A skills-based approach to early career hiring and compensation
This shift towards valuing emerging technical skills alongside traditional development needs creates new challenges for compensation teams.
It's a dilemma Alistair acknowledges doesn't have easy answers yet.
"On one hand, some junior hires may genuinely bring in high value AI skills – the kind of capabilities that companies are willing to pay a premium for,” he points out, “But at the same time, they often will not yet have developed the other critical skills that make someone effective in a team."
"It is one thing to know how to write code or chain together models. It is another to explain what you are doing, why it matters, and how it fits into a wider business or product goal," he explains.
One thing is clear: defaulting to levelling all entry-level candidates at the traditional P1 bottom rung of the career ladder may no longer make sense.
“It might be that they’re a P1 in terms of scope and communication, but a P4 in terms of technical depth,” Alistair suggests.
Renita sees the same challenge. For her, this idea of an employee who is skilled in some areas, but lacking in others, lends itself to a more skills-based approach:
- Review your level framework. Ensure job level definitions reflect the skills that the business actually needs to succeed. If AI integration is business critical, then AI expertise should be a core competency reflected in progression through job levels.
- Recognise expert knowledge where it exists. When hiring, focus on the skills the business needs rather than years of experience. Then, when determining compensation, evaluate their level of seniority for each relevant skillset. If someone brings valuable AI skills but is inexperienced in other areas, their salary band position should reflect that higher level expertise.
- Be transparent about growth areas for all employees. Clearly outline where development is needed for all employees. This is where Renita’s reverse mentoring concept becomes particularly valuable. Younger employees can learn business skills from experienced colleagues to support their development, whilst sharing their own AI expertise with those colleagues to help them progress in this new skillset.
The clarity this brings benefits everyone: job adverts become more targeted, candidates understand their pay and development areas, hiring managers get better-matched applicants, and compensation decisions become more defensible.
"Unclear job ads leading to piles of unfit candidates are the biggest issue I see in hiring," Renita notes. "With a skills-based approach, you can be much more transparent and targeted – we need this AI skill, but if you have less experience on stakeholder management that's fine. It’s so much more efficient."