Filtered Out Before You’re Seen

Venture in the Age of AI

By Alastair Goldfisher
Veteran journalist and creator of The Venture Lens newsletter and The Venture Variety Show podcast. Alastair covers the intersection of AI, startups, and storytelling with over 30 years of experience reporting on venture capital and emerging technologies.

The executive never expected she’d be ghosted.

She had the track record, the credentials and a resume tailored to the position. But after clicking submit on an online job application, she soon received a rejection email. That’s rare. Most applicants these days never hear back at all.

This exec didn’t make it past the initial phase, maybe because there were career gaps on her resume or perhaps she didn’t include the right buzzwords in her accompanying letter. For whatever reason, an algorithm likely filtered her out before a human even got sight of her application.

That and similar stories are what Patrice Williams Lindo is trying to lessen. Lindo is an Atlanta-based career strategist who helps mid- and senior-level professionals to navigate a system that often doesn’t see them.

“AI doesn’t understand a non-linear story,” she says. “It looks for keywords and patterns. So if your path doesn’t follow a straight line, you might get filtered out, even if you’re more than qualified.”

Through her consulting business, Career Nomad, her clients include qualified CEOs and execs who are tired of being rejected. Lindo views herself as a workforce futurist and a visibility strategist, helping people leverage their skills and abilities in the current AI-driven world. What she advises clients is to rebrand, network and find ways to raise their visibility through speaking gigs, thought leadership and direct outreach.

“I tell my clients to take stock of their strengths, to review the achievements and experiences that define their career and then use AI to match those to the roles they’re pursuing,” she says. “Don’t let the tool define you. You need to define what the tool sees.”

Of course, there’s still no guarantee. Lindo and I talked about a now-infamous cautionary tale. In 2018, Amazon scrapped an internal recruiting tool after it showed bias against women. The system, trained on 10 years of resumes from mostly male applicants, penalized candidates who mentioned women’s activities or all-women colleges in the applications.

“AI didn’t invent that bias,” Lindo says. “It just made it faster.”

Across sectors, from hourly employees to executive roles, AI tools are reshaping how people apply for jobs and how companies evaluate the applicants. From automated resume screeners to chat-based interview prep tools, new technologies and platforms offer promises of efficiency. But they’re also introducing new forms of bias and a lack of transparency.

In my interviews with technologists, career coaches, founders and others, a common thread emerged: AI is a powerful tool and a tricky gatekeeper. Used well, it can enhance how companies match talent to roles, and AI can help job seekers save time on their applications. But left unchecked, AI often dismisses promising candidates before anyone gets a chance to hear their story.

AI can help, but it won’t get you hired

Julie Schaller, a Seattle-based leadership and career coach who works with tech professionals, says most large companies today use AI in their applicant tracking systems (ATS). And while AI can help a candidate draft a resume or prep for an interview, it won’t land the job for them.

“It can help you get started, but you still need to edit, focus and add your voice,” she says.

In fact, a January report from Resume.io suggests that up to 70% of resumes are rejected before a human ever sees them, often due to formatting issues or lack of keyword alignment. In addition, despite the rise in AI resume tools—which are used by more than 30% of applicants, according to Resume.io—many still get filtered out for being too generic.

Schaller also noted that AI tends to reward specialists—those with clear, niche expertise—more than generalists. That might surprise people who believe being a flexible, cross-functional generalist is the superpower of the AI era. But when it comes to resume parsing and keyword targeting, a sharp and specific career focus will stand out when compared to a broad profile.

“You want to be the obvious fit for the role,” she says. “AI doesn’t interpret nuance well, so clarity counts.”

Instead of using AI tools to broaden your appeal, she advises job seekers to narrow in: edit and refine your message so it speaks directly to what the employer is seeking.

She also noted that while resumes go through AI machines and may be culled logically, hiring decisions are still frequently made emotionally first and then ultimately justified with logic. As a reminder that AI doesn’t replace chemistry or connection, she says a good story, and a strong, authentic signal, still matters.

Also, Schaller and others emphasize the importance of using personal connections in the AI era to go the extra mile, leverage the network and use LinkedIn to get past the initial screening.

“Don’t just rely on the online application process,” Schaller told me. “Your network matters more now than ever.”

Frontline workers enter the AI conversation

While much of the conversation around AI and hiring focuses on white-collar or executive roles, the majority of American workers don’t fall into those categories.

About 80 million Americans, a little more than half of the U.S. labor force, work hourly jobs in such sectors as logistics, manufacturing and hospitality.

Jarah Euston, CEO and co-founder of WorkWhile, believes AI can actually be a benefit for hourly workers if used right. She herself started working as a teen in retail and fast food jobs and now leads a labor platform focused on frontline roles.

“AI-powered screening could create for frontline workers a much richer tapestry of each individual’s skills and experience,” she says.

