Tech recruitment is easy with AI tools, or is it?

You can go it alone, but…

You may miss top candidates who don’t have the right keyword-optimized LinkedIn profile.

You may miss candidates who purposely avoid LinkedIn because of saturation.

If hiring outside your country, you may not be aware of inflation and currency trends or local labor regulations.

You may not have the ability to distinguish fraudulent from real candidates.

You might not have the network that can introduce you to the best candidates.

You may not know which company announced layoffs where candidates are about to become available.

You may not know which certificates are the most relevant for the required skillset.

You may not be able to tell if candidates are cheating by using AI in real-time that provides them with the optimum answers.

You may not know how to run background checks legally and effectively.

You may give short shrift to reference checks when, in fact, they are absolutely vital and mostly badly managed.

You may not know the legal nuances about what interview questions may be litigious.

You may not have heard of “job hugging” and how to address it.

You may not know whether to post salary ranges (or not) and what impact this has on candidates.

You may not know how to minimize bias in the recruitment process.

You may not know why you received 7,941 applicants and how best to filter them.

You may not know how many rounds of interviews are the norm for your industry and the tolerance of top candidates.

How difficult can it really be?

We have over 115 touch points in each recruitment cycle, so you don’t have to.
Trust the process.

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Why modern tech recruitment is more complex than ever

Hiring for technical roles used to be about posting a job and selecting from applicants. Today, things are decidedly more complex.

For one, 76% of IT-focused employers worldwide say they are struggling to find skilled tech talent.
Additionally, data shows that more than 86% of companies believe hiring technical talent is challenging.

And when you factor in AI tools, the recruitment process becomes even more layered: about 73% of companies use AI-powered candidate screening, and 68% of organizations implement skill-based hiring.

Recruitment is no longer simply about finding a developer or engineer; it’s about navigating regulatory complexity, global salary dynamics, diverse candidate pathways, and very high expectations for speed and quality.

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Why using AI alone doesn’t solve everything

Yes, AI tools can help automate many facets of recruitment: parsing resumes, ranking candidates, and scheduling interviews. The global market for AI recruitment is projected to grow from $661.56 million in 2023 to around $1.12 billion by 2030.
But there are caveats:

While 87% of companies now use AI in some part of their recruitment process, 35% of recruiters worry AI may exclude candidates with unique skills or unconventional backgrounds.
Studies suggest that a company’s recruitment cycle may incorporate between 40 and 134 touch points, depending on complexity.
Despite the tech, major issues remain like “ghosting” (where candidates or companies vanish mid-process), misleading job postings, and a lack of transparency. For example, over 53% of candidates say they encountered misleading hiring practices.

So if you lean entirely on AI tools and assume everything else is handled, you might miss the nuances that decide whether a hire succeeds or fails.

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What it takes to truly excel in tech recruitment

Aside from tools and automation, the following capabilities are critical:

A strong network and market insight: knowing which companies are hiring or laying off, which regions are hot, and what inflation or exchange rate dynamics matter.
Rigorous verification processes: distinguishing real from fraudulent candidates, performing background checks, legal screening, and reference checks are done well.
Understanding global labor and regulatory contexts: for example, when hiring in LATAM or remotely across borders.
Awareness of emerging skills trends: skill-based hiring is rising (versus degree-based), and many candidates may be using AI tools themselves in interviews.

According to a large study, in AI roles, the wage premium for skills exceeded that for degrees, and mentions of degree requirements declined by 15% in some sectors.

Efficient process design: many companies measure “time to fill”, “time to hire”, applicant abandonment rates, and candidate experience scores. E.g., tracking these metrics can reveal where your pipeline is leaking.
Bias mitigation and inclusive hiring: Reliance on automation might increase bias if not managed properly.

What we do differently at Netmidas

At Netmidas we’ve built a model that acknowledges all of this complexity, and we manage over 115 touch points in each recruitment cycle, so our clients don’t have to deal with it all themselves.
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Here’s how we approach it:

We combine AI and automation with human expertise, market insight, and strong networks.
We source not just based on keywords and resumes, but on market signals, passive candidate behaviour, and global context.
We verify, vet, and onboard with a full legal and logistic framework, especially when hiring across borders.
We track the right metrics throughout, so we don’t just fill a role, we optimise the process.
We focus on LATAM talent for US and global companies, so we understand regional salary dynamics, currency regimes, labor rules, and cultural alignment.

When you partner with us, you avoid the common pitfalls listed above, and you gain the infrastructure, strategy, and network to hire smarter, not just faster.

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