Workforce skill gaps are becoming one of the biggest challenges for organisations trying to grow, adapt, and remain competitive. Technology is changing jobs faster, business requirements are evolving, and many organisations are struggling to find people with the right combination of technical and soft skills.

At the same time, hiring teams are often dealing with large candidate pools, limited recruitment resources, and pressure to fill critical positions quickly.

Artificial intelligence can help address this challenge—but not simply by automating recruitment.

The bigger opportunity is to use AI to understand skills more effectively, identify where gaps exist, and connect organisations with the people who have the capabilities they need.

What Is a Workforce Skill Gap?

A workforce skill gap occurs when an organisation does not have enough people with the skills required to achieve its current or future business objectives.

The gap can take several forms.

An organisation may lack technical expertise in areas such as data analysis, cybersecurity, software development, or AI. It may also have shortages in communication, leadership, problem-solving, customer service, or other transferable skills.

Sometimes the issue is not a complete absence of a skill. Employees may have the foundation but need additional training or experience to reach the required level.

This distinction matters because the solution to a skill gap isn’t always hiring.

Sometimes the right answer is upskilling. Sometimes it is internal mobility. Sometimes it is external recruitment.

AI can help organisations make that decision with better information.

Start With a Clear Understanding of Required Skills

The first step in closing a workforce skill gap is understanding what the organisation actually needs.

Traditional job descriptions often focus heavily on responsibilities and experience requirements. However, they don’t always provide a structured view of the capabilities needed to succeed.

AI can help analyse job descriptions and identify the skills, competencies, and requirements associated with a role.

For example, a job description for a customer success position might indicate a need for:

• Customer communication
• Relationship management
• Problem-solving
• Product knowledge
• Data interpretation
• Conflict resolution

Turning this information into a structured skills profile can help recruiters and workforce planners understand what they should actually be looking for.

It also creates a stronger foundation for assessing candidates consistently.

Identify Skills Hidden in Resumes

Resumes contain valuable information, but skills are not always presented in a standardised format.

One candidate might describe a skill explicitly. Another might demonstrate the same capability through previous responsibilities or projects.

AI-assisted resume screening can help identify relevant skills and experience across large numbers of applications.

Rather than relying solely on job titles or keyword matching, organisations can look at the broader relationship between a candidate’s experience and the skills required for the role.

This can help recruiters identify candidates with transferable or adjacent skills who might otherwise be overlooked.

For organisations facing critical talent shortages, that can significantly expand the potential talent pool.

Assess Skills Beyond the Resume

A resume tells an organisation what a candidate has done. It doesn’t always demonstrate what they can do.

This is where assessments and interviews become important.

AI-powered assessments can help evaluate specific capabilities relevant to a role, while structured AI interviews can gather additional evidence through candidate responses.

For example, an organisation hiring for a customer-facing role may want to understand how candidates approach difficult customer situations.

A structured interview question could ask:

“A customer is frustrated because a problem has not been resolved after several attempts. How would you handle the conversation?”

The response can provide evidence about communication, empathy, problem-solving, and judgment.

The goal is not to replace human evaluation. It is to give recruiters more relevant information to work with.

Look for Transferable Skills

One of the biggest opportunities in addressing skill gaps is identifying transferable skills.

A candidate may not have the exact job title or industry experience an organisation initially expects but may possess many of the underlying capabilities required for success.

For example, someone with experience in hospitality may have strong customer service, communication, problem-solving, and conflict-resolution skills that could transfer to a customer success role.

AI can help organisations analyse experience and identify these relationships between existing capabilities and new role requirements.

This can encourage organisations to hire based on skills and potential rather than relying too heavily on traditional career paths.

Support Internal Mobility and Upskilling

Not every workforce skill gap needs to be solved through external recruitment.

Organisations may already have employees with many of the required capabilities.

AI-powered skills analysis can help identify where employees’ current skills overlap with the requirements of other roles.

