The Role of Generative AI in Performance Management

AI is often referred to as a prediction machine because it uses algorithms to predict outcomes and identify patterns and trends, which can help improve decision-making accuracy. While traditional AI can analyse data and provide insights, Generative AI (Gen AI) can use the same data to create something entirely new.

A report by investment bank Goldman Sachs predicts AI could replace the equivalent of 300 million full-time jobs. The report also notes AI’s impact will vary across different sectors – 46% of tasks in administrative and 44% in legal professions could be automated, but only 6% in construction and 4% in maintenance. 

With the rise of Gen AI, there is a growing curiosity about its potential impact on different HR tasks, one of which is performance management. ChapmanCG Director Elaine Khoo explores the different areas of the performance review and development process that the use of Gen AI could influence.

Understanding AI-Powered Performance Management

AI-powered performance management leverages artificial intelligence algorithms to make informed decisions about employee performance. It goes beyond traditional performance measurement by considering a range of factors within the review process. Rather than relying solely on ratings or scores, AI analyses data to identify areas for improvement and uncover strengths that employees may not be aware of. For example, the analysis of textual feedback from multiple stakeholders, project outcome analysis, work habits, communication patterns and performance trends. By making the most of the AI tools available to them, organisations can enhance their decision-making processes and drive a high-performance culture.

A quick poll in our HR network revealed that most HR leaders surveyed use AI primarily to automate repetitive tasks and recruitment, whilst performance management and L&D only rank third and fourth in this list. In a recent ChapmanCG hosted webinar, HR leaders suggested that the use of generative AI in this area was minimal due to its complexity and uncertainty.

Seven Ways to Incorporate Generative AI into Performance Management 

Here are some areas of Performance Management where the use of Gen AI tools may be helpful, even for someone just starting to adopt AI in their daily job:

Data Analysis and Insight Generation

Gen AI can identify patterns, strengths and areas for improvement that are not obvious through manual analysis. Companies like Deloitte are combining behavioural science insights with the latest AI technologies to create a new kind of tailored coaching experience for their employees. These new “smart AI coaching” systems combine multiple data sources to identify specific strengths and weaknesses in an employee’s performance and can effectively give the team member “nudge” on a timely basis. An individual’s response to different nudges can then be further analysed to develop a profile of their preferred learning style and the types of intervention that work best for them. 

Personalised Learning & Development

By analysing individual employee performance data, Gen AI can recommend tailored training programs that align with specific skills and career goals. At Siemens, the learning process starts with employees doing a self-assessment alongside their manager and then feeding those assessments into the company’s robust skills graph to receive personalised feedback about skills gaps and potential learning paths. This ensures that learning experiences are customised and impactful, promoting continuous growth and improvement.

Employee Engagement

Gen AI can gauge employee engagement levels through sentiment analysis on surveys, social media, and communication channels, helping organisations identify influencing factors and improve overall employee satisfaction. This valuable insight allows organisations to take targeted actions to improve overall employee satisfaction and create a more engaged workforce. 

Workforce Planning

Generative AI’s predictive capabilities can assist organisations in anticipating future workforce needs. By analysing data and trends, AI can provide insights into talent gaps, skill requirements, and potential growth areas. This enables organisations to strategically align their workforce and ensure they have the right talent to meet long-term objectives. 

Bias Mitigation 

By evaluating performance data objectively, Gen AI can identify and mitigate biases in the performance evaluation process, promoting fairness and inclusivity in performance management. Organisations can ensure that performance assessments are based on measurable outcomes and competencies rather than subjective impressions. 

Time and Attendance Monitoring

Gen AI can automate the monitoring of employee attendance, working hours, and productivity, offering valuable insights into potential areas for improvement and ensuring optimal workflow efficiency. This not only saves time but also ensures that employees are working at their optimal capacity. 

Succession Planning

Identifying employees with leadership potential is critical for succession planning. Generative AI can leverage skills, performance, and behavioural data to assist organisations in identifying high-potential employees. Johnson & Johnson uses AI to drive their career development program. J J Learn starts with collecting an employee’s reflections and insights on how they want to develop their careers. From there, AI makes recommendations on learning materials, suitable mentors, and real-world opportunities at J&J to guide employees’ upskilling journey. This helps the organisation maintain a robust talent pipeline and ensures a smooth transition of leadership roles.

Ethical Considerations in AI-Powered Performance Management

While AI offers significant benefits in performance management, it is important to consider privacy and ethical concerns when integrating generative AI into HR. Where possible, organisations should analyse anonymised data rather than individual employee data to ensure privacy. Transparency is crucial, and employees should be aware of the purposes behind AI-driven initiatives. It is also essential to avoid collecting excessive or irrelevant personal information not directly tied to improving performance management.

Despite all the hype, it’s not meant to replace humans, but to better unlock human potential— just as technology was always meant to do.

Deloitte AI Institute 2023: Generative AI and the future of work. The potential? Boundless.

It is also important to note that human interaction is still crucial in the role of HR practitioners. AI should be used to upgrade, not replace, human skills and decision-making. HR practitioners play a vital role in interpreting AI-generated insights and making informed decisions based on their expertise. By combining the power of AI with human judgement, organisations can create a more meaningful and inclusive workplace where biases are minimised and talent is identified and nurtured.