AI and the Future of Hiring (Expert Talks)

What happens when AI starts thinking like a recruiter? In this episode of the Retention Podcast, we chatted with Maksym Bilyak, CPO at Jooble, and Mark Opanasiuk, Product Lead at PawChamp, about how large language models are shaking up the hiring process. 

With Jooble helping people find jobs in 67 countries and PawChamp building a focused mobile experience, both guests bring sharp insights from very different corners of the hiring world.

We dug into how sourcing is changing, what’s happening to job boards, and why AI still can’t replace a recruiter’s gut feeling. Here’s what stood out.

Smarter Job Posts and Candidate Sourcing

Forget those one-size-fits-all job ads. AI is helping teams write openings that actually make sense for the role—and attract the right people. On the flip side, it can scan resumes and profiles to find solid matches automatically, even before a recruiter gets involved.

From Resume Analysis to Full Automation

Once someone applies, AI can jump in to screen, score, and compare candidates based on what really matters—skills, experience, and relevance. It’s fast and fair, and helps make sure strong candidates don’t get missed.

Helping Out Job Seekers

Job seekers get some help, too. AI tools now give tips for resumes and cover letters, prep you for interviews, and even suggest career moves based on your background. Pretty handy when you're not sure what comes next.

Are Job Boards on the Way Out?

AI-driven sourcing is flipping the script. Instead of people hunting for jobs, the jobs come to them. That’s putting pressure on job boards to figure out how they still fit in.

Bias and the Rules Around AI Hiring

One big issue: fairness. If the data going into an AI system is biased, the results will be too. That’s why regulations are starting to show up—things like explainable decisions and audit trails are becoming must-haves.

Reasoning in LLMs and Lead Gen

Large language models aren’t just fancy chatbots — they’re learning to reason. That changes everything. They can already review resumes with solid logic, but people still hire based on emotion, too. So candidates need to hit both: look good to the algorithm and connect with the human.

Lead generation is changing, too. It used to be about traffic—from newspapers to job boards to Google. Now LLMs can cut through the noise and figure out who actually fits and why.

Social Media, AI, and the Changing Job Market

Social media isn’t just for memes anymore. It’s where people find jobs and show off their skills. AI watches for signals and can spot when someone’s ready to make a move—even before they send out an application.

Is Google Still Needed to Find a Job?

LLMs are changing how we find work. Instead of sending you to Google to dig around, they take you straight to job opportunities that actually make sense. That could cut out job boards — and even Google itself — from the process.

These models still use platforms like Google and social media to gather info, but they don’t just send people there. They filter everything first and serve up what’s useful, no extra steps needed.

Search, But Smarter

Search isn’t just about keywords anymore. AI tries to understand what you mean, not just what you type. For hiring, that means better job matching and smoother experiences on job sites.

Finding Candidates (or Clients) Automatically

AI isn’t just for hiring — it’s big in sales too. Whether you're looking for the right hire or the right client, the process is similar: scan a ton of data, figure out who fits, and reach out.

The Race Between OpenAI and Anthropic

Two major players — OpenAI and Anthropic — are shaping the future of AI. OpenAI moves fast and open, while Anthropic leans toward safety and control. The tension between them is fueling innovation, but also raising tough questions about direction and responsibility.

Low-Code Tools and AI Product Building

Low-code and no-code tools are everywhere now. Thanks to AI, non-developers can prototype, build, and ship things faster than ever. You don’t need to be technical to launch something real anymore.

Will One Giant Win the B2C AI Race?

When it comes to consumer apps, there may never be one AI to rule them all. Instead, we’ll probably get a ton of niche tools powered by shared AI infrastructure. More variety, but more fragmentation too.

Critical Thinking in an AI-First World

One risk with AI? People stop questioning the info they get. LLMs can sound super confident — even when they’re wrong. Unlike a Google search, you’re not checking sources, you’re just trusting the answer. That’s where misinformation can sneak in.

Even though LLMs use the same data sources, they act as filters now. They decide what’s worth showing, so we have to trust their judgment — and that’s a big shift.

AI-Powered Marketing

Marketers are using AI to write, test, and analyze everything in real time. What used to take a whole team, one person can do now. It’s a game-changer — but if you’re not careful, it’s easy to push out a lot of noise.

Rethinking Tests and Interviews

AI is helping create smarter assessments. It can generate role-specific questions and adapt based on the candidate. That makes interviews more useful—but it also means we need new ways to understand the results.

Working with AI Is the New Basic Skill

If you want to stay ahead, knowing how to work with AI isn’t optional. Whether it’s prompt writing or integrating APIs, people who can use these tools will be the ones leading teams and building stuff.

AI in Tech Interviews

In technical hiring, AI can now simulate real-world problems, assess solutions, and even benchmark performance. It helps reduce bias and streamline the process — but it’s not perfect. Human judgment still matters.

AI and Final Hiring Decisions

AI doesn’t just help you build the shortlist — it can help with the final call too. It can sum up interviews, flag skill gaps, and show where team strengths overlap. This helps build more balanced teams that actually work well together.

Making Interviews More Objective

Interviews are getting a consistency upgrade. AI can suggest better questions, standardize feedback, and highlight unconscious bias. The result? Clearer data and better decisions, without losing the human touch.

AI and Structural Unemployment

As AI automates more roles, some jobs just disappear. It’s not about people failing — it’s that entire roles become outdated. This creates a gap between skills and available work. The fix? Ongoing learning and flexible career paths.

The Rise of New AI-Focused Roles

AI is wiping out some jobs but creating new ones just as fast. Think AI product leads, prompt designers, and LLM behavior experts. Many aren’t even technical roles —they need ethics, communication, and strategy skills.

Building Stable AI Products

AI can do incredible things—but it can also be unpredictable. That’s why testing and quality control are now top priorities. Teams spend as much time reviewing outputs as building features. It’s about shipping responsibly, not just fast.

The Roundup

AI is reshaping hiring from the ground up. We’re no longer stuck with clunky keyword filters — now, algorithms are picking up on intent, context, and nuance. Job sourcing, candidate matching, decision-making — all of it is getting faster and more precise.

But with that progress comes friction. Bias can hide in training data. AI-generated profiles can blur the line between real and fake, so there's a growing need to keep humans in the loop to make sure decisions stay fair and responsible.

As AI keeps advancing, the real challenge isn’t just using it — it’s knowing when not to. The future of hiring will be built on collaboration between tech and people, not one replacing the other. And hey, if a robot ever tries to interview you — maybe don’t ask them where they see themselves in five years.