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Three times in my recruiting career, I’ve seen our industry crack open. First, when job boards arrived in the late 1990s. Then when social media made sourcing infinitely scalable. And now it’s happening again with AI.

But this third wave feels infinitely different. It’s not just new tech; it’s a redefinition of how we work, what recruiters do, and how we deliver value. It’s exciting. It’s messy. And, for many, it’s nerve-wracking.

In late April, I moderated a panel of four incredible talent acquisition leaders:

• Rachel Allen, senior director of talent acquisition at 7-Eleven
• October Ambrose, VP of people partnerships and engagement at Central Health
• Dhiraj Gupta, senior manager of talent acquisition at Amazon
• Tim Wesson, SVP of talent acquisition at IQVIA

Each person was at a different point in their AI journey and what united them wasn’t a shared tech stack or use case. It was something more fundamental: a human-first mindset.

Here’s what we unpacked — and what every TA leader needs to know.

1. Don’t start with the tech. Start with the pain

When 7-Eleven acquired Speedway, Rachel Allen inherited chaos: two tech stacks, conflicting models, and the sudden removal of 400 recruiters. 

Her new brief? Deliver faster, scalable store hiring — with almost no people.

She didn’t go shopping for a shiny AI tool. She diagnosed the problem: missed hires due to slow processes, lack of visibility, and no accountability in store-level hiring. Then — and only then — did her team implement an AI-powered automation solution that now runs 95% of the hiring process.

It worked. Time-to-hire dropped from 11 days to under three. Store managers toggle hiring on or off with a button. The business now makes 120,000 hires a year — and sees a measurable uptick in quality.

Takeaway: AI won’t save you. Solving real problems will. “Before ever introducing the technology,” Rachel told me, “I think we don’t give enough credit to understanding the problem you’re trying to solve.”

2. Efficiency is not the enemy of empathy

October Ambrose works in the healthcare sector, where the stakes are deeply human. Her lens is different. “I’m not looking for speed,” she told us. “I’m really looking for efficiency and relevance.”

For high-volume roles like medical assistants, October’s team is exploring automation to reduce waste and get decisions faster. But for provider roles or tech specialists? White-glove, high-touch service remains essential.

And, for her, there’s another stakeholder: the patient. 

“The North Star is always our patients,” she explained. “It ultimately impacts the quality of care that we provide to patients when we have team members who are engaged.”

Takeaway: AI should never strip the soul from recruiting. Done well, it amplifies it.

3. Think micro: small AI wins everywhere

At Amazon, Dhiraj Gupta isn’t rolling out some monolithic AI solution. Instead, his team uses AI like seasoning: sparingly, but everywhere. From Boolean search support to interview debrief summaries to recruiter-built micro apps on Amazon Web Services — his team has embedded automation across the hiring lifecycle.

And here’s the kicker: Recruiters build many of these tools themselves.

“You know the pain points you are facing on a daily basis,” Dhiraj explained. “Why don’t you build the tool and we’ll give you the technology.” The result? A living, breathing ecosystem of micro-innovations that remove friction and increase recruiter productivity.

Takeaway: Make your culture the platform. Empower recruiters to be builders.

4. Build business cases that speak the CFO’s language

Tim Wesson didn’t mince words: Time savings mean nothing if they don’t hit the P&L. Saving recruiters an hour a day? That doesn’t move the CFO. If that hour doesn’t reduce headcount or increase output, it’s not real.

At IQVIA, 80% of hiring is client-billable. That means faster hiring literally drives revenue. AI’s value? Reducing time-to-bill. Lowering cost per hire. Keeping talent pipelines flowing to accelerate service delivery.

Takeaway: If you can’t draw a line from your AI initiative to revenue or scalable cost savings, rethink your pitch.

5. Change management isn’t a checkbox

Tech doesn’t fail. Change fails.

Rachel didn’t just roll out AI. She took it on tour. Road shows. Feedback loops. Visible pilots. Store leader buy-in on timelines. A dedicated helpline manned by former recruiters. Result? Enthusiasm, not resistance.

They even named their AI assistant Rita — short for “Recruiting Individuals Through Automation.” Store leaders loved her so much they genuinely thought she was real.

Takeaway: Treat your change strategy like a campaign. Win hearts before you roll out tools.

6. Don’t be blind to the bias

Let me tell you a quick story. I was demoing a fun AI tool that turns photos into Pixar-style cartoons. I shared a group image with colleagues. My friend Paul, who’s Black, looked at the image and asked, “What’s missing?”

He wasn’t in it. The tool had rendered everyone but him.

Later, it added Paul — but turned our Asian colleague Black. This is the insidious, unintentional bias AI can carry when the training data isn’t representative. And if it happens in harmless tools, imagine the risk in hiring.

Takeaway: AI decisions are only as fair as the data that feeds them. Trust, but verify. Then verify again.

7. Speed doesn’t kill quality. It unlocks it

There’s a myth that fast hiring sacrifices quality. Every panelist pushed back on that.

At 7-Eleven, cutting time-to-hire increased candidate quality because they got to the best people first. At IQVIA, hiring velocity improved manager and candidate NPS. At Amazon, AI-driven note summaries helped identify “silver medalist” candidates faster, fueling proactive, high-impact hires.

Takeaway: Speed isn’t the enemy. Delay is. 

Move fast and hire well. They are not in conflict like most people think – they’re synergistic.

Final thoughts: The real future — more human, not less

Here’s the biggest lesson I took away from my conversation: The future isn’t humans versus AI. It’s not AI instead of recruiters either. It’s humans plus AI. 

That’s the winning formula.

AI isn’t making recruiting less human. It’s making space for the parts that are most human.

More time building relationships. More insight into what makes a great hire. More ability to tailor experiences. More room for empathy, strategy, and values.

But none of this happens automatically. You need:

• Real business problems
• Strong data and measurable outcomes
• Stakeholder buy-in
• A human-centered implementation plan
• And a culture that rewards experimentation

If you’re in a TA leadership role, this is your call to action. The AI moment isn’t coming — it’s here. But the winners won’t be the ones with the flashiest tools. They’ll be the ones who lead with heart, solve with purpose, and scale what makes recruiting great.

This post was originally published in Johnny Campbell’s Talent Leader Insights Newsletter.

Johnny Campbell is a serial disrupter in the world of talent and HR. As founder and CEO of SocialTalent, the learning platform that helps you drive hiring excellence, he partners with some of the largest enterprises in the world (such as NBCU, Cisco, and CVS Health) to help them future-proof their organizations and build better workplaces.

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