Can AI open doors to hidden candidates?
This week on Work Is Weird Now, we sit down with Hannah Töpler, CEO of Intrare, as part of our She Shapes AI awards series.
Hannah is one of the brilliant finalists in the Future of Work category.
The hidden talent problem
Intrare is tackling a mismatch that most labour markets quietly ignore.
On one side: companies struggling to fill frontline roles across logistics, retail, and customer operations.
On the other: millions of capable people — refugees, migrants, single parents, LGBTQ+ candidates, older workers — locked out of formal employment and pushed into informal work.
The surprising reality? These groups make up around half the workforce, yet are routinely overlooked.
This isn’t just a social issue. It’s a market inefficiency.
Why hiring systems are broken (and AI made it worse)
Hannah doesn’t sugarcoat it: most hiring systems are deeply biased.
In fact, she shares that candidates from marginalized groups can receive up to five times fewer opportunities than equally qualified peers.
And AI hasn’t fixed this. It’s amplified it.
Because when you train systems on biased data, they don’t neutralise bias. They scale it.
That’s why Intra-A built its own approach from scratch, combining AI with fairness checks designed to actively reduce bias, not just automate decisions.
A different kind of recruitment experience
What makes Intrare stand out isn’t just the matching. It’s the experience.
Instead of forcing candidates through complex platforms, everything happens through WhatsApp:
Sign-up
Training
Coaching
Job applications
Interviews
For candidates who may not be digitally fluent - or who lack confidence navigating formal hiring — this radically lowers the barrier to entry.
It’s not just efficient. It’s human.
AI as an inclusion engine, not a filter
The real shift isn’t technological. It’s philosophical.
Most AI in hiring acts as a filter: narrowing down, screening out, optimising for speed.
Intrare flips that model.
Their system is designed to expand access, helping candidates:
Navigate documentation barriers
Build confidence
Find roles that match their real circumstances (like language level or childcare needs)
And crucially, their AI actively questions its own decisions, for example:
Would this candidate be treated differently if they were a man instead of a woman?
Small interventions like this can fundamentally change outcomes.
From 200 people a year to tens of thousands
Before building AI, Hannah’s team could support around 200 people annually.
Today, they’ve reached over 25,000 candidates, with plans to expand across Latin America and beyond.
That’s the unlock AI made possible: not just efficiency, but scale with intention.
The bigger tension: AI and inequality
Hannah is optimistic about AI, but not blindly so.
Her warning is sharp:
If we ignore bias → inequality accelerates
If we focus only on automation → opportunity shrinks
If value concentrates → society destabilizes
But there’s another path.
AI could help us:
Work less
Be more productive
Build fairer systems
The question is whether we choose to design for that outcome or drift into something else.
So, can AI open doors?
Yes, but not by default.
It depends on who builds it, what data it learns from, and whether we’re willing to challenge the systems we already have.
Because left unchecked, AI will mirror the world as it is.
Used intentionally, it can help reshape it.
This episode is for anyone thinking about the future of hiring, the risks of AI bias, or what it really takes to make work more inclusive at scale.
Because the future of work isn’t just about efficiency.
It’s about who gets in.
Learn more:
Find Hannah Töpler on LinkedIn
Learn more about Intrare
