May 27, 2025

The Impact of AI on Tech Recruitment: Tips for Employers

6 min read

Since the end of another great Techweek, I’ve been reflecting on the amount of AI-related content within the programme this year. While it’s not surprising given the impact of Artificial Intelligence beyond even the tech sector, I’ve noticed that it can be a tricky topic to tackle. There’s so much to dig into, and there are so many grey areas in terms of its use, that even just mentioning the subject of AI in general can be a bit polarising!

But at the end of the day, it’s hard not to talk about AI when it seems so ubiquitous. This was definitely the case when I attended Techfest in Christchurch. It was like the elephant in the room – we had to discuss it because we couldn’t escape the fact that nearly every person there had used some form of AI.

With that in mind, I got to thinking about the impact of AI in my own industry: recruitment. Artificial Intelligence is redefining tech roles, and reshaping teams and organisations across New Zealand. Rather than replacing humans (which was, and in some cases still is, a valid concern), we’re seeing it change how we work instead. So what are the impacts for tech employers, especially when workforce planning? Here are my thoughts and a few tips and advice.

 

Adapt Your Workforce Planning

Workforce planning used to be based on the assumption that job roles were relatively fixed and predictable. It focused on headcount forecasting, job classifications, and filling vacancies in a structured way.

But over time, business environments have become increasingly changeable, and expecting success with that more ‘traditional’ workforce planning approach is not very realistic anymore.

Today, AI is accelerating the evolution of tech jobs in ways that can make static job descriptions feel outdated before they’re even released. For example:

  • Data Analysts and Scientists: These roles used to be focused on data cleaning and preparation, but now AI tools are being increasingly used for automation, effectively shifting the focus more to strategic interpretation and insight generation.
  • Software Testers: Many repetitive, previously manual aspects of testing are being replaced with AI-driven automations, enabling testers to move into quality strategy and systems thinking roles.
  • IT Support Analysts: Routine troubleshooting can now be handled by AI-powered chatbots or diagnostics, pushing support roles toward more complex issue resolution, and enhancing user experience.

Recent reports suggest generative AI could redefine over 40% of all common work activities within the next few years. That’s crazy right? Nearly half of all common tasks are expected to change! I think that really helps demonstrate why a classic workforce planning approach – one that typically operated on a three-to-five year horizon, sometimes even longer – is almost obsolete.

 

What to Consider When Hiring

At Absolute IT, we’ve been discussing the rise in the relevance and value of soft skills in the tech sector for a number of years, and with the rise of AI, these skills are now more necessary than ever. As AI becomes embedded in the tools your team use, the ability to learn, adapt, think creatively, and solve problems, is hugely important. For employers, this means considering:

  • Hiring for AI literacy across all tech roles. A Harvard Business Review article notes that companies who proactively develop AI literacy across their workforces are better positioned to innovate and retain high-performing teams.
  • Putting as much value on soft skills, such as problem-solving and learning agility, as you do on coding languages or database knowledge.
  • Rewriting job descriptions to include these essential capabilities: curiosity, critical thinking, communication.

 

Build AI Capability in Your Leadership Team

It’s a common scenario in mid-sized or larger tech organisations: senior leaders are no longer ‘on the tools’, and in contrast, all the enthusiastic young grads are already integrating AI into their daily workflows. The issue is that this can lead to a lag in the understanding and adoption of AI at the leadership level. If your people managers don’t understand how AI is being used, or how it could be used, then they can’t support it, scale it, or lead change effectively. To tackle this, here are some ideas:

  • Audit AI literacy at the leadership level.
  • Invest in short, focused AI training for non-technical leaders.
  • Ensure emerging leaders, especially those from internal mobility, are upskilled before they step into decision-making positions.

 

Build AI Capability Across Your Organisation

More on the topic of upskilling: A 2024 report from BCG reinforces the challenges of getting tangible value from AI, with data showing that only 26% of companies surveyed had the capabilities to generate value. Developing capability across your organisation needs to be seen as an essential, ongoing commitment, because the pace of change is just too fast otherwise! When planning your workforce, a good place to start is by identifying:

  1. Which parts of your tech stack are adopting AI fastest?
  2. Which roles are at risk of skill redundancy? (This month/quarter and year)
  3. Where do you need to build new capability pathways internally?

In New Zealand, some tech employers are already running internal micro-learning sprints, allocating their teams time for experimentation, and bringing in external advisors to support AI tool integration into product, dev, and infrastructure teams.

 

Review Your Hiring Processes

Of course, all of the above means consideration on the recruitment side of things too. If your hiring process hasn’t changed in the last few years, it might not be assessing candidates for what matters.

AI is altering the skills that are needed, but also how candidates present themselves. We’re seeing a huge increase in Chat GPT-assisted CVs and cover letters, and as candidates get more savvy at using AI, it’s becoming more difficult to spot, making it harder to evaluate authenticity. Here are some ideas for how to deal with this challenge:

  • Focus more on practical assessments and scenario-based interviews.
  • Ask about specific AI tools used in prior roles, e.g. What was used, how, and what were the outcomes?
  • Be alert to over-polished applications, and look for depth in how candidates talk about learning and adapting (i.e. not just surface-level observations, whi).

You might also need to reframe how you position your roles. Candidates skilled in AI will want to know: Will I be empowered to use it? Will I get to lead or experiment with AI-powered solutions?

 

A Positive Attitude is a Competitive Advantage

Our former PM has some thoughts on this topic, calling for a shift in how we talk about AI: from fear, to opportunity. She notes that jobs won’t disappear overnight, but they will be redefined, and we’re better served by embracing that reality. In recruitment and workforce planning, this mindset shift can be the difference between attracting top talent, or losing them to competitors, who are faster to adapt.

I’d recommend encouraging your people managers to:

  • Talk openly about AI as part of team culture.
  • Invite experimentation and learning.
  • Remove stigma around using AI tools in day-to-day work.

 

Let’s Get Started!

With all this in mind, the conclusion I’ve come to is this: AI isn’t going away, and it’s evolving fast. That means we can’t wait for the perfect ‘how-to’ guide for advice on adapting, but we can take steps towards building an AI-ready workforce.

As for the people out there wondering, “What about me as a job seeker/employee?”. Don’t worry, I’ve got some ideas! Look out for part 2 of this blog coming soon…

And as always, if you need help building a hiring strategy or workforce plan, I’m here to help – get in touch.

 

Lucy Graham
Senior Consultant
I enjoy the buzz of the ever-changing technology world and creating a trusted connection with my candidates and clients.