Navigating "The Great Pause": Trust, Tech, and the 2026 Job Market

Job Seeker Nation

RecTech Podcast

The latest JobSeeker Nation report—built on a nationwide survey of over 1,500 U.S. adults—reveals a major shift in candidate behavior. Job seekers are hitting pause and stepping back from the job market altogether.

To break down why this is happening and what it means for HR leaders, the RecTech podcast sat down with Stephanie Manzelli, Chief People Officer at Employ (the parent company behind JazzHR, Lever, and Jobvite).

Here are the key takeaways from their conversation on trust, the impact of AI, and how companies can better connect with today's talent.

The Trust Gap: Why Candidates are Stepping Back

According to Manzelli, the biggest challenge facing people leaders today isn't just attracting talent—it's establishing and maintaining trust. A glaring disconnect between what is promised during the interview process and what is actually delivered is fueling early turnover.

• The 90-Day Reality Check: The report highlights that 46% of people who left a job within their first 90 days did so because the actual role did not align with what was communicated during the hiring process.

• The Rise of Hiring Scams: Trust is further eroded by a spike in fraudulent listings. 53% of job seekers report encountering job postings they believed were scams, flagging roles that look "too good to be true" or demand sensitive personal identity information too early.

• The Ghosting Epidemic: Recruiter and hiring manager ghosting is on the rise, with 32% of candidates experiencing it this year.

How Employ Tackles Ghosting: Manzelli notes that Employ prevents ghosting by refusing to leave job listings open indefinitely just to gather thousands of applications. Instead, they intentionally close posts down early to ensure the talent acquisition team can maintain meaningful follow-through with every applicant.

The Gen Z & Millennial AI Paradox

The report reveals a fascinating generational divide regarding the use of Artificial Intelligence in recruitment. While younger generations are highly comfortable using AI, they are also the most skeptical of its ethics.

• AI Concern by Generation: When asked about companies relying too heavily on AI, 60% of Baby Boomers expressed concern, compared to 49% of Gen Z. Interestingly, concern dropped even lower among Millennials (40%) and younger Gen Z brackets (39%).

• The Rejection Dichotomy: Despite being more tech-native, younger candidates are far more likely to believe they have been unfairly and automatically rejected by an AI algorithm. They expect companies to use advanced tech, but they are highly sensitive to its potential bias if left unchecked.

Human-in-the-Loop: Striking the Right Balance

With 40% of candidates stating they would feel more comfortable if a human reviewed AI-driven recommendations, Manzieli emphasizes that AI should remain a supportive tool, not a replacement for human judgment.

• What AI is good for: Generating consistent, unbiased interview questions based on job descriptions, streamlining application workflows, and scheduling.

• What requires a human: Understanding an organization’s unique context, evaluating candidate personas, and making the final hiring decision. Manzieli firmly stands against auto-rejections, advocating instead for using AI purely to surface matches for human evaluation.

Actionable Advice for Employers

To turn passive candidate interest into new hires during "The Great Pause," employers must transition from theoretical storytelling to tangible proof.

1. Make Growth Tangible: Don't speak in abstract terms about career progression. Outline transparent progression paths, clear timelines, and upward opportunities up front.

2. Close the Reality Gap: Give candidates a real look at how your teams operate day-to-day. Show them actual meeting structures, communication expectations, and leadership styles during the interview process.

3. Treat Flexibility as a Core Offer: Treat flexibility as a standard part of the job structure, not a perk. Clearly define whether a role is remote, hybrid, or open-scheduled so candidates can accurately assess alignment.

4. Don't Wait for Exit Interviews: Take a human-centered design approach to your workforce. Frequently pressure-test your employee experience using onboarding insights and new-hire check-ins to spot and fix misalignments instantly.

The full 2026 Job Seeker Nation Report is available on Employ Inc's website and their respective product channels.

AI, Trust, and the Future of High-Volume Hiring: A Conversation with Humanly CEO Prem Kumar

Prem Kumar, CEO of Humanly

RecTech Podcast

High-volume recruiting is undergoing a massive transformation. With the rise of generative AI, the lines between software and service are blurring, changing both how companies hire and how job seekers find work.

On a recent episode of the RecTech Podcast, host Chris Russell sat down with Prem Kumar, the CEO and founder of Humanly. Humanly, a high-volume recruiting platform, just announced a major milestone: a $25 million Series B funding round.

Prem shared his insights on what this funding means for the company, how AI is altering the economics of HR tech, and how organizations can leverage automation without losing the human touch.

1. The Next Chapter for Humanly

Fresh off the $25 million funding announcement, Prem noted that the team’s immediate priority is execution—specifically, building a better product and scaling their internal team. Currently sitting at around 50 employees, the six-year-old company is looking to expand its workforce across several key roles.

2. From "SaaS" to "Service as a Software"

One of the most provocative concepts discussed was the shift from standard Software as a Service (SaaS) to "Service as a Software."

Prem highlighted a massive discrepancy in market spend: while the recruiting technology market is worth roughly $14 billion, the staffing, RPO, and services market is a staggering $500 billion. This services market is heavily concentrated in hourly, deskless, and entry-level high-volume roles.

