Last summer we posted a new, open role for a director of finance – little did we know that it would kick off a season of hiring, where, nine months later, we’ll have seven new team members, effectively doubling our team over the course of a year.
In the past nine months we’ve learned a lot about hiring, marveled at how artificial intelligence (AI) has changed the landscape, worked to continuously refine aspects of the hiring process to align to our values and figure out how we maintain the human aspect of a process that is being reshaped in real time by AI.
The volume problem
The numbers tell a story that anyone hiring right now will recognize. In July 2025, we posted a finance role and received 146 applications — a manageable, human-scaled number of resumes to review. Then in September, we posted job openings on LinkedIn for three additional roles – program, administrative and research and collectively, over the span of one week, received over 3,000 applications, with 2,000 alone for the program role.
The number of applicants was a hard reality check that the AI-assisted tools to help candidates scan job boards, tailor cover letters, and submit applications in volume are here and are dramatically changing the hiring landscape. What used to take an afternoon for job seekers now takes minutes. For us, the unexpected and exponential number of applicants forced us to pivot our approach in reviewing applications, and (dare I say it), leveraging AI in the review process without losing the human aspect of hiring. Finding the people who are the right fit with Accelerate suddenly got harder.
The question that AI can’t ask
At a scale of over 2,000 applications for a single role, we faced a practical question: how do you find the resumes worth reading carefully without spending hundreds of hours on applications that aren’t really applications? After screening out a notable number of non-US based applicants, we quickly found that one of the most telling parts of the application was not the cover letter or resume, but rather, the two open questions: Why are you interested in this role? and How do you see yourself contributing to Accelerate’s mission?
We made a deliberate choice to focus on these responses as an indicator of applicant effort and genuine interest in Accelerate. As an invitation to tell us something beyond the resume, you’d be surprised at the number of responses to the questions that were a sentence or two, nothing at all, or were clearly written by AI (including the ones where the applicant would forget to edit their cut and paste response, leaving tell-tale indicators like [insert something personal here]). While the choice to have a machine screen applicants on a somewhat arbitrary aspect of the application may be open to debate, at that time we felt it was the right way to use AI to filter the applications for effort: Did the person engage with the questions asked? Did they know anything about Accelerate? Upward of 50% of applicants were removed from the pool based on these screens.
After the initial screening, our team pulled together to review resumes. The applicants we advanced were not always the most polished on paper. Some came with unusual backgrounds — career changers, people at various stages of their career and whose experiences cut across sectors beyond education and non-profits. Many had accomplishments in contexts that looked different from what we’d expected or seen before. Our human team of reviewers let us ask the question: is there something interesting here?
Putting our values to work
Having just defined Accelerate’s core values, we also intentionally integrated our values into our hiring process for the first time. We built questions for interviews and reframed the applicant’s written task to help us understand how people actually think – how they navigate ambiguity, how they approach problems they’ve never seen before, how they work with people who see things differently – and looked for alignment with our values.
For the applicant’s written task, we also moved to blind scoring. Evaluators scored assignments without knowing whose it was. That change alone shifted some of our conversations — when you can’t default to the halo or shadow of a candidate’s background and resume, you focus on what’s actually in front of you and let their work speak for itself.
And we stayed open to the candidate who didn’t fit the mental model for the open roles. Some of the applicants we moved into the final stages of interviews were the most interesting conversations about potential contributions to Accelerate and team fit.
What we’re still figuring out
The volume pressure from AI tools isn’t going away, and neither is the underlying challenge of figuring out who someone really is from a resume. We’re thinking about how to be clearer in our job postings about what we’re actually looking for – experience matters, but also alignment with our values and team culture. We’re watching the AI piece closely – the same tools reshaping how people apply are available to us as an organization. We think there’s a version of using those tools to make the process better and fairer, and a version that doesn’t. Figuring out which is which is ongoing work.
Truth be told, we don’t have this fully solved, and I imagine we’ll be intentionally refining and changing our hiring process with each new job opening. What we’re confident about is our commitment to keeping the process human-centered, and our intentional integration of our values to find people to join a team that is unwavering in improving student outcomes. We are genuinely excited for the team members that have joined and the ones who we’ll be welcoming into Accelerate in the coming months. We cannot wait to see and share how they are making us, and our collective work better.
Tu-Quyen Nguyen is Managing Director of Operations at Accelerate.
