Unlocking the future: AI-enhanced skills matching and ontology

Have you ever played matchmaker? It's no easy feat, and in the world of work, matching an employee's skillset is often very challenging. However, technology has a crucial role to play in streamlining this. Leveraging AI to build skills ontologies will create more accurate and dynamic databases, driving the future of AI-powered skill matching.

AI may seem complex, but it can be hugely beneficial to HR. Streamlining hiring through AI skills matching can transform the job market and benefit organisations and employees.

Skills matching made smarter with AI

1) What is skills matching?

Skills matching connects people to roles based on their skillsets and experience. Incorporating AI-driven talent-matching technology takes this one step further, showcasing each employee's strengths and preferences to find the perfect role.

Let's use an example: Grace is a developer, and she's looking for a new job that will match her skill set. Naturally, she's tech-savvy and a good problem solver. She eventually wants to become a CTO but needs help figuring out the next step on her journey. AI-powered skill matching can identify an engineering manager role that matches Grace's skillset and puts her one step closer to achieving her goal.

2) How AI powers skills matching

Products like our Skills Graph use AI algorithms to analyse data around job descriptions and candidate profiles and extract relevant information. Automating this process enables companies to transition to AI-driven talent acquisition strategies, allowing technology to source a suitable applicant. AI-powered recommendations help candidates find their ideal role quickly and efficiently.

3) Real-world example of AI-driven skills matching

We can look to the healthcare industry to understand how leveraging AI widens the talent pool. Candidates could be nurses with differing titles, such as A&E nurse or pediatric nurse — yet they will all possess related skills that can be transferred and used across the profession.

Maximising HR efficiency is key in the healthcare industry. Automatically matching candidates' skills to a role's requirements eliminates time-consuming and costly manual processes so that HR can focus on other tasks.

Unraveling ontology and skills mapping

1) What is a skills ontology?

A skills ontology is a set of unique skills with relationships to other skills or entities like job roles. It differs from a skills database, a list of terms with associated definitions, and a skills taxonomy, which incorporates hierarchical relationships between skills. Instead, a skills ontology provides context for how skills are related. For example, it can understand how administrative skills relate to IT skills, enabling AI-powered tools, like our Skills Graph, to understand different subject areas so they can better assist in skill matching.

2) How AI powers skills ontology

AI is integral to a skills ontology. It can learn quickly, process vast amounts of data, recognise patterns, and imitate human thinking — but quality output requires quality input. Feeding AI with as many skills and associated keywords as possible will help create accurate skills ontologies. It also ensures HR leaders are updated on their workforce's skill sets. AI can then deconstruct roles into specific skills to enable skill-to-job alignment, while leaders can facilitate meaningful conversations around skill development and chart growth.

Building a complete skilling strategy with AI and skills ontologies

1) Benchmark and assess

AI-driven skills profiles capture skills, proficiency, interest and enjoyment. Users perform self-assessments by selecting what they enjoy, what isn't of focus and where they can develop.

Peer assessments are equally important. These provide a holistic view of a person's abilities and pinpoint skills that a self-assessment may have missed. They also help highlight skills gaps so employees can begin upskilling or reskilling.

2) Closing skills gaps and empowering development and growth

AI-enabled skilling strategies ensure learning is personalised, with each opportunity matching a person's needs and interests. Once gaps are identified, AI delivers tailored learning content to close them. Doing so helps employees meet immediate performance expectations and connect to long-term career paths, interests and goals.

3) Enabling strategic deployment

HR leaders and managers can test employees' newfound skills with strategic deployment by accounting for goals, roles, projects and gigs. As skills are deployed, skills profiles change in accordance, helping managers visualise employee progression.

Scaling skilling strategies and other benefits

Skills ontologies empower leaders to scale up their skills strategies to be business-wide rather than existing in pockets and only impacting individuals. Beyond this, skills ontologies affect every area of HR. For instance, when it comes to recruitment, AI-powered skill matching can identify which candidates could close skills gaps, pairing them with the right roles at the right times.

Understandably, HR leaders may have concerns about AI, but its positive impact on recruitment, growth, and innovation is undeniable. Businesses can better reap the rewards by shifting HR's mindset to focus on AI's benefits.

Elevating efficiency through A-Powered automation

So, to reiterate — playing matchmaker isn't easy. Without AI, HR practitioners would have to spend a lot of time and effort building skills ontologies and matching candidates to roles. Not only would this be infinitely more difficult, but it would result in less detailed insights — and more human errors.

So, let AI take on the task! Automation can provide detailed and accurate insights to close skill gaps more efficiently, so the best candidates are selected for job roles and businesses experience more growth and success.

To learn more about how AI can enable better talent decisions, visit our website.