Recruiting has gone from faxed resumes and Rolodexes to AI tools that can do almost everything. We’re moving faster than ever, but are we actually hiring better?
That’s one of the big questions I explored with Julia Levy in a recent episode of TA Talk, part of my podcast, The JD Fix.
Julia has more than 20 years of experience in talent acquisition, recruiting operations, recruitment marketing, and global talent leadership. She’s worked with companies like CommScope and AutoZone, and today she’s consulting, advising HR tech companies, and building her own AI-powered tools.
We talked about AI in recruiting, what she learned at RecFest, the growing problem of application overload, and why better job descriptions may be one of the simplest places to start fixing hiring.
And yes, we laughed about how much recruiting has changed. Some of us actually remember when fax machines were part of the process.
Listen to TA Talk with Julia Levy
Want to hear the full conversation? Listen below as Julia and I talk about the future of recruiting, AI, candidate experience, and the changes TA teams should be thinking about right now.
AI in Recruiting Is Everywhere. But What’s It Actually Fixing?
One of the first things I asked Julia about was RecFest. I couldn’t attend this year, so I wanted to hear what stood out to her.
Unsurprisingly, AI was a big topic.
But Julia noticed something worth paying attention to. Plenty of vendors were talking about AI for hiring without clearly explaining what problem their technology was supposed to solve.
She even mentioned seeing what might be a little “vaporware” in the market.
That made me laugh, because we’ve all seen technology that sounds incredible in a demo but leaves us wondering what we’d actually do with it on Monday morning.
For talent acquisition teams, the question shouldn’t simply be whether a tool uses AI.
It should be:
- What task is taking too much time today?
- Where are recruiters getting stuck?
- What mistakes keep happening?
- Can this tool improve the process without creating more work?
- How will we know whether it’s helping?
I’ve seen a similar mix of excitement and caution in conversations with Ongig clients. Some teams are eager to use AI to handle repetitive job description work. Others have strict policies or need more time to get comfortable with the technology.
Both approaches are understandable.
Adding AI to a broken process doesn’t automatically make it a good process. Sometimes it just helps you make the same mistakes faster.
What If Recruiting Technology Worked Around Your Process?
Here’s another idea from our conversation that I think deserves more attention.
For years, companies have had to adjust their recruiting workflows to fit the software they purchased.
Anyone who’s worked in TA operations knows what that can look like.
You need a specific approval process, but the system only supports a standard one. Your company has different compliance requirements by location, but your tools treat every job the same way.
Before long, your team is managing spreadsheets, sending extra emails, or creating workarounds just to get things done.
Julia sees AI creating new opportunities for companies to build tools around their own needs.
That’s especially interesting when it comes to job description management.
At Ongig, we work with organizations that have very different processes for creating, reviewing, approving, and publishing job descriptions.
Some need multiple reviewers. Others need specific wording for different regions or business units. Some want tighter control over who can make changes.
AI agents and customizable workflows could eventually help teams handle more of those differences without forcing everyone into the same process.
That’s an area we’re working on at Ongig, and one I’m really excited about.
But even before introducing new tools, there’s a useful exercise for TA teams: write down every step involved in getting a job description from the hiring manager to the job posting.
Then ask which steps are necessary, which ones are repeated, and which ones could be simplified.
You may find opportunities to improve your process before adding another piece of technology.
More Applicants Doesn’t Always Mean Better Candidates
Remember when recruiters worried about getting enough people to apply?
Now, some teams are dealing with hundreds or thousands of applications for one opening.
AI has made it easier for candidates to tailor resumes and apply for jobs. Meanwhile, employers are using AI to screen applications and manage the volume.
That’s creating an interesting problem on both sides.
During our conversation, Julia described a scenario that probably sounds familiar.
A hiring manager finds a job description from three years ago, changes a few details, and sends it to recruiting.
The description still has a long list of requirements. Some are essential. Others may have been copied from an older role and never questioned.
Then candidates use AI to match their resumes to those requirements.
Recruiters receive a pile of applications that all seem to say the right things.
And figuring out who actually has the skills becomes harder.
Julia described the result as a lot of noise in the middle.
We spend so much time talking about how AI can help recruiters review more applications. But what if we spent more time improving the job descriptions that attract those applications in the first place?
Better Job Descriptions Can Help Reduce Recruiting Noise
A job description is usually one of the first places a candidate learns what an employer wants.
When that description is confusing, outdated, or filled with unnecessary requirements, it can create problems before recruiting even begins.
That’s why job description quality matters so much.
Here are four things I’d encourage TA teams to review before publishing another opening.
1. Separate Required Skills From Nice-to-Haves
Does someone really need every qualification listed to succeed in the role? Or have years of additions turned the description into a wish list? Work with hiring managers to agree on the skills that are truly necessary on day one. That makes expectations clearer for candidates and gives recruiters a better starting point for evaluating applicants.
2. Stop Recycling Outdated Job Descriptions
Using an existing job description as a starting point can save time. But it shouldn’t mean copying everything without reviewing it.
Responsibilities change. Technology changes. Teams change. A description written several years ago may no longer reflect the work someone will actually do.
Before reposting it, ask the hiring manager what has changed and which responsibilities matter most today.
3. Make Job Requirements Easy to Understand
Clear language helps candidates decide whether a job fits their experience.
That means avoiding vague phrases, confusing internal titles, and long paragraphs filled with company jargon. It also means explaining the work in a way someone outside your organization can understand.
When candidates know what they’re applying for, they can make better decisions about whether to apply.
4. Create a Consistent Review Process
Job descriptions shouldn’t depend entirely on whoever happens to write them that day.
A consistent process can help teams check for missing information, unclear requirements, inconsistent language, and potential compliance concerns.
It also makes collaboration easier when recruiters, HR, compensation teams, and hiring managers all need to weigh in.
