AI in Recruitment: A Powerful Tool — But Not the Whole Solution

Artificial Intelligence is becoming deeply embedded in the recruitment process, particularly in tech. From scanning CVs to analysing video interviews, AI promises faster, more consistent hiring decisions. For time-pressed tech hiring managers, that can sound like a silver bullet.

But the reality is more complex.

While AI offers efficiency, it also brings limitations that, if left unchecked, could see organisations overlook exceptional talent. Not just in terms of diversity — although that’s a significant concern — but also when it comes to softer, more human qualities: cultural fit, emotional intelligence, and potential.

In this article, we explore both the strengths and the shortcomings of AI in recruitment, and explain why a balanced, human-led approach remains essential — particularly for tech teams looking to build long-term success.

The Upside of AI in Recruitment

Used well, AI offers tangible benefits at various stages of the hiring process:

• Speed and Scalability: CV screening that once took hours can now be done in minutes.

• Process Consistency: Standardised filtering helps reduce the variance between how candidates are assessed.

• Data-Led Decisions: Historical hiring patterns can inform future choices and flag high-potential candidates.

It’s no surprise that many in-house talent teams are turning to AI to streamline hiring. But automation doesn’t equal accuracy — and it doesn’t replace human insight.

What AI Can’t See — And Why It Matters

Cultural and Team Fit

Success in a tech role isn’t just about technical skill. It’s about how someone thinks, communicates, and collaborates. AI can assess experience and keywords — but it can’t sense whether a candidate will complement your team’s dynamic or embody your company values.

Human Potential

A great hire isn’t always the one with the perfect CV. Career changers, self-taught developers, or candidates from underrepresented backgrounds often bring fresh perspectives and drive — but may not tick every traditional box. These are the people AI can easily filter out.

Emotional Intelligence

Traits like empathy, adaptability, and leadership potential are difficult to quantify — yet they’re often what define high performers. Algorithms, no matter how advanced, struggle to assess the nuance of soft skills that emerge in conversation, not code.

Motivation and Intent

Understanding why someone wants a role is just as important as whether they’re qualified for it. AI doesn’t capture personal drivers, career goals or values alignment — all of which shape retention and performance.

The Risk: Over-Filtering and Under-Hiring

There’s a risk that in chasing efficiency, companies actually lose effectiveness. Relying too heavily on AI can result in:

• Overlooked Talent: People who could excel are excluded based on rigid filters or lack of keywords.

• Homogenous Shortlists: A narrow focus on historical ‘fit’ can reinforce existing biases.

• Misaligned Hires: Candidates may look good on paper but fail to thrive within the team.

In short: faster isn’t always better if it leads to missed opportunities or hiring mistakes.

Our Approach: Balancing Technology with Human Insight

At Applause IT, we use technology to support — not replace — human expertise. Our process is built around human-led hiring, ensuring that no promising candidate slips through the net because of a keyword or an algorithmic assumption.

Here’s how:

• In-Depth Briefings: We work closely with hiring managers to understand the culture, the challenges, and the real requirements of the role.

• People-Centred Screening: Every candidate is assessed by experienced consultants who look beyond the CV.

• Tech Where It Adds Value: We use AI tools to handle admin, not decision-making.

• Focus on Fit and Future Potential: We evaluate soft skills, ambition, and alignment with your team — not just technical proficiency.

AI is here to stay, and its role in recruitment will only grow. But for hiring managers in tech, the key is to use it wisely — as a tool, not a crutch.

Because while algorithms can sort data, only people can truly recognise potential.