Aashir

A Startup Inside a Professional Services Firm

The EY chapter began when the firm's chief innovation officer recruited him into an idea that sounded almost contradictory: build a startup inside a professional services organization and transform the way contingent workers are hired. What emerged was GigNow, an ATS and CRM built specifically for direct sourcing contingent talent, and it scaled until billions of dollars were running through it.

The thesis was blunt. Traditional staffing agencies sat in the middle of the process without adding much value, and the people they placed frequently did not understand the work that needed to get done. Meanwhile the obvious fixes were structurally impossible. A manager who met a great contractor had no clean way to bring that person back. A strong contractor rolling off an assignment elsewhere in the firm was invisible to the next hiring manager who needed exactly that skill set.

Shroff framed the fix as a three way marketplace. Candidates found better opportunities. The organization saved cost and improved quality. Managers got their lives back, because direct sourcing and redeployment collapsed time to hire. It is a structure he has essentially been refining ever since.

Consumer First, Not Enterprise First

One conviction has followed him through every role: talent software is consumer software that happens to be sold to enterprises. At EY the standard was uncompromising. Signing up for a role could not take more than 20 seconds. Measured against that bar, the rest of the market looks indefensible. By his estimate, 99 percent of applicant tracking systems still demand 10, 15, sometimes 30 minutes and 25 to 30 clicks, most of it collecting information that never needed to be transferred at all.

At Eightfold, where he took on the talent acquisition product area along with contingent and several other product lines, the target moved from 20 seconds to one click. Upload a resume, answer almost nothing, and you are in the system. The point was never the single application. The point was what happens afterward. Six or twelve months later, the resume that everyone assumes disappeared into a black hole becomes a credible, already interested candidate the moment the right requisition opens.

That is talent rediscovery, and Shroff is unsentimental about why it matters. Companies pour money into talent marketing to fill pools with people they already have. Microsoft's careers experience, which runs on Eightfold, shows the alternative: drop in a resume and instead of 30,000 jobs you might believe you fit, the system returns the five you are genuinely qualified for. The organizations complaining about tens of thousands of inbound resumes and the organizations struggling to find the right skill sets are usually the same organizations.

The People Who Handed Him the Mandate

Shroff credits a specific set of people with handing him unusually large problems and then trusting him with them. Jeff Wong, EY's chief innovation officer, supplied the original provocation and the cover to build something genuinely new inside a firm not built for startups. Carlton Smith, already a partner, running the advisory business and serving as its CHRO, brought the inner workings of the enterprise. Paired with Shroff, Smith made it possible to think about product transformation and candidate experience at the same time rather than trading one for the other.

At Eightfold, chief product officer Suchit pushed the consumer first mindset to its logical endpoint, insisting the candidate journey compress to a single click. Dipali, who now works on Shroff's team, led the personal career side of that work, the piece concerned with targeting the individual rather than broadcasting to the crowd.

At Oracle, the mandate came from Ogden, the leader Shroff reports to, and it arrived with unusual clarity. The traditional talent management product had run fine for 15 years. The opportunity, Ogden told him, was to take everything he knew about AI and re-spin how the company had always thought about these problems. That license, Shroff says, has been paramount in unlocking massive customer value.

What Happens After the Offer

His current work begins where recruiting usually ends. Once someone has been hired, how do you find them the right internal opportunities and keep them on the right career path? Performance data, goals and the other signals already sitting in the system become raw material for improving a person's trajectory rather than paperwork filed once a year.

The other half is managers. Shroff wants the data in the system to make managers better at understanding their own people, both what they need in the short term and what they need over years. He applies the same test to himself. Running a team of 20, he wants a live heartbeat of what is happening rather than periodically chasing everyone down, information that flows into one place he can read or simply ask questions of. The insistence on AI that solves a real operating problem, and not AI for the sake of AI, is the through line of his product philosophy.

A Tool, and Who Controls the Narrative

Shroff treats AI the way he treats every technology wave before it, from web to mobile. It has pros and cons, and what matters is how well you leverage it. On the upside, it finally lets candidates stand out in a noisy, crowded space. Stitch together the resume, the interviews and everything else in the trail and you get a genuinely rich profile of a person, one that can answer whether they fit the job they applied for and whether they fit a different job six to twelve months from now. Before AI, he notes, that second question was simply unanswerable.

He is equally candid about the risk of bias, and he locates the answer in design rather than in abstention. Employer systems and candidate portals should be built so the candidate can own and control their own narrative. "If you control the narrative and you dive into it," he says, "you'll feel a lot more comfortable that the right things are being said in the right rooms about you."

He also declines to romanticize the human status quo. Ask anyone who has been interviewing for years how well trained they actually are, and the honest answer is probably not very. Even organizations that consider themselves world class at recruiting, playbooks and all, produce wildly inconsistent results. Shroff has watched it directly, sitting through 10 different interviews with 10 different hiring managers and finding every one of them different. Interviews should not be robotic, he is quick to add. But the goal is to surface the right signals about who genuinely fits, and on that score he is clear eyed: everyone carries some bias, and AI, done correctly, can help navigate it.