Morgan Wilson Says You’re Not Hiring a Document. The Recruiting Industry Needs to Catch Up.
By: Natalie Johnson
Somewhere between the mass application and the automated rejection, hiring forgot what it was supposed to do.
The volume numbers tell part of the story. A single job posting at a mid-sized company can generate several hundred applications within days. Recruiting teams, already stretched thin, turn to applicant-tracking systems, keyword filters, and algorithmic scoring to manage the workload. Candidates, knowing the game, optimize their resumes for those same systems, adding terms chosen for machines rather than humans. The result is a process that produces staggering quantities of processed documents while making it measurably harder to identify the people who will actually thrive in a role.
Morgan Wilson has spent over a decade watching this dynamic from the inside. As a recruiter and talent strategist across major law firms and Fortune 150 companies, she was positioned close enough to the machinery to see both how decisions were made and what those decisions consistently missed.
What she observed was not dysfunction, exactly. It was an optimization pointed in the wrong direction.
“You have job postings generating hundreds or thousands of applicants but no real infrastructure for evaluating them,” Wilson says. “So they lean on AI, on keyword matching, on pedigree, on brand-name employers, because that feels safer and faster than actually getting to know someone. And the candidate who might have been the best fit never gets past the first filter.”
The Narrowing That Never Should Have Happened
In legal recruiting, the narrowing took a particular shape. Firms competed fiercely for graduates from the top 10% of law schools, treating academic pedigree as a reliable proxy for professional potential. Non-linear candidates, those who had served in the military, worked as educators, or taken paths that did not follow the standard sequence, were routinely filtered before anyone had looked closely at them. In Wilson’s experience, those were often the candidates who had the most to offer.
“Some of our best lawyers were people who had done something completely different before law school,” she says. “They had life experience, perspective, a different way of thinking under pressure. None of that showed up in how the system evaluated them.”
It is not only legal hiring. Across industries, the pattern holds. The process was built to eliminate, not to discover. Volume required speed, and speed required shortcuts, and the shortcuts gradually became the entire system.
When the Tools Deepened the Problem
The rise of technology in hiring was supposed to help. In certain ways, it has. Smaller companies can now build recruiting infrastructure that would have required significant investment a decade ago. Candidates have broader access to preparation resources and market intelligence than at any previous point.
But the same tools that promised efficiency have compounded the volume problem in ways few anticipated. Easy-apply features lowered the barrier to submission so dramatically that a single graduating student might send out hundreds of applications in a given cycle, many of them tailored by AI to the specific language of each job description. On the receiving end of that volume, hiring teams face an impossible evaluation task, and so they reach for more technology, more automation, more filtering, to reduce the pile to something manageable.
What gets lost is the very thing that determines whether someone actually succeeds once they arrive.
“We’re automating the worst parts of hiring and calling it efficient,” Wilson says. “If a candidate doesn’t feel valued in the process, they’re going to look somewhere else. And if you’re moving so fast that you’re just matching keywords to keywords, you’re not hiring a person. You’re filling a template.”
The cost shows up on both sides. For candidates, it is the exhaustion of invisibility despite doing everything correctly: tailoring applications to systems that will never read them and optimizing resumes for algorithms not designed to recognize potential. For companies, it is the recurring expense of bringing in people who appeared right on paper and discovering the fit was never actually there, a cost that routinely runs to roughly 30% of that person’s annual salary, repeating every time the cycle begins.
What Intentional Hiring Requires
Wilson’s work at The Wilson Co. is built around a different premise. Both sides of any hire, the candidate and the organization, are making a mutual bet on each other. The process should be designed to reflect that.
In practice, this means backing into a role based on what success genuinely looks like, not on a job description that may have been copied from an old file and updated only minimally over time. It means asking what kind of person has historically thrived in a specific environment and what that pattern reveals about the culture as it is actually experienced, not the culture as described on the company website. It means treating the interview as a genuine conversation rather than an interrogation, and being as transparent about what the day-to-day work actually involves as you are about what you are looking for.
“The right fit happens outside the documents,” Wilson says. “A résumé tells you what someone has done before. It does not tell you how they think under pressure, what they need to feel genuinely engaged, or whether the leadership approach here is going to bring out their best. That is where the real evaluation has to happen.”
The Matching Problem, Rethought
This conviction is also the foundation of a new product Wilson is developing through The Wilson Co.: a matching platform designed to move hiring away from résumé-to-job-description keyword comparison and toward a more complete picture of both parties. The platform reflects a core belief that finding the right fit requires understanding what makes someone perform well and whether the organization can realistically provide what that person needs, not simply whether the words in one document align with those in another.
Wilson is precise about what the product is not. It is not a technology replacement for human judgment. The purpose is to create the conditions under which better human judgment can actually occur.
“You’re not hiring a document, and you’re not filling a template,” she says. “You’re asking two humans to make a mutual bet on each other. The process should honor that.”
The Relationship Hiring Left Behind
Before applicant tracking systems and mass job boards, recruiting operated differently. Decisions moved through relationships, through local networks and direct interaction, through someone deciding to invest in a person because of how they showed up in a real conversation, not how their credentials looked when filtered through an algorithm. That model carried its own inequities and limitations. But it understood something the current system has largely discarded: hiring is relational, and relationships cannot be compressed indefinitely without something important being lost.
When organizations optimize purely for speed and volume, the quality of evaluation that would have revealed whether the hire was right in the first place disappears.
Wilson’s argument is that the companies and candidates willing to treat the process as a genuine mutual discovery will consistently outperform those who do not. Not because slower is always better, but because the things that actually predict success in a role have never lived inside a document, and no degree of algorithmic refinement will make them appear there. The relationship that hiring has largely discarded is still the most reliable signal anyone has ever found.
