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.

The 20% Problem: Why Talent Readiness Is Enterprise AI's Critical Bottleneck

2026-06-19

Enterprises have spent billions on AI infrastructure. They have modernised data pipelines, deployed large language models, and piloted generative tools across every function. Yet according to Deloitte's State of AI in the Enterprise 2026 survey — covering 3,235 business and IT leaders across 24 countries, fielded August–September 2025 — only 20 per cent of organisations rate their talent readiness as high. Infrastructure readiness, by contrast, sits at 43 per cent. That 23-point gap is the clearest signal in the report: the bottleneck for enterprise AI is no longer hardware or software. It is people.

The readiness gap in numbers

The talent shortfall is not an abstraction. Deloitte's data shows that 84 per cent of organisations have not yet redesigned jobs or workflows around AI capabilities (Unite.AI). Most are layering AI on top of legacy processes — 37 per cent report using the technology at surface level with little or no structural change (Deloitte US).

Meanwhile, automation expectations are accelerating: 36 per cent of leaders expect at least 10 per cent of jobs to be fully automated within one year, and 82 per cent anticipate significant automation within three years (Eastgate Software). The workforce is being asked to absorb change at a pace that current upskilling programmes are not designed to support.

Access without adoption

Enterprise-approved AI tool access expanded roughly 50 per cent year-over-year, reaching approximately 60 per cent of workers. But access alone has not translated into adoption: fewer than 60 per cent of employees with approved tools use them regularly (Unite.AI). The gap between availability and habitual use suggests that organisations are clearing technical barriers while leaving behavioural and capability barriers in place.

Employee sentiment adds nuance. Just 13 per cent of non-technical workers express high enthusiasm for AI, while 55 per cent are open, 21 per cent prefer to avoid it, and 4 per cent actively distrust the tools (Unite.AI). The majority are persuadable — but only if organisations invest in the right enablement.

The upskilling response — and its limits

Organisations are responding, though unevenly. 53 per cent are educating their broader workforce for AI fluency, and 48 per cent are running upskilling or reskilling programmes. But only 33 per cent are restructuring career paths to reflect new AI-augmented roles (Deloitte Global). Training without structural redesign risks producing AI-literate workers who have no clear path to apply what they have learned.

"Across the enterprise, we're seeing massive ambition around AI, with organizations starting to pivot from experimentation to integrating AI into the core of the business," said Nitin Mittal, Deloitte's Global AI Leader (Deloitte US). That pivot demands a matching investment in human capability.

Productivity gains are real — revenue gains are not (yet)

The business case for closing the talent gap is already visible. 66 per cent of organisations report productivity and efficiency gains from AI, while 53 per cent cite enhanced decision-making. Yet only 20 per cent are currently growing revenue through AI — even as 74 per cent aspire to (Deloitte Global). The delta between productivity uplift and revenue growth is where talent readiness becomes a strategic differentiator.

"The organizations succeeding with AI aren't just investing in automation and algorithms, they're investing in their people," noted Jim Rowan, US Head of AI at Deloitte (Deloitte US).

Agentic AI raises the stakes

The talent gap matters even more as organisations move toward autonomous systems. Nearly 75 per cent plan to deploy agentic AI within two years, yet only 21 per cent have mature governance frameworks in place (Eastgate Software). Deploying agents without governance — or without workers who understand how to supervise them — compounds risk.

What HR leaders should do now

The Deloitte data makes the action plan clear: close the gap between tool deployment and workforce capability.

Audit readiness, not just access. Knowing how many employees have AI tools is table stakes. Measure how many can use them effectively and how many roles have been redesigned to leverage AI. Platforms like OVI can help quantify workforce readiness across hiring and internal mobility, giving HR teams data to prioritise where upskilling will generate the most return.
Redesign roles before automating them. The 84 per cent figure is a call to action. Restructure workflows first, then automate — not the reverse.
Build career paths for AI-augmented work. If only a third of organisations are redesigning career progression, that leaves two-thirds with a workforce that has no clear route to grow alongside AI.
Treat governance as a talent function. With agentic AI on the horizon, HR must co-own governance with IT — defining human oversight boundaries, audit processes, and accountability frameworks.

The 20 per cent talent readiness number is not a verdict. It is a starting line. Organisations that move first to close the gap will convert AI's productivity promise into sustained competitive advantage.

Sources:

Deloitte, "State of AI in the Enterprise 2026" (Global hub) — deloitte.com
Deloitte US, "From Ambition to Activation" press release, March 2026 — deloitte.com
Unite.AI, "Deloitte Maps the Untapped Edge" — unite.ai
Eastgate Software, "Enterprise Execution Lags Adoption" — eastgate-software.com