Eynat Guez Built a $3.7B Company for AI’s Hiring Boom

The world’s most ambitious companies no longer build their workforce in one city, one country, or under one employment model. An AI lab has researchers in London and Zurich, engineers in Tel Aviv and Bangalore, and a data operation spread across a dozen countries where the people labelling and reviewing model outputs are contractors, agency staff and gig workers rather than employees. A robotics company opens a site, then another, then acquires a third with its own workforce attached. They recruit, manage and pay people wherever the right talent exists, and they need to do it faster than the regulations governing that work can change.

Eynat Guez has a number for where this is going. Today, contingent workers make up roughly a fifth of a typical enterprise workforce. By her company’s projection, that share is heading toward 40 to 48 percent. The global gig workforce grows more than fourfold in the same window. The people labelling data to train AI models, about 3 million today, will become 35 million.

“Contingent labour is entering the core workforce,” the co-founder and CEO of Papaya Global told a room of analysts in Tel Aviv on September 9. It was not framed as a warning. Papaya provides the infrastructure that makes that workforce possible, and Guez has been building toward it long before there was a company.

Before the category existed

Guez was born in France and moved to Israel with her family at four, settling in Netanya. As a teenager, she was a competitive swimmer and a working journalist. She served in the Israel Defense Forces as an adjutant in an F-16 squadron, a job that is largely logistics: making sure people and resources are where they need to be, when they need to be there.

That turned out to be the career. In 2002 she joined LR Group, an Israeli holding company building infrastructure projects across Africa, and spent seven years as its chief operating officer, running HR and operations for a workforce scattered across developing countries, including a stint managing a new mobile operator’s project in Conakry, Guinea. It was global workforce management before the term had a market: expatriate relocation, talent sourcing across borders, payroll in currencies most software had never heard of, held together by people and spreadsheets.

In 2008 she quit. In early 2009 she founded Relocation Source, a corporate relocation and mobility firm that still operates today. Four years later came Expert Source, a professional employer organization helping U.S. companies expand into East Asia. By the time she co-founded Papaya Global in 2017 with Ofer Herman and Ruben Drong, she had spent fourteen years inside the problem she was about to build for, and she had a conviction most of the industry did not share: paying people across borders was not a software problem. It was an infrastructure problem wearing software’s clothes.

One infrastructure, not a stack of workarounds

Investors did not see it that way at first. Guez has spoken candidly about the early rejections, and about raising a round while pregnant with one of her three children. When Papaya broke through, it became the first Israeli unicorn led by a woman, was valued at $3.7 billion at its Series D, and moved its headquarters to New York. It has raised $450 million, reports 40 percent-plus annual growth and 97 percent enterprise retention, and serves more than 3,000 companies including Shopify, Nebius, Ericsson, Infosys and FIFA.

What Guez built is different in kind from the “hire anyone, anywhere” tools that defined the category after 2020. Papaya’s platform connects worker classification, compliance, workforce management and real-time payments across more than 180 countries, 110 of them with native gross-to-net and employer-of-record coverage, in 130 currencies. Instead of navigating fragmented local systems, changing regulations, and disconnected payment processes, a company manages its entire global workforce employees, contractors, agencies, and contingent workers, through one integrated infrastructure, in one record.

The decision that made that possible was the one competitors did not make. In 2022, Papaya acquired Azimo, a licensed cross-border payments company, and with it the ability to hold and move client money itself. Today it holds six money licences across the U.K., Europe, Hong Kong, Australia, Canada and the U.S. Client funds sit with J.P. Morgan and Citi. More than $50 billion a year moves through rails Papaya owns, and 95 percent of direct payments settle in real time.

“When you move payroll for global enterprises, you are holding their money in transit,” Guez told analysts. What matters, she said, is the capital behind the company, the banks under the rails, and the record. That is what she means by infrastructure: workforce data and payment execution operating together in one system, so every worker can be classified correctly, managed according to local requirements and connected directly to automated payment flows. It removes the delays, payment errors, and compliance exposure that have always come with international expansion, and it is why the company can point to zero compliance claims to date.

