AI Is Back in HR Tech — But We’ve Been Here Before
There’s never been more optimism in HR technology than right now. Every week, I meet founders building AI recruiting tools that promise to change how hiring works — and honestly, I’m excited for them.
But before we get too high on the hype, let’s pause for perspective.
We’ve seen this movie before.
Back in 2013, machine learning and natural language processing (NLP) were supposed to kill the résumé, automate screening, and make recruiters “more human.” CFOs expected cost-per-hire to fall dramatically.
That didn’t happen.
A decade later, hiring is still slow, expensive, and frustrating for everyone involved — recruiters and candidates alike.
After more than ten years building in this space, here’s what I’ve learned about what went wrong the first time and how AI in HR tech can finally deliver on its promise.
1. Don’t Make People Change How They Work
The first rule of adoption: if your tech requires users to change behavior, it will fail.
You can build the most advanced AI recruiting platform in the world, but if recruiters need to log into a new tool or abandon their existing workflow, it’s dead on arrival.
Integration is everything. Your product needs to plug seamlessly into the ATS, CRM, and communication systems teams already use. Enterprise recruiting operations are complex — if your platform disrupts the flow, it won’t get used.
This isn’t about “training users.” It’s about respecting how work actually happens. The most successful AI products in HR will be the ones that disappear into the workflow.
The more invisible your AI feels, the faster it scales.
2. Integrations Are the Whole Game
Every startup claims, “We integrate with all major systems.”
But anyone who’s worked with enterprise applicant tracking systems (ATS) knows that every implementation is unique — custom workflows, schemas, permissions, compliance rules, and IT policies.
Even “simple” integrations can take months.
If your AI recruiting product can’t go live with API credentials and minimal IT involvement, you’re already behind.
The real innovation in HR tech isn’t just in building smarter AI models. It’s in designing the infrastructure that makes those models usable across the messy, fragmented systems enterprises rely on.
That’s where trust and adoption are earned.
3. The Job Seeker Is the Customer
This should be obvious, but it still isn’t.
Candidates aren’t data points — they’re the customers of your hiring experience.
Too many systems still make people click through multiple redirects, upload PDFs, and complete endless forms just to apply.
The future of candidate experience is about frictionless design:
- One step, one flow, one good interaction
- No résumé uploads unless they add value
- Transparent next steps and conversational interfaces
When you treat job seekers like customers, not inputs, the entire talent ecosystem wins.
A great candidate experience doesn’t just improve conversion — it builds employer brand equity and drives talent acquisition efficiency.
The Hard Truth: Simplicity Wins
We don’t need another “AI for hiring” pitch deck. We need products that actually work inside the complex, often chaotic world of enterprise HR.
The companies that get this right — that build for recruiters’ real workflows and respect the candidate journey — will define the next decade of HR technology.
Everyone else will just add to the noise.
AI Can Finally Make Hiring Better — If We Let It
AI can absolutely make hiring better. But it will only succeed if we build with humility — respecting the systems, workflows, and people that make hiring work today.
2026 may well mark the inflection point for AI in recruiting. The winners won’t be the ones chasing buzzwords; they’ll be the ones who make technology fit naturally into how people hire.