Traditionally, software platforms give you the tools (like a kit to build an IKEA chair), but services companies deliver the actual outcome (the finished chair). Humanly is bridging this gap by shifting toward Pipeline as a Service. Instead of just selling an ATS or a CRM, they are providing a built-in flow of QIAs (Qualified, Interested, and Available) job seekers. This allows technology vendors to deliver agency-level outcomes with high SaaS-like efficiency.

3. The AI Reality: Engagement vs. Being Ignored

A common critique of AI in recruiting is that it removes the human experience. However, Prem flipped this perspective for high-volume hiring:

"From a job seeker standpoint, we’re not talking about human versus AI. We’re talking about AI versus being ignored and never hearing back."

Statistically, about 95% of applicants attracted via recruitment marketing are completely ignored because time-strapped hiring teams can only realistically review about 5%. Traditional applicant tracking systems rely on glorified keyword matching to filter that 5%.

Humanly leverages conversational AI to ensure 100% of applicants get a two-way screening interview. This helps companies learn more about every candidate beyond a piece of paper, while simultaneously building a robust "silver medalist" pipeline for future roles.

4. Bridging the "Trust Gap"

We are currently witnessing a unique phenomenon in enterprise technology: a massive gap between the appetite to buy AI and the trust required to deploy it safely. Prem referenced a study by Tideo showing that while 90% of Talent Acquisition leaders want to use AI, only 27% actually trust it.

To build this trust, Prem emphasizes that AI vendors must focus on:

• Transparency & Third-Party Audits: Ensuring models are externally audited for fairness.

• Giving Value Back: Job seekers trust AI when it provides immediate value, like resume coaching, constructive feedback, or a faster path to a job.

• Deep Collaborative Customization: AI allows vendors and buyers to sit on the same side of the table to custom-tailor workflows, tonal qualities, and brand experiences much faster than old code-heavy software allowed.

5. Combating Bias with Better Data

AI models face valid criticism for potentially automating or exacerbating bias. Humanly tackles this by training its models using data sets from hundreds of thousands of human-to-human interactions to identify systemic flaws.

For example, their research on 300,000 Zoom interviews revealed that junior women were given an average of 10 minutes less to speak. They also found that interviewers speaking over 150 words per minute severely disadvantaged candidates for whom English is a second language. By standardizing and guard-railing conversations, a properly trained AI interviewer can actually level the playing field and minimize human bias.

6. The Future: "Jobs Find You"

When asked about the current "AI arms race"—where candidates use auto-apply bots to flood inboxes and employers use AI filters to block them—Prem sees an ultimate paradigm shift on the horizon.

Right now, AI is being used to make existing, inefficient application processes faster. In the near future, Prem predicts we will move away from active applying altogether. Instead, a job seeker might interview or update their profile just once a year, and intelligent agents will pass that verified data to company agents. We will move toward an ecosystem where jobs find you, eliminating the "resume black hole" entirely.

Key Takeaways for Founders and TA Leaders:

• Data is the Moat: In the age of AI, transactional tracking tools are easy to build. The true value lies in recruiting-specific data sets that understand contextual nuances (like state pay transparency laws) to drive actual conversions.

• Empathy Matters: Use AI to absorb administrative, script-reading tasks so human recruiters can use the full capacity of their empathy where it matters most.

To learn more about Humanly and their open roles, visit humanly.io. For more insights at the intersection of recruiting and technology, subscribe to the RecTech Podcast.

Greenhouse Report: More Applications, Fewer Recruiters

The 2026 Hiring Landscape: A Deep Dive into Greenhouse's Latest Benchmark Report

Sharawn Tiption from Greenhouse

RecTech Podcast

The world of recruiting has hit a major "reset" button. Greenhouse, a leader in hiring technology, recently released its 2026 Benchmark Report, and the findings reveal a landscape fundamentally transformed by AI and shifting economic pressures.

To break down these insights, Sharawn Tipton, Chief People Officer at Greenhouse, joined the Rectech Podcast to discuss the report's key findings and what they mean for both employers and job seekers.

The Paradox: More Applications, Fewer Recruiters

The most striking trend in the report is the massive surge in application volume. Recruiters are now managing 411% more annual applications than they were in 2022. This explosion is largely driven by AI-powered tools that allow candidates to apply to hundreds of jobs with minimal effort.

At the same time, recruiting teams have been cut by more than half, seeing a 55% decrease in size since 2022. This creates a challenging "doom loop" where candidates feel ghosted by overwhelmed systems, and recruiters struggle to surface quality talent from a sea of automated applications.

Key Statistics from the Frontlines

• Increased Productivity: Despite smaller teams, recruiting efficiency has actually risen. Monthly hires per recruiter jumped 122% between 2022 and 2025.

• Application Surge: Applications per job have increased by 111%, rising from roughly 115 in 2022 to 244 in 2025.

• AI Integration: The use of AI in the interview process is climbing rapidly, up 13 percentage points in just the last six months.

Moving Beyond the "Doom Loop": Strategies for Success

Sharon Tipton emphasizes that while AI is driving the volume, it must be balanced with a human-centric approach. Here are Greenhouse’s recommendations for navigating this new era:

1. Embrace Specialized AI

The goal isn’t just more AI, but better AI. Tipton suggests using tools that integrate AI to provide a natural "uplift" in efficiency while ensuring the technology is built to mitigate bias and support a fair, structured hiring process.

