiency gains, and near-universal CHRO buy-in confirm that. But the path to broader adoption runs through people, not platforms. Addressing the human-centered barriers — awareness, skills readiness, and genuine respect for employee preferences — will determine whether the next 17-point jump happens in one year or five.

The organizations that get this right will be the ones that treat AI as a tool that augments human judgment rather than one that replaces it.

Note: The SHRM State of AI in HR 2026 report is based on a December 2025 survey of 1,908 HR professionals. SHRM is a professional membership body with a stake in advancing HR practice, including AI adoption. Data should be considered in that context. Given the pace of change in AI, these findings represent a snapshot that may shift rapidly.

FAQ

How representative is the 43% adoption figure?
The SHRM survey polled 1,908 HR professionals across organization sizes and industries. However, adoption varies sharply by company size — 60% at extra-large organizations versus 33% at small ones. The 43% aggregate should not be read as a universal benchmark (SHRM Full Report).

What should HR leaders who haven't adopted AI do first?
SHRM's data suggests the biggest barrier for non-adopters is awareness (67%), not budget or technical complexity. A practical first step: audit the AI tools already embedded in your HR tech stack. Many platforms now include AI features that may be underutilized. Pair this with a skills assessment — 83% of HR leaders acknowledge they need new competencies to work alongside AI (SHRM Press Release).

Does the preference for human interaction mean AI has no role in employee-facing HR?
Not necessarily. The 87% figure signals that employees want human involvement in consequential decisions — not that they reject all AI interaction. Tools that handle administrative tasks (scheduling, benefits queries, initial screening) while preserving human judgment for decisions like hiring, promotions, and performance reviews align with this preference. The key is designing human-in-the-loop workflows rather than fully automated ones (SHRM CHRO Insights).