This can support internal mobility and career development.

For example, an employee may have strong analytical skills and business knowledge but lack experience with a specific data platform. Rather than hiring externally, the organisation could provide targeted training and move that employee into a new role.

This approach can be valuable because organisations retain institutional knowledge while giving employees opportunities to develop.

Connect Skills Data With Workforce Planning

Skills intelligence becomes more powerful when it is connected to workforce planning.

Instead of asking only, “How many people do we need?”, organisations can start asking:

What skills will we need, where do we have them today, and where are the gaps likely to emerge?

This creates a more strategic approach to workforce planning.

AI can help analyse information from job descriptions, employee profiles, recruitment data, assessments, and other sources to identify patterns.

For example, an organisation preparing to introduce new technology may discover that it has enough employees overall but lacks specific technical capabilities.

That insight allows leadership to make more informed decisions about hiring, training, and resource allocation.

Make Recruitment More Skills-Focused

AI can also help change how organisations define and evaluate candidates.

Instead of starting with a long list of credentials, recruiters can begin with the capabilities that genuinely matter for the role.

This can make hiring more flexible.

A candidate may not have every preferred qualification but could demonstrate strong performance in the core skills required for the position.

Skills-based hiring can also help organisations access broader talent pools, particularly when traditional experience requirements unnecessarily exclude candidates with relevant transferable capabilities.

AI doesn’t make the hiring decision. It can help recruiters identify and organise the evidence needed to make that decision.

AI Should Support Human Judgment

There is an important limitation to remember.

Skills cannot always be reduced to a score.

A candidate’s career history, motivation, potential, context, and ability to learn can all matter. AI-generated recommendations or assessments should therefore be treated as decision-support information rather than automatic hiring decisions.

Recruiters and hiring managers should remain responsible for interpreting results and considering the wider context.

Organisations should also regularly review their AI-assisted processes to ensure that the skills being assessed remain relevant and that candidates are evaluated consistently.

Building a Skills-First Workforce

Closing workforce skill gaps is not a one-time exercise.

As technology, customer expectations, and business strategies change, the skills an organisation needs will change too.

AI can help organisations create a continuous skills cycle:

Understand required skills → Identify existing capabilities → Assess candidates and employees → Identify gaps → Hire, develop or redeploy talent → Measure outcomes → Update skills requirements

This moves organisations away from reactive hiring and toward more proactive workforce planning.

Instead of waiting for a critical position to become vacant, organisations can anticipate capability gaps and start developing or sourcing the required skills earlier.

The Future of Workforce Planning Is About Capabilities

The most important shift is moving from thinking primarily about jobs to thinking about skills and capabilities.

Job titles can change. Organisational structures can change. Technology can make some responsibilities obsolete while creating entirely new ones.

Skills provide a more flexible way to understand what an organisation needs.

AI can help bring this skills-based approach into recruitment, assessment, workforce planning, and employee development.

It can help organisations identify relevant capabilities, uncover transferable skills, assess candidates more consistently, and understand where their workforce may need additional investment.

But technology is only part of the solution.

The organisations best positioned to close critical skill gaps will be those that combine AI-driven insights with strong workforce planning, effective learning programmes, internal mobility, and thoughtful human decision-making.

The objective isn’t simply to hire more people.

It is to build a workforce with the right capabilities—both today and for what comes next.

Interviewer.AI is a purpose-built technology platform designed to help recruiters. We also partner with universities to support admissions and coaching, enabling them to use technology to better assess potential, skills, and readiness. Our mission is to make hiring more equitable, explainable, and efficient by enabling teams to screen candidates early and shortlist those who best meet role-specific criteria.

Schedule a demo today to learn more about how AI interviews can help.

Gabrielle Martinsson is a Content Writer at Interviewer.AI. She’s a tech geek and loves optimizing business processes with the aid of tech tools. She also loves travelling and listening to music in her leisure.