2. Prioritize AI Fluency

For job seekers, "AI fluency" is becoming a critical skill. Tipton notes that Greenhouse now tests for this during interviews—not just asking if a candidate uses AI, but how they use it to validate information and solve problems.

3. Human-Centric Interviews

Technology should enable human encounters, not replace them. Tipton stresses the importance of keeping the person at the center of the process, ensuring candidates feel respected and informed even when automated systems are involved.

4. Transparency as a Differentiator

In a crowded market, transparency builds trust. Companies that are open about how they use AI and provide clear timelines for the "next steps" in their hiring workflow will stand out as employers of choice.

The Takeaway

The 2026 hiring landscape is high-volume and high-tech, but the fundamentals of relationship-building remain the same. As Tipton puts it, "Business is personal". The companies that successfully navigate this reset will be those that use AI to enhance, rather than diminish, the human experience of finding the right job.

For more details, you can access the full 2026 Greenhouse Benchmark Report through the link here.

How to Optimize Your Career Site for the AI Ecosystem

In a landscape where candidates increasingly turn to Large Language Models (LLMs) like ChatGPT, Claude, and Gemini to find their next role, the traditional rules of SEO are shifting. According to employer brand expert James Ellis, being found by talent today requires a new strategy: ensuring AI can find you, understand you, and trust what it finds.

Here are the key takeaways from Ellis on how to turn your career site into a high-performing AI search asset.

1. Give Your Company a Real Entity Homepage

Most Fortune 500 career sites fall into the trap of "cookie-cutter" messaging, using generic phrases about growth and purpose that make every company sound the same.

• Take Ownership: Unlike third-party platforms, you own your career site and its domain authority.

• Stand Out: Avoid "recruiting-speak" and "legal-speak". Use your site to clarify exactly what your company offers in a way that LLMs can distinguish from your competitors.

2. Make Your Claims Auditable

AI systems value evidence over empty marketing claims. If you claim to have a culture that "cares," you must provide proof.

• Use Specific Examples: Ellis suggests moving beyond bullet points to include short, two-sentence stories or testimonials from employees.

• Provide Data: Tangible proof—such as a specific policy or the amount spent on an employee benefit—serves as undeniable evidence for an AI to rank your company as a credible answer to a user's prompt.

3. Build Durable Pages, Not Disposable Posts

A common mistake is placing all high-quality content inside job postings that expire and disappear after 30 days.

• Perpetual Evidence: LLMs look for evidence that is perpetual and evolving.

• Reinforce Your Story: While job postings are important for initial impressions, that content should also live permanently on your career site to reinforce your brand pattern across the web.

4. Leverage Structured FAQs and Q&As

FAQs are "low-hanging fruit" that provide the context LLMs crave.

• Feed the AI Context: LLMs struggle with ambiguity (e.g., distinguishing "CAT" the animal from "CAT" the tractor company).

• Be Specific: Instead of a generic "What is it like to work here?", use detailed questions like "What is the day-to-day for a claims adjuster in our Chicago office?". This allows the AI to play a better "matching game" with user queries.

5. Prioritize Living, Fresh Content

Your career site should not be a static archive; it needs to show "signs of life".

• Incremental Changes: You don't need a radical redesign every year. Instead, make small, weekly updates: swap a headline, add a new video, or refactor a company news story into a candidate-facing update.

• Fractal Branding: Ensure your core value proposition is present in every sentence. If innovation is your brand, it should be indicated throughout the site, not just in a single headline.

Measuring Success in the AI Age

As search shifts away from simple link lists, traditional ranking becomes less relevant. Employers should focus on citation visibility and traffic coming directly from LLMs in their analytics. By narrowing your focus to be intensely appealing to your specific target audience, you ensure that when an engineer asks an AI for the best place to work in Chicago, your company is the one that gets the recommendation.

How are you currently adapting your recruitment content to ensure it is "understandable" to AI?

The Rise of Workplace Misconduct: Why Your Screening Strategy Needs a Digital Upgrade

A Conversation with Ben Mones, CEO of Fama Technologies

DOWNLOAD THE REPORT

Ben Mones CEO of FAMA Technologies

RecTech Podcast

The workplace has changed dramatically. Your screening process should too.

In a recent conversation on the RecTech Podcast, Ben Mones, CEO of Fama Technologies, shared eye-opening insights about the state of workplace misconduct and why employers are falling behind in their talent vetting practices. With 11 years in the screening space, Ben has a front-row seat to how digital transformation is reshaping hiring—and what companies need to do to protect themselves.

The Numbers Don't Lie: Misconduct Is On the Rise

Fama's latest "State of Misconduct at Work" report reveals a startling trend: there's been a 34% year-over-year increase in online misconduct signals. We're not just talking about isolated incidents. Across industries, roughly one in 15 candidates screened shows some form of misconduct signal—whether it's trolling, violence, threats, or references to illegal drug use.

