Demystifying AI in Skill Assessments: What You Need to Know

Introduction:

Artificial Intelligence (AI) has become a buzzword in the world of skills and talent management. But is it all just hype, or can AI truly revolutionize skill assessment? In this blog post, we’ll explore the use of AI in skill assessments, breaking down the pros and cons in a way that everyone can understand.

The Importance of Skill Taxonomies

Many AI-driven skill assessment tools lack a critical element – a structured skills taxonomy. Without it, skills are often poorly described, and there’s no way to gauge proficiency levels. This poses a significant challenge. Proficiency benchmarks and skill-specific descriptions provide a clear understanding of what ‘good’ looks like. Without proficiency levels, conducting comprehensive skill gap analyses for individuals or organizations becomes nearly impossible. It also complicates career development and recruitment, as there’s no basis for distinguishing novices from experts.

Traditional Skill Assessments vs. AI Skills Inferencing

Traditional skill assessment methods involve self-assessment, peer feedback, and manager validation, often supplemented by evidence like testimonials and certificates. AI, on the other hand, employs skills inferencing technology to identify those an individual possesses. It can analyze certifications, code, tests, and other achievements. This approach claims objectivity by reducing human bias in skill assessment.

Challenges with Skill Inferencing

AI can infer skills, but gauging proficiency levels remains challenging due to the need for substantial data points from various sources. How reliable is AI inferencing for making critical decisions? Joint skill evaluation by an employee and their manager, still benefits from human input, despite its resource-intensive nature. Employee and manager involvement in the process fosters engagement, informs development discussions, and builds trust. The benefits of “employee engagement” are well-known in respect of the value it provides in retaining talent.

Conclusion

AI has its role, but it’s not an all-or-nothing solution. A hybrid approach, combining AI with existing tools and human input, offers compelling advantages. AI streamlines tasks like developing job profiles and matching skills while maintaining consistency. Skill inferencing technology is promising and evolving. However, a human-in-the-loop approach is crucial for success, at least for now.

At Lexonis, we leverage AI for various activities, but we’ve found that combining it with human validation is key. For instance, generative AI aids in job profile creation, and skill inferencing augments employee and manager assessments, creating a well-rounded approach.

If you are interested in learning more, click here to register for our free webinar on September 28th, The AI Advantage: Real World Benefits for Skill-based Organizations.