Ryan Saab

From Corporate Finance to Casting Rooms

Saab did not begin in talent. His early career was in corporate finance, work with no connection to recruitment, before he made what he calls the jump into helping people find opportunity. What followed was less a career change than a natural accumulation.

Working across the entertainment industry in New York City, Los Angeles, and Las Vegas, Saab helped build a company serving pre-professional and professional singers, dancers, and actors all over North America. The client list of aspiring artists grew large enough that the dynamic reversed itself: companies seeking talent began coming to him. Crucially, the firm was never an agency. It operated as an intermediary rooted in education and career development, preparing artists for the realities of the work and feeding them directly into large-scale entertainment operations and organizations.

That model made him something unusual. In earlier roles, Saab became the single source for recruitment strategy across very niche, specific entertainment platforms, the person organizations called when the requirement was specialized and the volume was high. The enterprise role he holds now grew out of exactly that reputation.

A Pragmatist on AI

Saab has watched the past year closely and reports a very big uptick in resumes and documents that are clearly written by AI. He is notably unbothered by it. "I personally don't see an issue with leveraging AI to help position yourself in a way that's authentic and real and accurate to what you can actually do," he says.

His reasoning is grounded in access, and it is the most distinctive idea he offers. Assembling a resume or CV package that a recruitment process will actually read is a specialized skill. Some candidates cannot afford help with it, some have no access to anyone who can teach them, and some simply do not understand what is expected of them. Tools that optimize a submission with ATS keywords and the other things that genuinely help, Saab argues, have opened up the door to those people. He sees real benefit there, and he believes the technology can be leveraged on both sides of the table.

The line he draws is precise. The problem arises when what is presented does not align with the actual experience. That, he says, is the moment to take pause, and he treats it as a vetting problem rather than a technology problem.

Vet Through It

For peers navigating 2026, his counsel begins with acceptance: AI is going to continue to be a presence in the recruitment environment, and pretending otherwise is not a strategy. The work, then, is learning to identify it and then to vet through it. That means taking the opportunity to understand and really analyze what you are looking at from a talent recruitment standpoint, and doing the work to confirm the information is accurate once you are speaking with the person directly.

He frames it as a leadership obligation rather than a personal habit. It is the job of leaders in the industry, he says, not only to teach their teams but to practice the same discipline themselves, navigating toward confirmation that whatever has been presented is genuinely accurate and applicable to the candidate. His summary of the whole posture is four words long. "Don't take everything at face value."

The Case for Judgment

There is a coherence to Saab's career that the individual chapters obscure. Finance taught him structure. Building a business around artists taught him what talent looks like before anyone has certified it. Producers and directors taught him what the work actually demands. Enterprise recruitment gave him the scale to apply all three at once.

The result is a leader unusually well suited to a moment when polished documents are cheap to produce and judgment has become the scarce resource. In a field where the deciding factors sit largely outside the paperwork, Saab has spent a decade building the instinct to recognize them, and the discipline to confirm what he is being told.