"Misconduct is on the rise writ large," Ben explains, pointing to the fundamental shift in how work happens today. With remote and hybrid work becoming the norm, employees are getting to know each other through Discord, Reddit, LinkedIn, and other digital channels rather than around the office water cooler. That digital footprint tells a story—and employers need to be reading it.

The Unexpected Culprit: LinkedIn

Here's something that might surprise you: LinkedIn has become ground zero for online misconduct, experiencing the biggest explosion of problematic behavior.

"I'm starting to see it as much more of a sewer," Ben says candidly. When Twitter faced upheaval under new ownership, many users migrated to alternative platforms like Bluesky and Mastodon. But eventually, they found their way to LinkedIn—bringing their unfiltered behavior with them. The result? A platform once known for polished professional networking is now seeing harassment, inappropriate advances, and other problematic content at scale.

Your Workforce Has Changed—Has Your Screening?

With six generations now in the workforce, the demographic makeup of talent has shifted dramatically. Half the workplace is now made up of Gen Z and millennials—digital natives who have spent their entire lives online. For these candidates, their social media history is often richer and more revealing than any traditional background check.

Ben uses a vivid metaphor: "Are you screening like it's 1999 on Windows XP, or are you screening on a MacBook Pro with Claude and Gemini?"

The point is clear: if your screening strategy hasn't evolved to match your workforce, you're operating with incomplete information.

The Real-World Impact

Chris Russell, the podcast host, shared a powerful anecdote that illustrates why this matters. Before hiring someone for a financial role with access to sensitive data and credit cards, he did a simple Google search on the candidate's name. He found an article mentioning that the person had been caught stealing from someone's purse at a school. When confronted, the candidate admitted it.

That's the kind of critical information that can be hiding in plain sight—if you know where to look.

Technology Is Smarter Than You Think

One of the biggest misconceptions about social media screening is that it's just keyword matching. That's outdated thinking. Modern AI has evolved dramatically.

Today's systems can distinguish between "My boss and I are going to kill it on this project" and "I'm going to kill my boss after I wrap up this project.". The difference matters—and sophisticated AI now understands context in ways that simple keyword searches never could.

How Employers Are Actually Using This

About 80% of Fama's clients use social media screening during the final candidate shortlist—typically when they're down to three or four people and ready to extend a conditional offer. This positions screening as a complement to traditional background checks rather than a replacement.

Interestingly, about 20% of their clients are also doing ongoing employee re-screening, monitoring for regulated behaviors like workplace harassment, violence, or threats.

Privacy First: Consent and Compliance Matter

A common concern: isn't this invasive? The answer is nuanced.

All legitimate screening should be fully compliant with FCRA and GDPR regulations, with explicit candidate consent. Importantly, candidates get to see the results and explain themselves—just like any other background check. This isn't a black-box process; it's a conversation.

And here's the surprising part: when employers are transparent about their screening practices, most candidates appreciate it. People want to work somewhere that screens for intolerance, harassment, and illegal drug use. It signals that the company takes its values seriously.

Beyond Binary: The Future of Screening

Traditional background checks are binary. You either have a conviction or you don't. But social media screening is different—and that requires a different approach.

A candidate posting one tasteless joke is different from someone with a pattern of offensive behavior over years. Employers need room for nuance and judgment. This is where the future of screening is headed: away from rigid, automated decisions and toward explainable, behavior-based AI systems that track candidates over time.

Ben envisions a future where screening provides longitudinal insights—understanding not just who someone is at one moment in time, but how they've evolved, what patterns emerge, and what that might predict about their future behavior in your organization.

What Employers Should Do Now

Ben's recommendations are straightforward:

Don't change your why. You still have clear values and standards. The question is whether your screening process reflects them.

Review your code of conduct. Is it just a document employees sign off on, or do you actually enforce it? Screening is a way to make those values real.

Lean into compliance, not away from it. Be transparent with candidates about what you're screening for and why. Most will respect you for it.

Adapt your screening sources. For a workforce that's largely digital natives, social media screening should be part of your toolkit—just like reference checks or background checks.

The Bottom Line

Workplace misconduct is rising, and it's happening in the digital spaces where your future employees spend their time. The question isn't whether to screen for it—it's whether you're screening in the right places, using the right tools, and doing it in a way that's both compliant and fair.

As Ben puts it: your screening strategy should be reflective of the workforce you're actually hiring, not the one you hired 20 years ago.

Transforming Recruiting with Transparency

Doug Berg

Match2

In this episode, Doug Berg from Match2 and I discussed a critical problem plaguing the recruiting industry: the one-sided, inefficient systems that leave candidates frustrated and employers exposed to legal risk.

The Problem: A One-Sided System

The recruiting industry has built itself around what Burr calls "screening out technology." Companies invest heavily in ATS systems, CRMs, and career sites designed to process candidates—but these are fundamentally transactional, not relational. Candidates apply, disappear into a black hole, and rarely hear back.

The result? Ghosting at scale. One candidate reported applying to 100 jobs and hearing back from only 44—with 56 companies ghosting them entirely. This isn't just a candidate experience problem; it's damaging employer brands and creating legal liability.

Why Candidates Don't Apply

Here's a sobering statistic: 80% of candidates who are 75% or better matched for jobs don't apply. When researchers asked why, the answer was telling—many candidates said they won't bother applying to an ATS because they're never going to hear anything back anyway.

