Why Skills-Based Hiring is the Future of AI-Driven Work

AI is changing the world of work faster than academia is able to keep up. Graduates seeking roles in tech, project management, marketing, consultancy, and many other industries find themselves graduating with knowledge that is no longer relevant.

In response, 53% of employers in the UK, and 57% in the US, have already dropped degree requirements from their job postings. However, the results have been mixed, with little to no difference in the number of employees being hired without an undergraduate degree.

In order to truly embrace skills-based hiring and keep up with AI innovation, structural change is needed.

The end of the degree era?

There are, of course, countless fields where higher education is non-negotiable. What’s coming to an end is the arbitrary requirement of degrees as a ‘guarantee’ that a candidate is right for the job. For example, entry-level marketing roles that require journalism degrees, and junior product manager roles that require computer science degrees. Success in these roles actually depends more on practical skills. Ones which evolve too quickly for universities to keep up with.

For employers, arbitrarily requiring degrees leads to a smaller and less diverse talent pool and longer recruitment cycles. There’s also the risk of missing out on skilled talent who followed a less traditional path. A growing number of businesses realize this, which is why 83% of companies in the UK are moving toward or have already adopted a skills-based hiring model, with the sentiment mirrored around the world.

However, there’s a significant gap between the policy of dropping degree requirements and the actual hiring of non-degree candidates. According to research by Harvard, non-degree hires have only increased by around 3.5% on average across US employers. This is despite college enrollment in the US declining. This suggests that, among other factors, companies may have updated their job postings, but they haven’t fundamentally changed their hiring practices.

A practical approach to skills-based hiring for an AI-assisted workplace

So if dropping the degree requirement isn’t enough, what does a switch to skills-based hiring actually look like? It means going beyond the recruitment stage, gaining a new understanding of what skills your business really needs, and transforming your culture into one of continuous learning.

1. Identify core skills for your organization

Start by identifying the core skills and attributes required for your organization. These can be tied to your values, your mission, or working model, and should be soft or attitude-based. For example, in a remote-first setting, you need teams who are well-organized and accountable. At Deel, we prioritize adaptability and motivation, which are vital for moving at Deel speed as our organization grows.

As AI plays an increasingly important role in your employees’ day-to-day, consider choosing core skills that complement AI-driven work. This doesn’t mean coding or having experience with the specific AI tools in your stack. It could look like basic AI literacy, critical thinking, or problem-solving.

2. Identify skills gaps and audit job postings

Without investing in training, you risk a growing gap between long-time employees who predate your AI rollout and new hires who are already fluent in these tools. Conducting a skills gap analysis will enable you to evaluate where your strengths and weaknesses are, and who needs to be brought up to speed. Once you’ve mapped out skills and competencies across your organization, you can prioritize where you need to upskill and where you need to hire.

With a complete understanding of your skills needs, audit your job postings and the language you use to attract candidates. You’re looking for more than just a lack of degree requirements. You’re looking for an accurate representation of the skills needed for the role and the most important attributes for thriving in your team.

3. Build AI-friendly skills assessments and projects into hiring pipelines

Typically, employers opt to discourage AI use in these assessments, unless the role revolves around AI technology (machine learning engineers, data scientists, etc). They want to see what people’s ‘natural talents’ look like. For the future of work, we need a more balanced approach. If AI tools shape people’s output, you need to understand how adept they are at working with them.

By creating assessments that allow employees to showcase both their human skills and their AI capabilities, we gain a clearer picture of what they’ll really be like on the job. For example, in a software engineering interview, have candidates complete a coding challenge with the help of AI assistants. To keep the focus on their skills and not just proficiency with AI, have them explain their choices and reasoning. This will demonstrate their judgement, critical thinking, and problem-solving abilities, as well as their AI proficiency.

4. Prioritize continuous learning

Learning shouldn’t stop at the point of hiring. Extend your skills-based hiring strategy into a learning and development strategy.

Pair your formal L&D strategy with an informal culture of learning and education. At Deel, our entire library of courses is available through Deel Engage, for any employee to explore topics and skills outside of their wheelhouse. We also encourage teams to run self-led learning sessions to share knowledge.

As we continue to innovate with AI, this continuous learning makes AI a collaborative effort. Leadership and engineering set the policies, create the guardrails, and ensure safety and compliance. And our teams create techniques and workflows that help them in their day-to-day. Not only does this lead to an organically upskilled workforce, but it also increases excitement and enthusiasm for AI, greatly boosting adoption.

By focusing on skills during the hiring process and intentionally providing an environment of learning, we’re building a workforce that is best suited to scale with us and to build the best solutions for our partners.

5. Create internal mobility paths based on skills development

If skills are the basis of hiring, they should also be the basis of growth. Your upgraded learning and development strategy should come with career paths aligned with skill development. Create transparent internal mobility frameworks, allowing employees to understand which skills are needed for roles.

When employees understand their skill set, know which roles are within their reach, and have access to the skills training they need to make a move, you increase internal mobility. This builds a more engaged workforce, lowers retention, reduces hiring costs and time to hire, and improves your employer brand. You become an organization where people learn the skills of the future and can grow in their careers.

The human edge in the AI age

Human skills can never be overlooked or underestimated, even as AI tools become more powerful and take on more tasks. Creativity, judgement, and intuition remain key. By rethinking our approach to hiring and skill development, organizations can better prepare for the evolving future of work.

Gaining a competitive edge lies in cultivating a skills ecosystem, which starts with hiring and is consistent throughout the employee experience. But it has to begin with hiring for ability, and not for pedigree.