Harnessing AI & ChatGPT for Hiring: A Holistic Approach

If talent teams are to get on the board anytime soon they need to accelerate learning. And in this part of my journey, I'm exploring AI and Hiring.

What I'm hearing and reading in communities is this:-

AI can't do what I do

AI won't replace me

AI will take all our jobs soon

Does anyone have any uses cases

The list goes on...

It's time to let go of the fear and anxiety and embrace it, I firmly believe if you dont embrace it you will be left behind. AI and ChatGPT in recruitment isn't about removing human recruiters but instead supercharging them. It's about a future where technology and human expertise coalesce to redefine what talent acquisition is and how its perceivd.

Let's start with what it will not do:

No matter how advanced, AI will never replace the irreplaceable: human intuition, empathy, cultural fit discernment, and everything that comes with that.

Instead of viewing AI as competition, it's more constructive to view it as collaboration—a tool to make recruitment more efficient.

Now it's in your tool kit let's look at a few holistic use cases applying marketing and data methodologies:

Marketing

Retargeting: Ever noticed how after viewing a product online, its ads seem to follow you around? That's retargeting in marketing. In recruitment, AI can help "retarget" candidates who might not have been a fit for one role but could be ideal for another. Or, it could remind candidates who started but didn't complete an application to finish it.

A/B Testing: One of the pillars of digital marketing is A/B testing, where two versions of a campaign are run to see which performs better. Talent teams can adopt this methodology using AI. Test two different job pitches or two distinct interview approaches and see which one yields better results. Then pauses, analyse the results and iterate.

Fun fact: Amazon is said to run over 12,000 experiments a year!

Dynamic Content Creation: Marketeers employ dynamic content that changes based on who's viewing it. In recruitment, AI could craft dynamic job descriptions. Depending on the candidate's background and skills, the emphasis in the job description could shift, highlighting the aspects most relevant to them. (having said that - it could be a great product to build for job seekers, instead of adjusting their cv for every job manually or having 5 different CV's.;) )

Segmentation and Personalisation: In marketing, audiences are segmented to the smallest possible identifier based on location, interests, behaviours, and more. This granularity allows for highly personalised campaigns. Imagine using AI to segment your potential candidate pool based on skills, experience, aspirations, and even cultural fit. Instead of a generic recruitment message, each candidate receives a personalised pitch that speaks directly to them, making them more likely to engage. We could go deeper in to content-led journeys but I'll save that for another time.

Data

Deep Data Mining: Think how much data ATS' databases contain!! And so much of it hold vast amounts of the untapped data point. Forget CV's, there's data about communication patterns and interview feedback, and if you add transcripts into the mix you really start to build up a good picture. By deep-diving into this data, you and your team can find insights that wouldn't be obvious at a superficial level. For example, data might reveal that candidates from a particular university or with a specific certification consistently outperform their peers.

Data Storytelling: In the world of data analytics, storytelling is an art and a science. It's not just about presenting numbers but twisting and turning those numbers into a compelling narrative. For recruitment, data storytelling can be an invaluable tool.

Instead of just telling people we had 110 people apply 50 moved to interviews 20 went to 2nd stage 10 passed the test and ew hired 2 people imagine presenting a story that tracks a candidate's journey through the recruitment funnel. Visualisations could highlight where most candidates drop off, or perhaps which stage in the interview process is the most challenging, using feedback loop data, to potentially identify any bias in the process. By framing data within a story, it becomes relatable and actionable and not just based on opinion" or "gut feeling". This will also help build credibility to your internal stakeholders.

Conclusion

So in conclusion, harnessing the power of AI in recruitment is an ongoing journey, not a final destination. Don't get left behind. Start by engaging with experts, attending workshops, and most importantly, keeping an open mind.

If you enjoyed this and want to be part of this change? Come on the journey of getting talent teams in the boardroom