This creates a vicious cycle. Candidates resort to spray-and-pray job applications, flooding systems with noise. Employers respond by deploying AI screening tools to filter out the noise. But those tools often reject candidates without explanation, creating legal exposure and further damaging the employer brand.

The Solution: Pre-Apply Validation, Not Post-Apply Filtering

Berg's core argument challenges the industry's decade-long obsession with post-apply AI scoring. Instead, he advocates for pre-apply validation—letting candidates see how well they match a job before they apply.

The benefits are remarkable:

Candidates self-select: When shown they're only a 50% match, 90% of candidates opt out rather than waste their time.

Better data quality: Fake and bot applications drop by 90% when candidates are informed about their match score.

Improved experience: Candidates feel respected and included in the process rather than rejected in the dark.

Legal protection: By keeping candidates in the loop, employers reduce bias and discrimination risks.

Universal Candidate Profiles: The Missing Piece

The core innovation is a universal candidate profile—essentially, a candidate-owned resume that travels with them across platforms. Think of it like sharing a Google Doc with employers.

This solves several problems at once:

Fragmented data: Candidates are currently scattered across multiple systems at the same company—career site, CRM, ATS—with no way to update their information once.

Ghosting: When candidates can easily broadcast their status (took another job, off market, back in the market), recruiters finally have real-time information.

Passive candidate engagement: Companies can finally connect with the 90% of career site visitors who never apply, without adding recruiter workload.

Match2: Overlaying Intelligence Without Disruption

Rather than forcing companies to rip-and-replace their existing systems, Match2 integrates with any ATS or CRM. It works like this:

Candidates upload their profile and see intelligent job matches

Pre-apply validation shows fit scores

When candidates apply, the application goes directly into the company's existing system

As recruiters update dispositions in the ATS, candidates see real-time updates

If a job closes, candidates automatically see similar opportunities

The result: better data, better candidate experience, and no additional work for recruiters.

Transparency as Competitive Advantage

One of Berg's most compelling points: transparency isn't just ethical—it's a business advantage. When a physician uploads their credentials and sees three great matches, and a recruiter reaches out the same day with personalized questions about relocation and EHR systems, that's a consumer-grade experience that fills hard-to-fill roles.

Compare that to the typical ATS experience—which Berg describes as "as hard as doing a tax return just to be in consideration for a job."

The Legal Landscape

Law firms are already proactively recruiting plaintiffs for civil suits against ATS vendors over AI bias. However, Berg makes an important distinction: while vendors are being sued, the real responsibility lies with employers who configure the AI systems. The solution isn't to avoid AI—it's to deploy it transparently, with candidates in the loop rather than in the dark.

Looking Forward: A Two-Sided Marketplace

Burr's vision is ambitious: transform recruiting from a one-sided employer-controlled system into a true two-sided marketplace, similar to Facebook Marketplace or eBay.

Key developments on the horizon:

Application receipts: Candidates should receive confirmation of what they submitted and how they were scored.

Job throttling: When a position receives enough applications, it should pause to let recruiters process them before accepting more.

Candidate-owned "personal ATS": Candidates manage their own profile and can see which companies are actively recruiting them.

Re-recruitment: When companies lay off employees, they can maintain connections and re-recruit them later.

The Bottom Line

The recruiting industry's obsession with post-apply filtering has created a broken candidate experience and legal exposure. The solution isn't better AI screening—it's better pre-apply validation, universal candidate profiles, and transparency at every step.

By putting candidates in the loop, companies can reduce noise, improve quality, and build the kind of consumer-grade hiring experience that actually fills hard-to-fill roles.

Eightfold AI Lawsuit: What It Means for Hiring Transparency and Data Sovereignty

Lawsuits & Hiring Software

Alex Murphy and Leah Daniels from Jobsync

The recent Eightfold AI class action lawsuit is making waves in the recruitment technology industry, but it's not really about AI—it's about data protection and personal data sovereignty. In today’s podcast, industry experts Alex Murphy (CEO of JobSync) and Leah Daniels (COO of JobSync) break down what this lawsuit means for vendors, employers, and job seekers alike.

The Core Issue: Hidden Dossiers and FCRA Violations

In January 2026, plaintiffs filed a class action lawsuit against Eightfold, alleging violations of the Fair Credit Reporting Act (FCRA) for creating undisclosed consumer credit reports on job seekers. The company allegedly scraped personal data from third-party sources like GitHub and LinkedIn to rank applicants without providing transparency or allowing candidates to dispute the information.

"It's really around data and data protection and call it personal data sovereignty," Murphy explained. "We can build technology, but it actually has to be done inside the scope of what the law of the land is."

Not All AI Is the Problem

An important distinction: this lawsuit isn't about AI scoring itself, but about how vendors use undisclosed external data to influence hiring decisions. As Daniels points out, "Not all AI is going to fall under this... An AI that rewrites your job description is unlikely to be swept up in this particular lawsuit."

