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.

Saudi Arabia Declared 2026 the Year of AI — Here's How Its Giga-Project Companies Are Building Hiring Systems for Jobs That Don't Exist Yet

By Tim Kreling, Co-Founder, OVI

Published 2026-07-03

Somewhere in Riyadh, a hiring manager at King Salman International Airport needs to fill a role that didn't exist three years ago: an AI-integrated passenger flow architect responsible for coordinating autonomous systems across a facility designed to handle 120 million passengers annually by 2030. There is no job board keyword for this position. There is no talent pool of candidates with five years of experience in it. The traditional applicant tracking system has nothing to match against.

This is the hiring reality Saudi Arabia's giga-projects now face — and the reason the Kingdom's 2026 Year of AI designation matters far beyond technology policy.

A Whole-of-Government AI Commitment Reshaping the Labor Market

The Saudi Cabinet officially designated 2026 as the Year of Artificial Intelligence — a whole-of-government initiative centralizing AI across all ministries and agencies. The decision follows extraordinary investment: $9.1 billion in AI sector funding through 70 deals in 2025, bringing the number of companies operating in Saudi Arabia's data and AI sector to 664.

The Kingdom already ranks first globally in public sector AI adoption, with 98% of government workers reporting they have used AI at work. Through its SAMAI program, Saudi Arabia trained 1.1 million citizens with accredited AI certifications in 2025 — 52% of them female — with 11,000 specialists in advanced AI fields and a target of 20,000 AI and data specialists by 2030.

These are not abstract technology indicators. They signal that Saudi Arabia is generating an entirely new category of workforce — and the hiring infrastructure to staff it doesn't yet exist.

Giga-Projects Creating Roles Without Precedent

The scale of Saudi Arabia's giga-project ambitions is staggering. King Salman International Airport targets 120 million passengers by 2030, with expansion plans reaching 185 million by 2050. Marafy, Jeddah's new mixed-use waterfront development, is being built for over 130,000 residents — creating urban management role categories with no historical benchmark. HUMAIN, the Public Investment Fund-backed AI company launched in 2025, is building entirely new company categories within the Saudi AI ecosystem, with AI specialists already commanding salaries 20% above the global average.

Each project requires thousands of workers in roles that sit at the intersection of emerging technologies and traditional industries — AI infrastructure engineers who understand airport logistics, smart city operations managers who coordinate IoT sensor networks, and compliance officers who must navigate both Saudization mandates and novel AI governance frameworks.

Modern data center and digital infrastructure CEOs must now integrate expertise across capital allocation, cybersecurity, energy supply, and customer demand simultaneously — a dramatic shift from a decade ago when success focused primarily on operational reliability. Boards are increasingly recruiting from adjacent expertise areas to fill capability gaps that didn't exist five years ago.

Why Traditional ATS Fails the Novel-Role Challenge

Traditional recruitment technology relies on backward-looking pattern matching: scan resumes for keywords that match a job description, rank candidates by years of experience in named roles, and filter by credential requirements established for existing job categories.

This approach breaks down when the roles themselves are unprecedented. Research shows that companies with strong talent pipelines reduce time from application to hiring by up to 75%, but building those pipelines requires identifying transferable competencies rather than matching historical job titles.

The talent competition compounds the urgency. In technical markets, 70% of workers receive multiple job offers when switching roles — the decision window is often shorter than the time it takes a recruiter to discover and screen candidates manually. Across hiring markets, 90% of employers now use automation to filter applications, meaning initial screening decisions happen before a recruiter ever sees a resume.

For Saudi Arabia's giga-projects, the math is unforgiving. When you need to fill hundreds of novel roles while operating under Saudization (Nitaqat) quotas that carry real enforcement consequences — including fines and visa restrictions for non-compliance — the gap between what traditional hiring systems can deliver and what these projects require becomes existential.

AI-Powered Talent Engineering as the Path Forward

The answer emerging across Saudi Arabia's giga-project ecosystem is rubric-based competency screening: instead of matching keywords, AI systems assess candidates against structured competency frameworks that define what success looks like in a new role — even when no one has held that role before.

This shifts the fundamental question from "Does this resume contain the right keywords?" to "Does this person demonstrate the reasoning, domain adaptability, and technical foundations required for a role that will evolve as it's built?"

Tools built on this principle are already operating in the region. OVI, an AI-native ATS, uses two agents — Sora for proactive sourcing and Milo for rubric-based audio screening — to assess competencies where no keyword history exists. Milo's audio chat evaluates how candidates think through unfamiliar scenarios, directly relevant when the scenarios themselves are unprecedented. Sora's proactive pipeline building supports organizations working toward Saudization workforce targets by identifying candidates with transferable skills from adjacent industries.

What This Means for HR Leaders

Saudi Arabia's giga-project hiring challenge is a preview of what every organization will face as AI-driven roles proliferate globally. The Kingdom arrived first because it committed $9.1 billion and 664 companies to the problem simultaneously.

For HR leaders watching from outside the region, the lesson is clear: if your hiring system depends on matching candidates to roles that already exist, you are building on infrastructure that will break the moment your organization creates something genuinely new.

Frequently Asked Questions

What is Saudi Arabia's Year of AI 2026?

The Saudi Cabinet officially designated 2026 as the Year of Artificial Intelligence, a whole-of-government initiative centralizing AI strategy across all ministries and agencies. It follows $9.1 billion in AI investment and brings the number of data and AI companies operating in the Kingdom to 664.

Why do Saudi giga-projects struggle with traditional hiring systems?

Projects like King Salman International Airport (120M passengers by 2030) and Marafy Waterfront (130,000+ residents) create roles with no historical precedent — AI infrastructure engineers, autonomous systems coordinators, smart city operations managers. Traditional keyword-matching ATS platforms cannot identify candidates for roles no one has held before.

How does Saudization affect giga-project hiring?

The Nitaqat program mandates specific quotas for Saudi nationals in private-sector roles, with 2026 requirements stricter than previous years. Non-compliance carries fines and visa restrictions, adding urgency to building AI-powered talent pipelines that can identify qualified Saudi nationals with transferable skills.

What is rubric-based competency screening?

An AI-driven approach that assesses candidates against structured competency frameworks rather than keyword matching. Instead of searching for exact job title matches, the system evaluates whether candidates demonstrate the reasoning and adaptability required for new roles — even when those roles have no hiring history.

How many AI specialists is Saudi Arabia training?

Through the SAMAI program, Saudi Arabia trained 1.1 million citizens with AI certifications in 2025 (52% female) and 11,000 specialists in advanced AI fields. The Kingdom targets 20,000 AI and data specialists by 2030.