The Majority of Employees Underestimate Their Skill Levels. That Can Be a Disaster for Your Company’s Growth.

The way we train and develop employees is changing.

Companies are moving away from the rigid job descriptions and educational requirements of the past shifting instead towards a skills-based approach — evaluating and training employees for the specific abilities they need for tasks and projects. 

In this new environment, learning and development (L&D) takes on new importance. A company that can identify the right skills for its employees and train them quickly will soon overtake a company that has stronger recruiting but poor skills development. Building these skills effectively requires an organization to understand its employees’ current skill levels and where they need to focus their attention.

Workera is a skills development platform that uses artificial intelligence to assess employee skill levels and prescribe the most effective path for development. We recently conducted an analysis of our platform’s data to understand how employees rate their own skill levels. The results have serious implications for any organization that hopes to improve their L&D.

How do employees evaluate their own abilities?

We gathered anonymized skills data from several thousand Workera users, who together conducted more than 22,000 domain assessments since the beginning of 2023. In each case, the user was asked to evaluate their current ability level before performing a computerized adaptive test (CAT). The CAT result is an accurate proxy for their current ability level; comparing the two scores reveals how accurately a user is able to assess their own skill levels.

Workera assesses domains (larger categories of individual, highly specific skills) on a 300-point proficiency scale. Users who score between 0–100 are considered Beginning; 101–200 are Developing; and 201–300 are Accomplished. The number of points they add to that score per week is referred to as their “learning velocity”; a standard learning velocity is equivalent to five points per week per domain. If the difference between the self-assessment and the CAT result is greater than 10 points, we consider the learner to have inaccurately estimated their skill level and how long it would take them to close the gap.

Here’s what we found in the data:

• Users underestimated their skill levels in 56% of the cases, while 32% overestimated their skills. Just one in 10 users (11%) accurately estimated their skill level.
• Even as you increase the margin for error, users are far more likely to underestimate their skill levels. If the difference between the self-assessment and the CAT result is greater than 30 points, we find that 47% underestimate their abilities, 24% overestimate, and 29% fall within the acceptable range of accuracy. To put it another way, seven in 10 users (71%) aren’t able to accurately judge their current ability levels one way or another.
• The more technical the domain, the more likely the user is to accurately evaluate their abilities. We broke down the results according to specific domains, ranging from highly technical domains (machine learning; probability and statistics) to those that depend more on fluency (generative AI; communicating about AI). The results show that users have a better understanding of their abilities in technical domains: for example, just 17% of users underestimated their abilities in machine learning (55% estimated accurately), while 69% underestimated their abilities in communicating about AI (27% estimated accurately).

Taken together, there are two clear takeaways: employees are most likely to underestimate their skills, and a surprisingly low percentage of employees are able to accurately assess their own ability levels. That can put organizations on shaky ground as they work to develop their employees’ skill levels. 

Why accurate skills measurement matters

The point of L&D is to move your organization forward — so why is the starting point so important? 

Time is a finite resource. Employees can only devote a certain number of hours to skills development; the more efficient those hours are, the more that employee will be able to contribute to projects going forward.

When employees chronically underestimate their skills, they end up spending valuable time studying material they already understand. The result is a workforce that spins its wheels, standing in place instead of moving forward. Over time, this will add up to a competitive liability as your organization falls behind competitors that understand their ability levels and are constantly driving forward.

Of course, it’s also important to pay attention to the 32% of employees who overestimate their skills. These employees don’t recognize the need to study specific fundamental domains: as a result, not only do they lack the skills to complete specific tasks and projects, but they also lack the knowledge building blocks that will enable them to develop more advanced skills. The result is functionally the same as in underestimation — a workforce that is unable to steadily move forward.

Four quadrant classification of
upskilling risks

Awareness about relevance of skills

Awareness about
own skill level

Unknown unknowns

Skills I didn't know I don't have

Overestimates own skills. E.g. has skills gaps that prevent confident and safe  task execution

High cost

Unknown knowns

Skills I don't know I have

Underestimates own skills. E.g. spends valuable time studying material they already understand

Moderate cost

Known unknowns

Skills I know I don't have

Accurate estimates of own skills. Devotes effort to acquire the skills required in tasks and projects that are not currently owned

Precision upskilling 

Known knowns

Skills I know I have

Accurate estimates of own skills

Least likely scenario

Our consistent inability to evaluate our own skills points toward the need for objective, accurate measurement. Workera’s use of adaptive tests as part of our skills assessments allow an organization to build on a stable foundation. Workera’s scoring don’t just show where an employee stands today, but also the path forward: Workera’s personalized learning pathways allow users to acquire skills six times faster than competing platforms. 

Committing to skills-based development is an important first step for the future of work. But for this strategy to succeed, organizations must embrace objective, AI based assessments. 

Ready to learn what verified skills assessments can do for your business? Connect with one of our assessment experts today.