The problem arises when vendors create what Daniels calls "secret dossiers"—secondary sets of data about candidates that they use for evaluation without the candidate's knowledge or ability to correct it. This is particularly dangerous because of data accuracy issues. "People with the same name, especially like a junior and a senior, could go to the same university, could even have worked at the same company. That will confuse most technology into thinking it's the same person when it is not," Daniels warns.

The FCRA Requirements Are Clear

The regulations governing consumer reports are extraordinarily specific. A simple checkbox on an application form is insufficient compliance. "The law is actually really clear about the fact that it has to be a separate document from the application. So you can't sneak it into like a check the box type of exercise," Murphy explains.

Once this lawsuit puts the industry on notice, ignorance is no longer an excuse. "You don't have that excuse anymore," Murphy states, suggesting that vendors and employers now have clear warning that compliance is mandatory.

The Transparency Problem: Easier Said Than Done

While transparency seems like an obvious solution, it creates its own challenges. If vendors must disclose the AI models and training data used to score candidates, how can they explain a black-box algorithm to job seekers? And if candidates can dispute scores, does that eliminate the efficiency gains that AI scoring was supposed to provide?

"If I score a hundred people and ten of them get a ninety and better and the other ninety get a ninety or lower, you're going to have ninety people disputing the score," Daniels notes. "That has not created any efficiency for the recruiting teams. That has created nothing but inefficiency."

Leah predicts that upfront scoring algorithms may disappear entirely as a result of these transparency and dispute requirements.

The Resume Arms Race: AI vs. AI

Adding another layer of complexity, job seekers are increasingly using AI to generate and optimize their resumes. This creates a problematic feedback loop: when AI-written resumes are evaluated by AI scoring algorithms, the result may simply be the most cleverly optimized prompt, not the best candidate.

"When one AI evaluates the quality of a resume as a match for the job posting when that resume was written by another AI, the AI says that's a really, really good match. That's what I would have written had I written that resume," Murphy explains.

Job Seeker Empowerment: New Models Emerging

Some platforms are taking different approaches to help job seekers stand out. Greenhouse has introduced "dream jobs"—free tokens that allow candidates to signal strong interest in a position. ZipRecruiter is bringing back cover letters as a way for candidates to highlight their interest. Indeed is testing paid priority placement in Canada.

However, there's speculation about where these models will lead. "I wonder how long it'll take before they are tempted with, 'Oh, but a second token costs you 20 and you can buy three for 50,'" Murphy muses. While Greenhouse currently operates in the enterprise software business rather than charging job seekers, the financial temptation may eventually prove irresistible.

What TA Leaders Need to Do Now

The implications for talent acquisition leaders are significant. They need to become more technically sophisticated in evaluating vendors and asking harder questions about data usage.

"TA leaders need to be much more technical. They have to ask a lot more questions. How, where, why? What will that do for me? What's the risk?" Daniels advises.

Specifically, leaders should understand the distinction between data controllers and data processors—a concept more familiar in Europe but increasingly critical in the U.S. "If you have any experience or any exposure in Europe, that is actually a thing that you really do completely need to understand," Murphy notes.

The Bigger Picture: A Broken Hiring Market

Beyond the lawsuits, both experts agree the entire hiring marketplace is fundamentally broken for everyone involved. The economy's uncertainty, geopolitical concerns, and post-COVID overhiring have created a hiring environment driven by replacement needs rather than growth.

"How does anybody make any decision to commit and hire a big group of people and a team of people? At best, really what you're doing is you're doing replacement hiring," Murphy observes.

What's Coming Next

The Eightfold lawsuit represents a watershed moment. While the Workday-Mobley lawsuit may favor the employer, the Eightfold claims appear much stronger given the company's marketing materials about using third-party data sources.

The industry should prepare for stricter regulatory scrutiny. Vendors must implement transparent candidate data disclosure and dispute processes similar to FCRA requirements for any AI hiring tools that collect or utilize third-party candidate data. And TA leaders should be ready to ask tougher questions about vendor compliance and data protection.

One thing is certain: the days of hidden dossiers and opaque AI scoring are numbered.

The Inbox vs. The Pocket: Why ATS Vendors Need to Embrace Text for Hourly & Skilled-Trade Hiring

The world of work is evolving, and so are the ways we communicate. Yet, in the critical realm of applicant tracking systems (ATS), one stubborn legacy persists: the mandatory email address. For high-intent hourly and skilled-trade workers, this isn't just an outdated formality – it's a colossal barrier, costing employers valuable talent and frustrating candidates before they even begin.

The data paints a stark picture:

• Mobile Domination: A staggering 98% of U.S. adults own a mobile phone. Their lives, and their job searches, happen on these devices.

• Text Wins the Engagement Battle: Text messages boast an astounding ~98% open rate and a 30-45% response rate. Responses happen in minutes.

• Email Lags Far Behind: Email, in contrast, averages a ~20% open rate and often single-digit response rates. Responses can take hours or even days.

This communication gap hits hourly and skilled-trade candidates the hardest. Imagine a construction worker on a job site, a truck driver on their route, or a healthcare assistant in the middle of a shift. They're working with their hands, constantly on the go, and often wearing gloves. For them, a quick text message is natural, immediate, and convenient. Diving into an email inbox on a small screen is slow, cumbersome, and easily postponed – or worse, forgotten entirely.

