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.

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.

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 ChangeMy 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.

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/

In a recent podcast episode, Chris Russell sat down with Daniel Walsh, CEO and founder of Veroskills, to discuss how their AI-powered staffing platform is addressing the $1 trillion blue-collar labor gap. With a new $5.3M funding round, Veroskills is on a mission to transform hiring and empower both employers and job seekers in the blue-collar sector. Here are the highlights:

Bridging the Blue-Collar Labor Gap Veroskills focuses on connecting skilled blue-collar talent with nationwide employers, leveraging AI to streamline and enhance the recruitment process. Their technology enables efficient job matching, deep skill assessments, and even resume creation for candidates without one.

How the Process Works

• Employers provide job details, which the platform transcribes and uses to launch multi-channel job postings and targeted social media ads.

• Candidates progress through an AI-driven interview and skills assessment—an in-depth, language-agnostic process lasting up to an hour.

• AI scores candidates and determines readiness for background checks.

• For candidates without resumes, the platform generates one automatically from the interview insights.

Human Touch Where It Matters After onboarding and payroll setup, Veroskills staff coordinate interview scheduling and direct communication. Candidates are kept informed by text throughout, including preparation tips and onboarding steps.

‘No-Risk’ Working Interview Day Veroskills introduces a “working interview day,” letting candidates work on-site and get paid before a hiring decision. This builds trust with employers and has an 80% success rate in placements.

Business Model Built for SMBs As employer of record, Veroskills manages payroll, taxes, and insurance—relieving small business owners of complex administrative tasks. The platform serves sectors typically untouched by large staffing firms and charges a transparent mark-up over hourly wages.

Upskilling & Future-Proofing the Workforce Recognizing a shortage of skilled workers, Veroskills offers a library of 900 free upskilling courses to help employees advance from general labor to licensed trades, supporting both worker growth and employer retention.

Competitive Advantage By automating and scaling the candidate pipeline, Veroskills processes thousands of interviews daily and fills jobs in days, not weeks. Their AI-first approach allows them to serve niche and remote roles with efficiency unmatched by traditional firms.

Rapid Growth & Industry Connections With about 50 employees and plans to expand presence at industry conferences, Veroskills is poised for further growth. CEO Daniel Walsh emphasizes the company’s focus on human flourishing—helping people find meaningful, well-paid work in trades with long-term demand.

Conclusion Veroskills is redefining how the blue-collar workforce is sourced, screened, and onboarded—making it easier for businesses to hire qualified workers and for individuals to access promising career paths in skilled trades.

Learn more at veroskills.com.

RippleMatch recently announced the launch of its AI-Talent Marketplace, a skills-based hiring engine built to meet the realities of a job market transformed by AI. The new platform replaces resumes and proxies with verified skill signals showcasing AI fluency, interpersonal skills, and technical proficiencies. Designed to serve the next generation of talent and companies building the modern teams of tomorrow, this product marks a “shift in how early-career hiring happens”.

Here to discuss the new features and the state of early career recruiting is their COO Brennan Delsing.

TOPICS

1. Give us a brief history of Ripplematch and tell the audience what you do?

2. Your announcement places a huge emphasis on "AI fluency" as the new critical skill. This is a new and abstract concept for many. How does your platform practically and verifiably measure a candidate's ability to "wield AI tools," beyond just them listing it as a skill?

3. The releases notes that AI has amplified hiring problems by enabling "bot-like behavior and inflated qualifications." How does your marketplace technically differentiate between a candidate who truly possesses a skill versus one who simply used AI to generate a polished-but-empty application?

4. Demo …

5. With AI automating so many traditional entry-level tasks, many young professionals are anxious. How does your platform actively guide a candidate to identify their specific skill gaps and become what you call "AI-ready"?

6. This platform is built on "verified skill signals" instead of "outdated resumes." Five years from now, do you see this as the beginning of the end for the traditional resume? And what impact will that shift have on the broader early-career ecosystem, from universities to the "AI-native" students themselves?

7. Got a favorite feature?

Todays episode is sponsored by ⁠Cliquify⁠, my travel sponsor for this event.

In this episode you will hear from a variety of TA and Employer Brand execs tell you what’s in store for 2026, how AI is affecting their jobs and more!

• Ian Ide, Foundation Medicine

• Rachel Duran, HP Enterprise

• Tractor Supply TA team

• Dan Lockhart, Sondermind

• Cathy Rogers B2B VIP

• JCK, GBS Worldwide

• Kylie Denk, Index Exchange

• Michael Glenn, Agility Hire

• Nick Russell Advisor360

• Kara Yarnot, Author

Around 2,000 folks hit the Fairgrounds in Nashville for the annual two day RecFest event.

Melissa King is the SVP of Product & Technology for Paylocity. We chatted at the recent HR tech Conference in Las Vegas.

• How long have you been at Paylocity and describe your role?

• Myth you do more than payroll…All the payroll companies seem to be HCM suites at this point, correct?

• How Paylocity is weaving AI into its platform to power smarter navigation and real assistance across the HR functions? AI assistant

• Is the future of HR systems agentic?

• Whats your fav new AI feature in the product?

• What is HR software like in 10 years? Describe a couple use cases

• What do you think of all the M&A going on…?

John Deal, Phenom’s Sr Director of Product Marketing stops by to catch us up on their Agentic AI rollout.

• You announced your Ai agents back in March give us an update on where the rollout stands.

• Any new features since the spring?

• Whats your favorite feature?

• Thoughts on all the acquisitions?

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isolved’s Heidi Barnett stops by at the HR Tech show to detail their new partnership with Indeed. Along with Workable, isolved is one of only two hand-selected partners worldwide to seamlessly integrate  with Indeed Talent Scout, a new intelligent conversational artificial intelligence (AI) agent  designed to improve how employers find, engage and hire talent.