Built for companies that scale in weeks

The case Guez made to analysts is that this becomes critical for companies operating at the speed of the AI economy. An AI or robotics business may need to onboard a large and diverse workforce quickly, support several worker types at once, and change the shape of that workforce as operational demand changes. By Papaya’s count, it is doing that across 48 countries that require staffing licences, 32 that cap how long an employer-of-record arrangement can run, and 65 with strict contractor-classification tests. Its workforce infrastructure has to be as dynamic as the technology it is building.

Papaya’s answer is an operating model that chief product officer Amit Levi laid out in four layers. A data layer, OneData, ingests HR, time, and expense data from any system as it arrives and maps it in flight. Five AI agents, for connecting data, checking compliance, hiring, validating, and paying, run on top of it. A compliance engine called Papaya ONE grounds every decision in local regulation, the company’s own policies, and cited sources; asked on stage whether a role could be hired in the Netherlands under a contingent-workforce policy, it returned the recommended path, the policy it relied on, cited Dutch sources, and a list of what it would not decide alone. And above the agents sits a team of in-country human experts who handle the ambiguous cases, approve anything consequential before it executes, and own the outcome. “AI scales execution,” Levi’s slide read. “Experts assure outcomes.”

Speed is built in. Forward-deployed engineers map a customer’s real operation and build customised agents around it during migration, with payroll live within one cycle, standard onboarding the same day, and a stated ambition of 40-plus countries and 20,000-plus workers in under eight months. Measured on Papaya’s own operation, support tickets are down 24 percent and manual checks per payroll cycle down 55 percent.

Two customers made the case in person. Andrew McAulay, who runs EMEA payroll across 18 countries for Illumina, described consolidating a patchwork of manual processes onto one partner. Sara Avital, payroll director at CyberArk, said payroll never missed a cycle through four acquisitions and the company’s own $25 billion sale to Palo Alto Networks, completed in February.

Real-time payments, and the worker at the end of them

Real-time payment is the centre of the infrastructure, and the product that shows where Guez is taking it is aimed at the worker rather than the enterprise. Banco, live now, gives each worker their own account and Visa card. Earnings land in seconds rather than three to five banking days. No local bank account is required. One account follows the worker across the countries they work in, at up to 80 percent lower cost per payout, and it accepts income from other payers as well.

Set against her demographics, a workforce heading toward half contingent, much of it in markets where bank access is the barrier, it is a financial-wellbeing product for the people who will do an increasing share of the world’s work. Workers get a consistent experience wherever they are. Employers get visibility, control and confidence across every market. And for anyone who remembers her first job, it closes a loop: the woman who once spent her days making sure workers in Guinea got paid now runs a company that can do it in seconds.

Building around opportunity, not geography

Guez has built Papaya with a 50 percent female workforce, a rarity in enterprise software, and has been named by Fortune among the most powerful women in tech. She has been candid about the loneliness of the CEO role and about running a company through a pandemic while pregnant. None of that made it onto an Analyst Day slide. What did was a set of forward targets: threefold AI productivity in 2026 and more than 35 percent of revenue from autonomous agents and services by 2027, each labelled as a target, with a request that analysts hold the company to the labels.

The result she is describing is a unified operating layer for the global workforce: flexible enough for new employment models, compliant across every jurisdiction, and scalable enough to support companies that grow in weeks rather than years. It gives the most innovative companies the freedom to build their workforce around opportunity rather than geography, and to expand without operational or regulatory boundaries.

Papaya’s tagline for it is six words: build anywhere, employ everywhere, pay in real time. Guez arrived at it not through a strategy deck but through two decades of being the person responsible when someone, somewhere, did not get paid. As work becomes more distributed, more dynamic, and more global, that may turn out to be the most valuable experience in the industry.