The "Email First" Mandate: A Relic Holding Back Progress

Despite these undeniable realities, almost every ATS still demands an email address as the very first step to apply or even connect. This isn't just about a full application; it prevents career site visitors from joining talent communities, receiving vital job alerts, or engaging with potential employers in real-time.

Are we truly optimizing for the needs of today's dynamic workforce, or are we simply bowing to the limitations of legacy systems?

The Solution is Clear: Text-Based Job Alerts

It's time for ATS vendors to catch up. The solution isn't complex; it's intuitive: offer integrated text-based job alerts for employers.

Imagine the impact:

1. Reduced Friction, Increased Conversions: Instead of abandoning an application due to an email hurdle, candidates could opt-in for text alerts instantly. This drastically lowers the entry barrier, boosting application start rates and ultimately, successful hires.

2. Meeting Candidates Where They Are: Employers could deliver relevant job openings directly to candidates' pockets, leveraging the communication channel they use most frequently and are most likely to respond to.

3. Real-Time Engagement: When a new relevant position opens, a text alert means instant notification. No more waiting for candidates to check their overflowing inboxes. This real-time interaction is crucial for capturing high-intent talent quickly in competitive markets.

4. Enhanced Candidate Experience: By offering a convenient and preferred communication method, employers demonstrate an understanding of their candidates' lives and work styles, fostering a more positive and efficient experience from the very first interaction.

5. Competitive Advantage for Employers: ATS platforms that offer this functionality will empower their employer clients to outperform competitors who remain shackled to email-only strategies.

The candidate experience begins with the very first field required. By clinging to email as the sole gateway, ATS vendors are inadvertently creating unnecessary friction that alienates a massive segment of the workforce.

It's time to disrupt the status quo. The future of hiring for hourly and skilled-trade roles isn't in the inbox; it's in the pocket. ATS vendors, the call to action is clear: embrace text-based job alerts and unlock a new era of talent acquisition. The first step for ATS vendors to take is to integrate mobile-first solutions, like text-based job alerts, directly into their platforms. This means re-evaluating the initial application fields and offering SMS as a primary communication option.

Greenhouse CEO Daniel Chait on Breaking the AI "Doom Loop" in Hiring

Daniel Chait

Greenhouse CEO

In this episode of the RecTech Podcast, Chris Russell sits down with Daniel Chait, CEO of Greenhouse Software, to discuss the company's expanded mission to make hiring work for everyone—not just employers. Here are the key takeaways from their conversation.

The AI Doom Loop: A Problem for Everyone

Chait opens by describing what Greenhouse calls the "AI Doom Loop"—a vicious cycle where both job seekers and employers are struggling. Job seekers use AI tools to automatically apply to hundreds of jobs, while employers are overwhelmed with thousands of undifferentiated applications and resort to using AI filters to narrow them down. This creates a tightening window for candidates and pushes them to apply to even more jobs, perpetuating the cycle.

The key insight: It's not that AI is bad—it's that the current AI tools are making the hiring problem worse for everyone.

Expanding Beyond Employers to Job Seekers

After 14 years of focusing on helping companies hire better, Greenhouse is now bringing job seekers directly into its mission. Chait explains that the problems job seekers face are often the same problems companies face, so solving for both sides is essential.

New Features Driving Change

My Dream Job

Candidates can designate one preferred application per month across Greenhouse customers. This creates a strong signal to employers that the applicant is genuinely interested and reasonably qualified. The results speak for themselves: over 1,500 candidates have gotten their dream jobs, and these applicants convert at five times the rate of other candidates.

My Greenhouse Portal

Job seekers can create profiles, easily apply to jobs, and track their application status in real-time. As candidates move through the hiring funnel, their portal automatically updates—eliminating the dreaded silence that plagues most job searches.

Greenhouse Verified Badges

Employers earn badges for providing timely feedback and completing interview scorecards. This transparency helps job seekers identify responsive employers and avoid wasting time on companies that don't communicate.

Real Talent: A Triple Layer of Trust

Greenhouse recently launched Real Talent, a product that combines three critical trust layers:

1. Candidate Intent Matching — Distinguishes high-intent applicants from those who auto-applied

2. Bad Actor Detection — Uses technical and behavioral signals to identify fraudulent applications

3. Identity Verification — Confirms applicants are who they claim to be in a remote-first world

Importantly, Greenhouse audits these systems monthly through Warden AI to ensure fairness and prevent bias.

The Future: Beyond Resumes

Chait envisions a future where AI agents represent candidates dynamically rather than static resumes. Instead of a one-page document unchanged for years, candidates would have living profiles that communicate their skills, interests, and cultural fit to employers.

AI Interviewing: More Fair Than Human Interviews?

While acknowledging skepticism, Chait argues that AI-driven interviewing has the potential to be fairer and more consistent than human interviews, which have well-documented biases. The key is intentional design with input from legal, HR, and DE&I experts.

Legal and Ethical Considerations

Recent lawsuits against companies like Workday and Eightfold highlight the need for transparency in AI hiring systems. Greenhouse's approach: involve legal, HR, and DE&I teams early in product development, not as an afterthought.

