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.

LTIMindtree Is Putting All 87,000 Employees Through MIT's AI Curriculum — Here's the Playbook

2026-06-19

Most corporate AI training is PowerPoint theatre — a half-day workshop, a certificate, forgotten by Monday. LTM (formerly LTIMindtree) just bet differently: every one of its 87,000+ employees will complete MIT's "Universal AI" curriculum, earning an MIT-issued credential. No coding required. No carve-outs. The entire organisation.

Announced on April 6, 2026, the initiative is delivered through upGrad Enterprise and marks one of the largest single-company enrolments in an academic AI programme to date.

What the programme actually is

Universal AI is an MIT Open Learning curriculum structured as 16 self-paced modules built by MIT faculty. It covers how AI systems work, the technologies beneath them, and the ethical questions they raise. Critically, there are no coding prerequisites — the programme is designed for finance, HR, operations, and legal professionals just as much as engineers.

Participants who complete the curriculum receive an MIT Open Learning certificate — an externally recognised credential that carries weight beyond an internal badge on a company intranet.

"With AI advancing rapidly, the importance of human intervention in AI solutions is crucial for effective functioning and optimised outcomes," said Gururaj Deshpande, Chief Delivery Officer at LTM. The message is clear: AI fluency is no longer an engineering function — it is an organisational capability.

Why 87,000 matters

Most enterprise AI upskilling touches hundreds, maybe a few thousand employees in a pilot cohort. Enrolments at the 87,000 level represent full-organisation deployment — not an experiment, but a strategic commitment.

The delivery mechanism matters too. LTM partnered with upGrad Enterprise to handle the logistics of onboarding, pacing, and credentialing at this scale. As upGrad Chairperson and Co-Founder Ronnie Screwvala put it: "Providing upskilling opportunities in AI to employees bridges capability gaps with speed, scale, and precision."

This is a model worth noting: academic rigour (MIT) plus at-scale delivery infrastructure (upGrad Enterprise) plus role-agnostic design (no coding gate). Each element solves a different barrier that stalls most L&D programmes.

The enterprise upskilling gap

LTM's move gains sharper context against recent workforce data. According to IBM's 2025 CEO study, 59 percent of enterprise leaders report a significant AI skills gap in their organisations, yet only 35 percent have a mature, org-wide AI upskilling programme in place. Among those that do, AI return on investment nearly doubles.

The gap is not awareness — every CHRO knows AI upskilling is on the agenda. The gap is execution. DataCamp's 2026 analysis found that 54 percent of CEOs are hiring for AI roles that did not exist a year ago, while 31 percent of the broader workforce will need retraining within three years.

These numbers make the case for programmes that move beyond targeted cohorts. When a third of your workforce needs reskilling, a pilot that reaches 500 people is not a strategy — it is a rounding error.

What HR leaders should steal from this

LTM's playbook contains four moves that any L&D or HR team can adapt:

1. Don't gatekeep AI literacy to technical roles. The Universal AI programme has no coding prerequisites by design. When only engineers understand AI, the rest of the organisation cannot meaningfully govern, deploy, or evaluate AI-powered workflows. LTM's approach treats AI fluency as a core competency, not a specialist skill.

2. External credentials beat internal badges. An MIT Open Learning certificate on a LinkedIn profile does something an internal completion badge cannot — it signals market-recognised competence. That matters for retention (employees value portable credentials) and for employer branding (the market sees you invest in your people).

3. Platform partnerships enable scale L&D teams alone can't achieve. Running a 16-module academic programme for 87,000 employees requires infrastructure that most corporate L&D functions do not have in-house. upGrad Enterprise handles delivery, pacing, and support — freeing LTM's internal teams to focus on adoption and business alignment.

4. Tie upskilling to a business thesis, not just "future readiness". Deshpande's framing is precise: human intervention in AI solutions is what makes them function effectively. The programme is not upskilling for its own sake — it supports a specific operating model where humans and AI work together, and every employee needs to understand both sides.

The bottom line

The question for HR leaders is no longer whether to run AI upskilling. It is whether your programme moves skill levels at scale — or just ticks a compliance box.

LTM enrolling its entire 87,000-person workforce in an MIT curriculum, with no role-based gatekeeping and external academic credentialing, is a clear signal of what serious enterprise AI literacy looks like in 2026.

If your AI training strategy is still a half-day workshop and a survey, it is time to rethink.

Sources: ANI News, The CSR Universe, DevDiscourse, TradingView/Reuters, IBM Newsroom (2025 CEO Study), DataCamp (2026 AI ROI Analysis)