How AI Can Help You Find Niche Talent & Close Skills Gaps
Organizations today are struggling to find and recruit the specialized talent needed to drive their most critical initiatives. Many of these roles demand niche skills, making the recruitment process more complex and time-consuming.
According to LinkedIn, more than 10% of professionals hired today have job titles that didn’t even exist in 2000 – roles like AI Engineer and Head of AI. By 2030, 70% of the skills used in most jobs will change.
Traditional methods, often relying on generic job descriptions and outdated role definitions, leave businesses with mismatched candidates and inefficiencies in their hiring processes. But there’s a new way forward: a skills-first approach to filling skills gaps, supported by the power of artificial intelligence.
Powering The Hunt For Specialized Talent 🔍
Specialized roles often demand a highly specific skill set that’s not always reflected in standard job descriptions or traditional recruitment pipelines. So how do organizations identify and engage the right talent for these roles? And how do they avoid mismatches that can lead to inefficiencies and delays?
The answer lies in moving away from generic role definitions and embracing a more agile, skills-based approach to filling skills gaps. This strategy allows organizations to define roles based on a deeper understanding of the skills required and, more importantly, match candidates who possess those skills.
The Skills-First Approach: Build A Stronger Talent Pipeline 💪
To tackle the challenge of recruiting specialized talent, organizations must take a step back and rethink how they define roles and engage candidates. You should be asking yourself:
- How do we define skills at our specific company?
- What skills and capabilities exist in my organization today?
- How do we define jobs and tasks, and how do they relate to each other?
- What skills are we missing?
- How are skills “trends” changing in the wider labor market?
Getting to the answers was previously a time-consuming process, with data living in silos, often out of date or incomplete. Today, there are fast and precise ways to truly visualize, holistically, what you have and what you need in terms of skills – and how to plug those gaps.
1. Clarify Role Definitions
Accurate role definitions are the foundation of a successful recruitment process. But traditional role definitions are often too broad, leaving room for ambiguity about the exact skills and qualifications needed.
By leveraging AI, organizations can standardize job descriptions – while also building clear, consistent definitions for specialized roles.
AI can analyze a wide range of (unstructured) data sources, including job descriptions, to infer the necessary skills and proficiencies required for every job and job family in an organization – with excellent precision. Beamery clients, for example, have seen an amazing 90% accuracy of skills labels (on first review).
A team of humans (or consulting partner) could tackle this sort of project over several months, and be left with a static output that went quickly out of date. With appropriate AI tools, companies quickly get a cohesive, customized skills framework that can be used to match relevant candidates to tasks and roles – on an ongoing basis.
For instance, working with Beamery, Flex was able to reduce 1,200 job descriptions to just 40 standardized, skills-based compositions – in a matter of days. They also had a portal where users could easily review and edit roles as necessary, evolving them to reflect changing requirements inside the business, new technological innovations, or wider industry needs.
“Our skills-first hiring strategy required us to effectively connect the dots between various job grades and profiles. We recognized the opportunity to leverage AI technology to enhance our talent calibration process, ensuring that we attract and identify candidates whose skills align more closely with the specific requirements of the roles we are hiring for.” – Angela Athas, TA Partner: Sourcing Strategist, Flex
2. Empower Recruiters With Skills Intelligence
Once roles are clearly defined, the next step is ensuring that recruiters have the tools to match candidates to these roles effectively. Centralized, dynamic skills-based talent profiles means recruitment teams can truly see the full picture of the talent pool.
“[Our] new skills-based view of specialist roles has really helped users to calibrate the vacancy they are working on, and communicate with hiring managers around: what should we be targeting, what does good talent look like, and which candidates are those we can take action on.” – Angela Athas
Rather than relying on outdated resume keywords or generic titles, recruiters can focus on the actual skills required for a role, and match candidates based on their proficiency levels. As well as getting to more accurate talent matches, at speed and scale, this approach helps reduce bias, by ensuring that candidates are evaluated based on their true capabilities, not just their titles or past experiences.