Instead of relying on resumes alone, WorkWhile uses chat-based AI tools to probe for details of a person’s work experience. For example, what kind of forklifts someone has used or whether their volunteering experience includes industrial kitchen work. Euston says that kind of nuance is too often missed in traditional high-volume screening.

Her platform doesn’t just surface the right workers. It also stores their data, helping to match them with future roles as new shifts open up.

Euston says there are benefits of using AI for training and upskilling. And she echoed a theme raised by others, which is to not fear the tech, but to learn it.

“Frontline workers who are fluent in AI tools may end up ahead of some white-collar workers who are more resistant to change,” she says.

And while LinkedIn may not be as relevant for workers in a warehouse or restaurant, referrals are just as vital for frontline workers.

“Good people know other good people,” she says. “Whether you’re a CEO or an entry-level employee, that personal connection still opens doors.”

The jobs you don’t see

While Euston and WorkWhile are focused on overlooked frontline talent, Andy Mowat is thinking about roles that never even get posted.

Mowat, founder of Whispered, runs an executive hiring platform focused on VP and C-suite roles that are almost never posted publicly.

“Seventy to eighty percent of these jobs are never listed,” he says. “Because when companies do post, they get flooded. And with AI-generated resumes, everyone looks polished. It’s harder to tell who’s actually a fit.”

Whispered uses AI behind the scenes to suggest matches, but its real strength is in humans communicating on the platform what roles are available. Mowat’s takeaway is that tech should support connection and not eliminate it.

In the following clip from a recent podcast I recorded with Mowat, he explains how AI has changed the hiring game and why companies are quietly pulling back on publicly posting open roles.

🎧 Watch on YouTube the full conversation with Andy Mowat on the podcast The AI Cognitive Shift, which I host in collaboration with AiNews.com.

Behind the curtain of hiring tech

Brandon Amoroso, co-founder of SCALIS, adds another layer to this picture, one that looks at how the application system itself is broken.

He points out that platforms like LinkedIn and Indeed lose contact with a candidate the moment they hit “apply” and move into a company’s ATS.

“That breaks the feedback loop,” he says. “The system can’t learn who actually got hired, so the AI behind the recommendations doesn’t improve.”

SCALIS was built to close that loop, he says, as it acts as a sourcing engine and an ATS. Brandon emphasized this provides a critical use-case for scaling high-volume hiring, such as in cold-calling agencies or SaaS organizations with large sales teams.

SCALIS stands out by staying with the candidate through the process, tracking outcomes, learning what works and improving with each cycle.

Like others, Amoroso says he’s cautious about the AI hype.

“AI is not a silver bullet,” he says. “If you feed it biased or poor data, you get poor results.”

He also warns that the danger of AI is that one in four job applicants may be fake by 2028, citing a CNBC story. He adds that poorly implemented AI hiring can create legal and ethical minefields.

Still, he’s hopeful. “There’s fear around AI, but people need to see it as a tool. If you’re thoughtful about how you use it, it can make the process better for both sides.”

Closing the loop

One of the biggest complaints from job seekers—beyond just rejections—is silence. Many candidates never even realize their resumes were rejected by an algorithm, and the lack of transparency leaves them frustrated and powerless.

Growing concerns about bias and transparency have prompted new regulations, like New York City’s AI in hiring law, which requires employers to conduct audits of it automated hiring tools and notify candidates when AI is used. And the EU’s sweeping AI Act, which imposes rules on high-risk AI systems in recruitment and employment decisions.

Meanwhile, job seekers are left refreshing their inbox, waiting for a positive reply to their online application.

“Most applicants, when you apply for a job, you essentially get ghosted,” says Arsham Ghahramani, co-founder and CEO of Ribbon.AI, in a recent podcast on YouTube with AiNews.com. “You don’t even get a rejection. That’s a horrible experience.”

Like SCALIS, Ribbon stays engaged throughout the hiring flow, helping recruiters make faster, better-informed decisions. Ribbon uses voice-based AI to conduct interviews and provides instant feedback to applicants, something Ghahramani says is more humane and more efficient. The company claims it can reduce hiring timelines by 40% and improve employee retention by 30%.

As AI takes on more responsibility in hiring, the challenge isn’t just learning to use the tools, it’s knowing where they fall short. Applicants are adapting, and so are recruiters.

“The truth is, the market is lumpy right now,” says Euston of WorkWhile. “There’s economic uncertainty, but AI adoption is accelerating. The challenge—and opportunity—is making sure it works for everyone, not just the top of the ladder.”

And while the landscape is shifting, one thing remains clear: Applicants still need to tell their story. They still need people in their corner. For all the automation, the hiring process is still—and maybe always will be—deeply human.

🎙️ Stay informed by subscribing to The Venture Lens for the latest insights and updates from Alastair.