Bots over Bosses - The Effect of AI in Performance Evaluation

Performance evaluations are an important part of employee management in companies. However, it has never been perfect, due to various factors such as unconscious biases, inconsistent feedback, ineffective assessments, and more. 

Now, with the entry of Artificial Intelligence (AI) in workspaces, companies have started using it to evaluate their employee performance. So let us understand the effect of AI on performance evaluation.

The Promise of AI in Performance Evaluation 

AI has opened a new frontier for evaluating employee performance. Unlike traditional methods, which rely on frequent inputs, AI-based tools gather and analyze performance data continuously. 

Hence, performance evaluation processes like finding out how long it took to complete tasks, identifying project completion efficiency, etc., can be undertaken without manual inputs. 

With the help of Machine Learning, companies can even identify patterns in high-performing employees, enabling them to understand what makes these employees stay dedicated, while also helping them detect any early signs of performance issues. It can also analyse 360-degree feedback and provide actionable insights to the organization. 

As a result, performance evaluations have become more technical, with reduced human biases. It results in a performance management process, which is more streamlined and aligned with the organizational objectives. 

Challenges and Ethical Considerations 

➤ AI might be far superior in terms of analyzing data and sharing meaningful insights; however, it still lacks context. AI may provide unbiased performance evaluations, but it doesn’t consider unforeseen challenges, employees’ mental health, or team dynamics, all of which can influence employee performance. 

➤ Since AI runs on algorithms making use of data, if the training data was based on a biased database, its evaluations will also have the same biases, resulting in serious issues with its evaluations. 

➤ Another major challenge is maintaining transparency in performance evaluations. While employees may be sceptical about sharing their performance data with a system, it can also affect managers when asked to justify their evaluation of a specific employee.

➤ AI systems also lack the human element of leadership, such as empathy and judgment, which are critical in performance evaluations. 

The Right Balance 

As with anything in life, finding ‘The Right Balance’ is critical for AI usage too. The ideal approach for AI implementation is ‘AI with humans’, and not ‘AI vs Humans’. Managers and HRs should use AI as a support mechanism rather than depending solely on its observations and deductions. 

While AI can surely highlight patterns and identify trends, humans should be the ones using their judgment to understand the subtleties of evaluating another human being! 

Here are some of the best practices for using AI in performance evaluations: 

• Let AI support manager evaluations.

• Train managers to figure out AI-generated data and gather insights from it.

• Remain transparent about data collection practices with your employees.

• Audit your AI and related tools to avoid any form of bias.

Conclusion 

While AI is transforming performance analytics with data-backed evaluations, it should be used cautiously with human intervention to provide contextual understanding. 

A responsible and ethical use of AI can improve your operational efficiency, while supporting your performance evaluations with human empathy enables you to create a culture of fairness and engagement.