Case study: Sellafield
For AI and skills intelligence to yield results, you do need to have a healthy database of active job seekers and passive talent. For example, Sellafield worked with Beamery to build an engaged talent network, meaning they always have a pool of pre-qualified candidates when a new role opens.
Now, when a job requisition is created in SAP Recruiting, it’s automatically pulled into Beamery, where recruiters can quickly match it against their existing candidate database. The results?
- Reduced time-to-fill for critical roles
- Higher quality of hires by focusing on skills.
- A continuous pipeline of skilled talent, ready when needed.
(Note: When selecting a partner to help you with skills-based hiring and AI-powered recommendations, do ensure they can integrate seamlessly with the systems you already use.)
For Sellafield, implementing Beamery’s AI-driven tools to match candidates to highly technical roles based on precise skill sets led to a notable reduction in mismatches and helped their recruitment team find better fits for critical positions faster.
“AI will help us understand how we identify skills that we need… the Beamery platform will really help us have a clear picture of what skills we have, and what skills we need to be successful both today and tomorrow,” said Martin Stubbs, Talent Acquisition Leader at Sellafield Ltd. “Filling critical and hard-to-hire roles is central to our ability to drive our mission at Sellafield. Combining the power and capabilities of SAP and Beamery is how we’ll do that.”
It’s also worth remembering that internal talent mobility is a powerful strategy for addressing niche skills gaps – and AI can play a critical role in making it effective. By using AI-driven insights, organizations can identify employees with transferable skills and move them into specialized roles, reducing the need for external hiring. This approach also fosters employee engagement and retention by offering career growth opportunities, which helps keep talent within the organization and reduces turnover.
Whether it’s people who’ve applied for roles in the past, silver medallists, sourced candidates, employees or even fractional or contingent labor – you do need a warm database of talent, and a consistent approach to building out their profiles.
3. Harness AI for Better Matching
As well as normalizing talent and role data, through the “currency” of skills, AI-powered recruitment tools can automate the process of matching candidates to roles, going beyond basic job descriptions to uncover a deeper connection between a candidate's skills and a company’s needs.
By using AI to analyze vast amounts of data – including skill proficiency, inferred skills, and seniority – organizations can create a more precise matching process.
AI allows companies to identify candidates who might otherwise be overlooked, ensuring that the hiring process is not only more efficient but also more inclusive. Check that your vendor has a clear commitment to transparency, compliance and bias reduction: baked into the AI models themselves, and within the interfaces that HR teams are using.
“By empowering our recruiters to easily unlock and review inferred talent, we can identify solid, qualified candidates who may have otherwise been overlooked. Ultimately, this approach will create a more agile and nimble recruitment process, allowing us to find and hire talent more efficiently and level the playing field in our industry.” – Angela Athas
Make Faster, More Informed Talent Decisions 🚀
By integrating AI into the recruitment process, organizations can significantly reduce the time and complexity involved in hiring for specialized roles.
Moreover, the AI-powered skills-first approach drives broader business outcomes:
- Greater organizational agility: By filling specialized roles quickly and accurately, businesses stay agile, enabling them to respond faster to market shifts and strategic initiatives.
- Competitive advantage: AI enables companies to secure rare talent, giving them a competitive edge in industries where specialized skills are the differentiator. With AI, businesses can consistently attract the expertise required to innovate and lead.
- Future-proofed workforce: AI-driven recruitment helps organizations not just meet immediate needs but anticipate future skills gaps. By understanding and addressing evolving skill requirements, companies can future-proof their talent pool and maintain long-term stability.
- Increased ROI on Talent Acquisition: AI enhances hiring efficiency, reducing time-to-hire and cost-per-hire. This ensures that recruitment budgets are spent wisely, maximizing the return on investment while securing top-tier, specialized talent.