The Job Market Reality

The job market isn't monolithic. While healthcare workers and AI-capable engineers are in high demand, other fields face tougher competition. Chait's advice for job seekers: apply early and be strategic. Data shows that early applicants are significantly more likely to get hired.

Scale and Responsibility

With over 60 million job applications processed quarterly and over 1 million daily active users, Greenhouse has both the opportunity and obligation to improve hiring for everyone.

What's Next for Greenhouse

Expect a multimillion-dollar investment in AI-powered solutions throughout 2026, with regular feature releases designed to help both job seekers and employers break the doom loop.

Key Takeaway

Greenhouse's shift to focus on job seekers alongside employers represents a meaningful pivot in the ATS market. By solving problems for both sides of the hiring equation—and doing so with intentionality around fairness and transparency—the company is positioning itself as a leader in reimagining what hiring could be.

AI Recruiter 2.0: Transforming Recruiting with AI-Powered Tools

Mike Wolford

The AI Recruiter 2.0

In a recent podcast episode, Michael Wolford, author of AI Recruiter 2.0, discussed how artificial intelligence is revolutionizing the recruiting industry by automating administrative tasks and empowering recruiters to focus on what they do best: building relationships and adding real value1.

The Vision: Freeing Recruiters to Focus on People

Michael's core philosophy is straightforward: use AI to eliminate administrative burden so recruiters can spend their time on high-value activities1. Rather than drowning in scheduling, feedback tracking, and prospect research, recruiters can:

Advocate for candidates through interview prep and guidance

Act as business advisors equipped with data and solutions to help hiring managers make informed decisions

As Michael notes, this shift not only improves job satisfaction but also enhances recruiter effectiveness. One example highlighted was a recruiter named Jordan, whose mental energy shifted from administrative tasks to meaningful interactions with people—transforming her job experience1.

2026: The Age of Empowerment

Michael identifies 2026 as a pivotal moment where recruiters no longer need to wait for vendors to build the "perfect tool." Instead, they can build customized solutions themselves1.

Building Recruiting Apps Without Coding

A prime example is Prospect Pro, an app Michael built to automate Boolean searches and email synthesis from publicly available data1. Using tools like:

LM Arena — Free access to all major AI models

Gemini 3 Pro — For technical planning and guidance

Lovable — A no-code platform for building web apps

Michael created a fully functional sourcing app that:

Automates Boolean searches on Google

Synthesizes email addresses for prospects

Generates CSV exports with names, titles, companies, and contact info

Reduced manual sourcing time from hours to minutes1

Remarkably, his first app build took five hours; now he can build similar applications in just 1.5 hours1.

The Prompt Pyramid: Mastering AI Communication

To get quality results from AI, Michael emphasizes the importance of the "prompt pyramid," which consists of five layers1:

Task — What you want done

Context — Defining the AI's persona and target audience (the most critical missing piece)

Constraints — Limitations or specific requirements

Example — Sample outputs to guide the AI

Output — The desired format

The context layer is particularly important because AI works through statistical language models that map word relationships mathematically1. Without context about who the AI is speaking to and why, results become generic and repetitive.

Real-World Impact: Candidate Pitches and Outreach

AI-Generated Candidate Summaries

Michael demonstrated how AI can elevate recruiter output. A well-structured prompt can generate:

Professional candidate summaries

Match percentage tables comparing candidate qualifications to job requirements

Quantitative proof points that help hiring managers say "yes"1

Outreach Response Rates

LinkedIn data shows compelling results1:

Human recruiter outreach: 22% response rate

AI-generated outreach: 31% response rate

Looking forward, Michael predicts AI will become even more sophisticated, personalizing not just message content but also timing, channel, and tone based on candidate behavior patterns1.

Creative Personalization

During the podcast, Michael demonstrated real-time email generation with creative constraints—writing in Yoda's voice with emojis—showing how AI can produce engaging, personalized outreach at scale1.

Beyond Recruiting: Creative Use Cases

Recruiters are already discovering innovative applications1:

Automating entire interview processes with suggested questions and rubrics

Company-wide skills assessments to identify organizational gaps

Rediscovery agents using API/MCP keys to search entire ATS databases beyond typical limits, enabling tailored filtering by recruiter-defined criteria1

The Future: Agentic AI Replaces SaaS

Michael predicts that AI agentic apps will replace traditional SaaS vendors due to lower costs and faster deployment1. This shift creates a new job opportunity: the Prompt Engineer—professionals who can translate domain expertise into effective AI prompts without writing code1.

Michael's Final Advice

As Michael concludes, the path forward is clear1:

Document your current manual recruiting processes

Automate them with AI tools

Focus on value, not effort — Nobody cares how hard you work; they care about results

In a world where AI can handle the administrative heavy lifting, job security comes from adding genuine value to candidates, hiring managers, and your organization.

About the Guest

Michael Wolford brings deep recruiting expertise, having worked in agency recruiting, managed sourcing teams at Twitter (2021-2022), and written extensively for SourceCon and Recruiting Daily for nearly a decade1. He's authored multiple books on AI in recruiting and is the founder of what is becoming Generative Sales Pro (formerly Lex Duo).

https://www.linkedin.com/in/mikewolford/