5 steps to creating a best-in-class early career candidate experience in the age of AI

11/03/2025

Artificial intelligence is reshaping the recruitment landscape at an unprecedented pace. With 88% of students and recent graduates regularly using AI tools, and 86% describing themselves as proficient in using AI, employers must rethink how they recruit and engage talent in this new environment. But while AI can enhance efficiency, it also presents challenges—candidates can now ‘hack’ traditional assessments, and the risk is not just in the integrity of the process, but also higher renege and attrition rates.

So, how can organisations create a best-in-class emerging talent recruitment process in the age of AI? Eli Onboarding and Arctic Shores shared a practical, experience-led approach to ensuring that AI complements, rather than compromises, the recruitment process. The five key take-aways were:

Provide AI guidance

To navigate AI’s growing role in hiring, organisations must update their career sites (and internal comms) to give clear guidance on AI use. This means:

Providing candidates with guidelines on good use and bad use of AI in their applications (see the Arctic Shores templates which have been used by the likes of Monzo, HMRC and others).
Being transparent on where and how AI is used by your organisation in the recruitment process. Candidates are just as worried that they will be rejected by an AI algorithm without human oversight as they are of how to use AI themselves.

Rethink the recruitment process

Psychometric assessments and video interviews have become a staple in hiring. However, candidates increasingly report feeling disconnected and uncertain about how technology determines their outcomes. To counter this, organisations should:

Design a process where candidates can use AI tools sensibly to level the playing field while not opening the door to ‘bad AI’ behaviour.
Ensure human oversight in automated filtering so that any decision is based on a recruiter determined set of criteria and not a black box algorithm (however ethically designed that black box might be!).
Look at online tools that use tasks rather than language to assess candidate capabilities and suitability. CVs and text-based application forms are highly vulnerable to AI tools to ‘enhance’ candidate capabilities.

Reduce dropout and attrition rates

With 57% of students willing to reject an accepted offer if a better one arises (Bright Network, 2024), the cost of poor candidate experience is high. Eli Onboarding’s data shows that experience-led onboarding can halve dropout rates and reduce attrition by 20%, saving businesses significant costs while improving engagement.

Address the impact of ‘Delayed Adulthood’ on employment readiness

Young people are taking longer to reach traditional milestones than previously – they’re reaching financial independence, buying homes, securing employment all much later in life. This, coupled with increasing neurodiversity in the workforce, means early career candidates require more support than ever. Employers can bridge this gap by:

Providing pre-learning and training before day one and using the time between offer acceptance and start date to do so.
Creating personalised content that builds understanding of the company’s culture and values before day one.
Ensuring managers are equipped to deliver an engaging onboarding experience.

Ensure a ‘golden thread’ from application to onboarding

The best candidate experience will be one where best-in-class solutions have been seamlessly integrated to measure what matters in an AI resilient and friendly experience. By guiding candidates clearly, redesigning assessments for robustness, and strengthening onboarding, organisations can make AI a tool for inclusion and engagement rather than an impersonal barrier.

Embedding a ‘golden thread’ of transparency, support, and human connection throughout the hiring journey, employers will attract and retain top talent in an AI-driven world.