The Skills Standoff: How Misaligned Perceptions are Breaking Hiring

The global labour market faces an interesting paradox. Nine in ten workers are confident in their skills and experience, but two-thirds of employers are concerned about finding talent with the right skills. This mismatch in expectations comes during a time when AI is transforming work and technology at an unprecedented pace, with both businesses and employees rushing to catch up.

With talent listed as the number one challenge to innovation, organizations hoping to scale, innovate, or go global in the near future must pay attention. Ending the standoff will require a shift in how we think about skills, and how we approach learning and development.

Diagnosing the skills standoff

This lack of understanding, on both sides, is largely due to the shifting skills landscape. While workers are confident that they have the skills necessary for jobs as they are currently, employers are already looking for the skills of the future. The World Economic Forum estimating that 39% of workers’ core skills will change by 2030. This is a less seismic shift than the estimate made in 2020 (57%) as the world shifted to predominantly remote and hybrid work, but is significant enough to be disruptive.

Traditional education is unable to keep up with the pace of this change, perhaps leaving graduates with high expectations of their prospects, but without the skills employers want. Those learning skills through other education systems don’t gain much of an advantage thanks to credential inflation, with MBAs, micro-courses, bootcamps being perceived as less valuable. This leaves applicants feeling confident in abilities that are all but invisible to recruiters.

Employers may also have unrealistic role requirements as a hedge against uncertainty. One of the ways this manifests itself is a lack of confidence in transferability, leading recruiters to narrow their search to candidates with experience in the same industry or niche. Whereas workers assume domain or interpersonal skills translate seamlessly into new contexts.

AI literacy is fast becoming a must-have for new hires, but AI education is lagging behind the need. While 61% of of employees have access to AI training, only 23% report having access to comprehensive programs. And only 3% of employers believe that universities adequately prepare candidates for AI skills. So while applicants are increasingly listing AI skills, employers don’t have the same trust in their capabilities.

Risks and consequences for AI adoption and global teams

Without intervention, this widening gap leaves applicants wondering why they’re not getting hired, and employers spending more time trying to find the right talent.

If hiring filters don’t match real skills, recruiters can reject viable candidates. This risk is amplified by the increasing application of automation in the early stages of hiring. Combine a lack of human oversight and a list of objective requirements that don’t mesh with reality, and you get a system which doesn’t source top talent.

In borderless hiring, the gap is further widened by discrepancies in education systems and credentials. When applicants come from such a variety of backgrounds, comparing skills and capabilities becomes more complicated, intensifying the standoff.

The risk is not limited to hiring. Existing employees who believe they are undervalued may disengage. On the other side, employers who don’t understand the value of their employees may be overlooking opportunities for promotion or internal mobility. Underutilizing talent due to skill uncertainty, in a moment when companies are hesitant to add headcount, can delay projects and strategic initiatives. This cripples innovation, and halts the progress of things like AI adoption.

Bridging the perception gap

The skills shortage is currently the number one barrier to business transformation, and bridging the perception gap is imperative.

• Invest in AI training: Prioritize the skills every employee needs, regardless of function, such as AI literacy, prompt engineering, and data protection. Your goal should be to ensure that all employees are able to use AI tools sensibly, safely, and efficiently.

• Joint calibration exercises: Your feedback cycles shouldn’t only focus on output and performance metrics. To foster a culture of continuous learning, skills include joint calibration exercises to map out current skills and competencies. This makes it easier to see what’s needed for promotion or progression.

• AI/data tools for real-time diagnostics: Adopt internal capability mapping platforms or skill intelligence tools to spot gaps. We use Deel Engage to identify skill gaps and development opportunities across the company and at the individual level using tools like skill matrices, 9-box, and bar charts.

• Assessment-driven recruitment: Embrace skills-based hiring, and use project work, micro-assessments, and portfolio reviews to assess candidates over resume headline filters. Find the balance between assessing their core competencies, and their AI literacy. For example, allow them to use AI to complete a take-home task, and then assess how they used it and why. This allows you to measure both their technical abilities and their human judgement, which paints a more realistic picture of their output.

• Cultural narrative shift: Endorse a skills-first mindset across your organization. This can be done practically by providing a discretionary budget for upskilling, bringing in experts to give talks and workshops, and building a library of courses.

• Audit job postings for buzzwords: Check the language you’re using in your job postings, and root out where you’re relying on buzzwords such as ‘self-starter’, ‘driven’, ‘team player’, and ‘passionate.’ The less room for interpretation, the better you represent your organization’s needs to prospective candidates.

Turning the standoff into an opportunity

A pivot to skills-based hiring will help organizations to embrace a more nimble and diverse talent pool, attracting candidates that have the capabilities needed for the future of work. But to build robust pipelines, more is needed.

Where traditional education is falling behind, business who step up by investing in L&D will gain a future-ready workforce. These businesses will be the ones that stay agile, attract top talent, and drive innovation in the AI age.