At Ongig, this is a big part of what we help companies manage through our job description software.
The goal is to make it easier to create clear, consistent job descriptions without turning every edit into another email chain.
The TA Team of One Has a Lot on Its Plate
Another part of my conversation with Julia focused on something I’ve been hearing more often: smaller recruiting teams managing workloads that haven’t gotten any smaller.
Budgets are tight. Teams are lean. Hiring managers still need their roles filled.
And the work doesn’t disappear just because the team has fewer people.
Julia has experienced this challenge throughout her career, including at large organizations where business growth didn’t always mean more recruiting resources.
This is where AI can offer real value.
Think about how much time a recruiter or TA operations professional spends on tasks like:
- Cleaning up job descriptions before posting
- Checking that required information is included
- Following up on approvals
- Making the same wording changes across multiple jobs
- Coordinating reviews with hiring managers
- Finding the latest version of a document
These tasks matter, but they can consume hours that recruiters could spend speaking with candidates, advising hiring managers, or improving the hiring process.
My suggestion is to start with one repetitive task and look for a way to simplify it. You don’t have to rebuild your entire recruiting operation overnight.
And if you’re already doing the work of three people, the last thing you need is another giant project added to your plate.
Should AI Make Hiring Decisions?
One of my favorite questions to ask TA Talk guests is what they’d fix if they had a magic wand.
When I asked Julia, she focused on improving how organizations understand candidate skills and competencies.
With AI helping people create resumes, it’s harder to tell candidates apart based on their applications alone.
Julia wants better ways to understand what people can actually do. But she also made an important distinction: AI doesn’t necessarily need to make the hiring decision.
Instead, it can help recruiters gather information, improve workflows, and spend more time evaluating what matters.
I think that’s a useful way to approach AI in hiring. Use it to support good judgment, not replace it.
For example, AI might help identify unclear job requirements or organize information for review. But people still need to check that the criteria are appropriate, job-related, and fairly applied.
Hiring decisions affect real people. Accuracy, fairness, and human oversight matter.
Don’t Forget the Human Side of Recruiting
We also talked about the candidate experience and what job seekers can do to stand out in a crowded market.
Julia’s advice came back to something that’s been important in recruiting for decades: relationships.
She compared networking to a bank account. You need to make deposits before you can make withdrawals.
I loved that comparison.
We’ve probably all received messages from someone asking us to find them a job, sometimes without much introduction.
And while those requests usually come from a good place, building genuine relationships over time is a much stronger approach.
Julia has even created a tool called Your Network Read to help job seekers better understand their LinkedIn networks and find ways to build connections.
It’s a reminder that while technology can help people find opportunities, relationships still matter.
The same goes for recruiters.
AI may help with repetitive work, but conversations, trust, empathy, and understanding what a candidate brings to the table are still essential parts of hiring.
From Rolodexes to AI Agents: What’s Next?
Near the end of our conversation, Julia and I talked about just how much recruiting has changed.
She’s seen the days of faxed resumes, newspaper ads, and Rolodexes. Now we’re talking about AI agents, custom tools, and technology that can help recruiters rethink entire workflows.
That’s a pretty big leap.
Julia is embracing these changes through her consulting work and tools like Rec Sentry, which focuses on job posting compliance.
She’s also co-hosting The Missing Manual podcast with Jenny Cody Kangas, exploring the things we deal with at work that nobody gives us instructions for.
And I think that sums up where recruiting is right now. We’re learning as we go.
Some AI tools will make a meaningful difference. Others may create more work than they save. And some of the biggest improvements may come from fixing the processes we’ve been using for years.
As my three-year-old likes to say, everything is moving at “super speed.” He wasn’t talking about recruiting, but the description fits.
My takeaway from talking with Julia is simple: before asking how much faster AI can make hiring, ask whether you’re improving the experience and results along the way.
Better job descriptions, clearer requirements, simpler workflows, and more time for real conversations are all good places to start.
Why I Wrote This
Working with talent acquisition and HR teams at Ongig, I see how much time goes into creating, editing, reviewing, and managing job descriptions.
I’ve also seen how easily outdated content and inconsistent processes can create extra work for already busy teams.
My conversation with Julia was a good reminder that the best technology starts with a real problem.
At Ongig, we help organizations improve job description quality, create more consistent content, and make job description workflows easier to manage.
If your team is spending too much time fixing job descriptions, chasing approvals, or dealing with inconsistent content, request a demo of Ongig to see how we can help.
And if you haven’t listened to my conversation with Julia yet, check out the podcast player above. I’d love to know what you’d fix first if you had a magic wand for recruiting.
FAQs About AI in Recruiting
How is AI being used in recruiting?
AI is being used to help write job descriptions, source candidates, organize applications, support recruiting workflows, and reduce repetitive tasks. The most useful applications solve a clear problem and leave people responsible for important hiring decisions.
Can AI improve job descriptions?
Yes. AI can help teams identify unclear wording, improve consistency, and review job descriptions more efficiently. Human review is still important to confirm that responsibilities, requirements, and compliance details are accurate.
Why are recruiters receiving so many applications?
Online job boards and AI-powered application tools have made it easier for candidates to find and apply for roles. Clear job descriptions and well-defined requirements can help candidates better understand whether an opening is right for them, although they won’t eliminate application overload on their own.
Will AI replace recruiters?
AI can automate some recruiting tasks, but hiring still requires human judgment, relationship building, and an understanding of candidates and business needs. Teams should focus on using AI to support recruiters while maintaining appropriate oversight.
Where should a small TA team start with AI?
Start with one repetitive, time-consuming task, such as reviewing job descriptions or coordinating approvals. Define what improvement looks like, test a suitable tool, and measure whether it saves time without reducing quality.
