AI in Recruiting: What It’s Actually Doing Today and What It Could Unlock Tomorrow

The future of work is undoubtedly global, and that means Talent acquisition (TA) teams like mine are operating in a much bigger sandbox. This opens up incredible opportunities to find top talent anywhere in the world.

At Deel, we hired 2,700 people in 2024. This year, we are forecasting around 1.8 million applications, up from 1.3 million last year. When you’re operating at our global scale, the biggest challenge is not access to talent. It’s handling volume and keeping focus. Without the right tools, it’s simply not possible to consistently find and connect with the right candidates.

That’s why AI isn’t a futuristic concept in talent. It’s already here. But the question isn’t whether to use AI in recruiting. The real question is how we use it well without losing what makes hiring human.

What AI in recruitment actually means today

There’s a lot of talk about AI “replacing” recruiters. But, in my opinion, AI’s most impactful use today is pragmatic and people-centric.

The most mature and widely adopted version of AI in recruiting today is assistive AI. Unlike selective AI (which would make hiring decisions for you and is currently complex due to legislation) or predictive AI (which is still evolving), assistive AI is all about helping recruiters do more, faster, and more effectively.

Assistive AI allows you to identify the best candidates, no matter where they are in the pile

At a global scale, assistive AI helps recruiters sort through thousands of resumes and surface the best matches, not just the first ones that come in.

For example:

• AI can scan and index resumes from massive databases based on obvious job criteria (listed in job descriptions) and the “unspoken” ones—like competencies, values, or team fit.
• It can highlight the most promising candidates even if they applied 400th out of 400. That means the best person for the job doesn’t get overlooked just because they weren’t first in line.

These features is transformative in high-volume environments. It expands our reach to the entire talent pool, not just the first page of applicants.

AI creates new visibility into job requirements

One of the most powerful—but often overlooked—impacts of AI in recruiting is the way it helps us reflect insights back to the business.

With AI-driven insights, talent teams can now say:

“You’ve had 400 applicants for this role, and not a single one meets all of your must-have requirements. We need to refactor the job description or adjust expectations.”

Instead of silently filtering out candidates based on impossible criteria, we can push helpful, data-backed feedback upstream. As a result, hiring teams can course-correct earlier and design better, more inclusive job specs from the start, resulting in better candidates sourced faster.

And it works in both directions: if your requirements are too broad and too many candidates are flooding in, AI can flag it and help you tighten the criteria to target what you actually need.

Efficiency in recruitment only matters if you reinvest it

If you use AI just to save time or reduce costs without a clear plan for how to reinvest that time, you’re missing an opportunity.

Recruitment is, at its core, a human contact sport. People join companies for deeply personal and emotional reasons: the people they meet, a sense of purpose, or the belief they can grow. AI should never replace the human part of hiring. It should free recruiters up to spend more time on those moments of human connection.

Anecdotal evidence suggests that people using AI aren’t necessarily working less. In fact, they’re often doing more. The time saved—usually 1–2 hours a day—is just getting filled with the next task. That highlights the need for intentional design: AI doesn’t automatically lead to better work-life balance or productivity unless leaders are deliberate about how time is used.

When AI makes the early stages of hiring—resume review, sourcing, screening—more efficient, we should repurpose that time to:

• Build stronger candidate relationships
• Offer a more thoughtful, transparent interview experience
• Communicate timelines and expectations more clearly

Recruiters should use every minute they get back to make the human parts of hiring more intentional and meaningful.

Transparency is the missing link

Despite all the progress we’ve made, there is still something holding many companies back: a lack of communication.

Even inside companies actively using AI, not everyone knows where or how it’s being used. That uncertainty creates anxiety, skepticism, and resistance. Closing that communication gap is key.

If you can simply say, ‘Here’s where we’re using AI, and here’s where we’re not,’ that transparency builds trust. It also demystifies the technology for employees and candidates alike.

AI adoption isn’t just a tech problem. It’s a change management challenge. And clarity is one of the most powerful tools too manage it.

Looking ahead: My four predictions for where AI in recruitment is headed

Based on my experience leading global hiring at scale, here are my top predictions for what AI in recruitment can unlock in the upcoming years:

1. Smarter and broader resume and database reviews

AI will help recruiters index and search hundreds of thousands—if not millions—of applications and past candidates. It will be able to leverage keywords present in resumes and infer skills and competencies, leveraging information across external platforms.

For example, even if a CV doesn’t explicitly list a programming language, AI could infer it based on job titles, employer names, or activity on public platforms like Stack Overflow. That means your internal candidate database becomes exponentially more valuable—not just a digital filing cabinet but a living source of talent.

2. Data-driven internal mobility

AI will give organizations visibility into internal skillsets, enabling better internal movement, career growth, and workforce optimization.

AI can surface patterns like:

• People with X background tend to thrive in Y team
• Skills from Department A map surprisingly well to success in Department B

Such insight lets companies design enablement programs and internal moves with real data, which is instrumental during organizational redesign, workforce optimization, upskilling efforts, or retention plays.

3. Smarter interviews and continuous feedback loops

Recruiters often describe interviews as a “black box.” Did we ask the right questions? Did we assess skills consistently? Were the right signals captured?

With AI-powered transcription and analysis tools, we’re beginning to unlock feedback loops that connect interview content to on-the-job performance.

As a result, AI will enable:

• More consistent hiring practices
• Stronger signal-to-noise ratios in interviews
• Better alignment between role expectations and reality

It also gives recruiters and hiring managers data they can use to refine their approach and improve the quality of hires over time.

4. More strategic TA planning and headcount forecasting

AI won’t just support individual hiring decisions—it will reshape how TA contributes to business strategy.

With better insights, TA leaders will be able to answer questions like:

• What’s our conversion rate from application to offer by region?
• Which job descriptions result in too many underqualified (or overqualified) applicants?
• How should we reallocate recruiter bandwidth based on bottlenecks?
• Where should we spend more (or less) on advertising and sourcing?

This kind of visibility elevates TA from tactical executor to strategic advisor. That shift will be a competitive advantage in a world where workforce planning moves fast.

The bottom line: Use AI in a human way

Using AI in recruitment isn’t a question of if but how to do it intentionally. As HR leaders, we have a critical role to play in advocating for AI tech that strengthens the human connection.