Exploring the benefits and challenges of using AI when creating skill-based compensation models

The nature of work is rapidly changing. Technological advancements and automation are reshaping job roles and skill requirements. As a result, the traditional approach of compensating employees based solely on job titles and tenure is no longer sufficient. Skill-based compensation, also known as pay-for-skills, offers a more nuanced and flexible approach to rewarding employees based on their specific skills and competencies. This shift allows organizations to align compensation with the value employees bring to the table, fostering a culture of continuous learning and growth.

AI has the potential to revolutionize the implementation of pay-for-skills models. AI-powered systems can analyze vast amounts of data, including employee skills, certifications, performance metrics, and market trends, to determine fair and competitive compensation levels. By leveraging AI algorithms, organizations can identify the skills that are most valuable to their business and reward employees accordingly. This approach ensures that compensation is directly linked to the skills employees possess and the value they bring to the organization.

Implementing AI for pay-for-skills

Implementing AI for pay-for-skills offers several benefits for both organizations and employees. Some of these benefits include:

• Enabling a more accurate and objective assessment of skills
• Analyzing data without preconceived notions and subjective biases that can be present in normal compensation models
• Providing real-time insights into the market value of specific skills
• Facilitating personalized career development plans
• Identifying skill gaps and recommending relevant training opportunities

AI in the real-world

In a recent Mercer study with IBM, Binny Rieder, VP Global Compensation and Recognition and Anshul Sheopuri, VP & CTO, Data and AI, IBM spoke with Mercer’s Head of Product, Career Business, Jean Martin. They discussed the AI tool IBM has been working on implementing to facilitate a pay-for-skills philosophy and ease the burden of compensation decisions. Over the past 5 years, IBM has been transitioning to this pay-for-skills philosophy and was able to run a pilot within one of their markets.

“At the outset, IBM did not launch the AI powered skills-based compensation program worldwide. Rather, the organization started with a pilot project of 30 managers in a small market where the concept was beta tested. Additionally, to take it to the next level, this new program needed investment. But this was one area where an investment case was a no brainer.

This was because for a company of IBM’s size, where remunerations account for a large share of total expenses, even a 1% increase in efficient fund utilization can deliver substantial outcomes.” (Mercer.com).

Challenges and considerations

While the use of AI for pay-for-skills holds immense potential, there are challenges and considerations that organizations must address.

One key challenge is ensuring the accuracy and reliability of AI algorithms. Organizations must invest in robust data collection and validation processes to ensure that the AI systems provide accurate and unbiased results.

Additionally, organizations must be transparent in communicating the criteria and factors used in determining compensation to maintain employee trust and engagement. Ethical considerations, such as privacy and data security, must also be carefully addressed to protect employee information and comply with relevant regulations.

Some of the biggest roadblocks to pay-for-skills are:

• Complexity in implementation. Implementing a skill-based pay system can be more complex than traditional pay strategies, as it requires a thorough analysis of required skills, competencies, and certifications for various roles within the organization.
• Potential for subjectivity. There may be challenges in defining and measuring specific skills or competencies, which can lead to subjectivity and inconsistent pay decisions.
• Cost implications. Encouraging employees to acquire new skills and competencies can result in increased training and development costs. (HRMHandbook.com)

Steps to success

To successfully implement AI for pay-for-skills, there are a few things organizations should prioritize. First, it is crucial to involve HR professionals and subject matter experts in the design and implementation of AI systems to ensure alignment with organizational goals and values. Second, organizations should provide clear guidelines and training to managers and employees on how AI will be used in compensation decisions. This transparency fosters trust and understanding among employees. Regular monitoring and evaluation of AI systems is essential to identify and address any biases or inaccuracies that may arise. Third, organizations should continuously invest in employee development programs to ensure that employees have access to the necessary resources and opportunities to acquire and enhance their skills.

Leverage industry experts

AI has the potential to revolutionize compensation systems by enabling the implementation of pay-for-skills models. By leveraging AI algorithms, organizations can create equitable and effective compensation systems that reward employees based on their specific skills and competencies.

The experts at Mercer have been innovating in the AI and skills space. Our skills library is a market-derived skills taxonomy curated by Mercer and mapped to the Mercer Job Library and architecture. This enables the user to understand the skills that matter the most to each job and provides the solid foundation needed for any skill-based use case. The skills mapping tool is an online workflow solution that enables streamlined and validated mapping of jobs to the trusted skills taxonomy. It allows users to experience an easier skill customization workflow to build a validated skill-first foundational architecture. The combination of these two tools is powered through AI job matching, skill and proficiency level mapping, customization, and validation through review and approval automation.

This approach not only aligns compensation with the value employees bring to the organization but also fosters a culture of continuous learning and growth. Like with any automation, organizations must address challenges such as algorithm accuracy, transparency, and ethical considerations to ensure the successful implementation of AI in pay-for-skills. With careful planning and implementation, AI can be a powerful tool in creating fair and future-ready compensation systems.

By working or partnering with a human capital management consulting firm such as Mercer a company has firsthand access to the latest thinking in leveraging AI, industry expertise, and years of experience in pay philosophy and pay practice implementation.

Connect with us today at 1-855-286-5302.

About the Authors

Augie Bronson, Senior Analyst

Augie is a Senior Analyst in Mercer’s Career business in Houston, TX. He has experience in compensation and rewards, sales incentive plan design and effectiveness, project management, and data analysis and reporting.

James King, Principal

James is a Principal in Mercer’s Career business in Dallas, TX. He assists clients with talent strategy, workforce management, broad-based compensation, and sales compensation.