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.

82% of Companies Fund AI Training, But Only 21% See Real ROI — Here's Why

2026-06-19

82% of Companies Fund AI Training, But Only 21% See Real ROI — Here's Why

Most enterprises have answered the AI skills question with a budget line. The harder question — whether that spending is working — most have not.

A February 2026 survey of 517 business leaders conducted by DataCamp and YouGov found that 82% of companies now provide some form of AI training to their workforce. Yet only 21% report seeing a meaningful return on that investment. (BusinessWire, Feb 26 2026)

That 61-point gap is the defining L&D problem of 2026. And the data tells us exactly why it exists — and how to close it.

What the Numbers Actually Say

The DataCamp/YouGov survey reveals a skills landscape in transition. While 82% of companies are funding AI training, 59% of respondents still identify a significant AI skills gap inside their organization. Something is clearly getting lost between the training budget and the training outcome.

The most telling finding: only 35% of companies describe their AI learning programs as "mature" — meaning structured, role-specific, and integrated into broader talent strategy. Among that group, reported ROI nearly doubles compared to companies with ad-hoc or informal programs.

In other words, it's not whether you're spending on AI training. It's how.

Why Most Programs Fail to Deliver

The gap between funding and return comes down to four structural failures:

1. No measurement framework. Most organizations cannot define what AI training success looks like. Without measurable skill benchmarks or performance indicators tied to AI capability, it's impossible to know whether training moved the needle.

2. Ad-hoc delivery, not structured curricula. Many companies are offering one-off webinars, optional e-learning modules, or generic vendor training. This creates pockets of knowledge rather than organizational capability. IDC and Workera's research on AI skill development consistently finds that unstructured programs produce minimal workforce-level impact regardless of participation rates.

3. No manager accountability. When managers are not held responsible for their team's AI skill progression — and not equipped to reinforce learning on the job — training evaporates after the session ends.

4. Tools without strategy. Deploying AI tools and calling it "training" is one of the most common misfires. Access to a tool is not the same as knowing how to use it strategically. The DataCamp 2026 report notes that organizations conflating tool rollout with upskilling consistently report lower ROI. (DataCamp State of AI Training 2026)

What Mature Programs Look Like

The 35% of companies achieving near-doubled ROI share a common architecture:

Role-specific learning paths rather than one-size-fits-all modules. A finance analyst, a recruiter, and a software engineer have different AI skill needs — mature programs treat them accordingly.
Structured curricula with assessments. Competency benchmarks before and after training allow organizations to demonstrate progress and identify gaps that persist.
Manager integration. Learning is connected to performance conversations. Managers receive coaching on how to reinforce AI skill application in day-to-day work.
Hiring and onboarding alignment. Mature programs treat AI capability as a continuous pipeline, not a one-time initiative. New hires enter a structured onboarding track; existing employees are on a defined progression ladder.

Four Moves to Shift from Ad-Hoc to Mature

If your organization is in the 65% with informal AI training, here are the highest-leverage actions:

Define your AI skill taxonomy. Identify the 5-10 AI competencies that actually matter for your business — segmented by role family. This is the foundation everything else builds on.
Audit current programs against that taxonomy. Map what you're offering today against what you need. The gaps become your roadmap.
Assign ownership to managers. Build AI skill development into manager OKRs. Budget without accountability is wasted.
Build a measurement loop. Pre/post skill assessments, application metrics, and business outcome tracking don't need to be complex — they need to exist. Even simple skill confidence surveys, run consistently, create the feedback mechanism most programs currently lack.

The Bottom Line

Eighty-two percent of companies have made the easy decision: fund the training. The harder decision — building a program with the structure, accountability, and measurement needed to deliver results — is what separates the 21% seeing ROI from everyone else.

The gap won't close with more budget. It closes with maturity. The organizations that figure this out in 2026 will spend less and gain more than those still running ad-hoc programs by 2027.

Sources:

DataCamp/YouGov Survey, Feb 26 2026 (n=517 business leaders) — via BusinessWire: https://www.businesswire.com/news/home/20260226875765/en/DataCamp-YouGov-Survey-AI-Training-ROI
IDC/Workera AI Skills Gap Research
DataCamp State of AI Training 2026: https://www.datacamp.com/blog/state-of-ai-training-2026