When it comes to processes that employers, managers, and leaders dread, it’s likely to be performance management. And unfortunately, according to Gartner research, 71% of CHROs agree that managers are not fulfilling their role when it comes to performance management. And as a result, employees aren’t getting the type of feedback that they need to perform.
These shortcomings ripple beyond individual performance and can affect organizational success. A May 2024 Gartner survey of 1,456 employees found that only 52% believe performance management is helping their organization achieve its business goals.
What prevents employees from getting the most out of performance management is likely due to a perception of bias or lack of fairness in the process. Surprisingly, employees are starting to view AI as being less biased than humans when it comes to performance decisions. An October 2024 Gartner survey of nearly 3,500 employees found that 87% of employees think that algorithms could give fairer feedback than their managers right now, and an additional Gartner survey from June 2024 found that 58% of employees believe humans are more biased than AI when it comes to making compensation decisions.
Generative AI in performance management
Employees are embracing the idea that AI or generative AI (GenAI) can increase, rather than erode, fairness in the workplace. Understandably, a healthy level of skepticism still exists. At Gartner, we found that only 34% of employees agree or strongly agree that if an algorithm provided performance feedback (instead of their manager), the feedback would be fairer.
It’s the duty of CHROs to improve the effectiveness and fairness of performance management at their organizations. But if that means integrating GenAI to achieve their goals, they need to take the following steps.
Step one: Evaluate the benefits of GenAI against performance management pain points
To leverage GenAI to improve performance management, HR leaders need to understand the pain points at their organization. They also need to have an idea of how GenAI capabilities might be useful in addressing them.
Data from Gartner employee and manager surveys, as well as interviews with CHROs and heads of talent management, revealed two common complaints about performance management. First, the effort required is too high. Employees and managers complain that the process demands too much of them, is overly complex, and relies on cumbersome technology. Second, many questioned how useful it actually is. Employees and managers shared that performance management was not relevant to how they work, not aligned with business needs, and disengaging and unmotivating.
To have a greater understanding of the pain points within their unique organization, CHROs and heads of talent management should ask managers and employees across the organization to provide feedback on their biggest pain points. From there, HR leaders can assess whether GenAI is the right tool to address those issues.
For example, if fairness is an issue, leaders can implement GenAI as a tool to evaluate text for bias. If time-spend and disparate technology are an issue, companies can use GenAI to summarize data and generate insights from multiple HR systems.
Step two: Gauge readiness for GenAI in performance management
Not all workplaces are alike, and some may be more open to the full spectrum of GenAI capabilities than others. Surveys can be a great tool to assess workforce readiness for GenAI in performance management. This way, leaders can ensure that the technology enhances, rather than detracts, from the employee experience.
Leaders should combine quantitative survey data with qualitative feedback by equipping managers with tools to get a fuller picture of workforce GenAI readiness. This might mean sharing standardized GenAI statements reflecting the desired performance state with managers. For example, that might mean using GenAI as a way to level bias in performance management, increase efficiency, and employee satisfaction.
In addition, question guides can also support managers in gathering candid employee input, such as whether employees are comfortable with GenAI drafting goals or suggesting performance ratings (with human oversight). Managers should collate feedback to assess GenAI’s limitations in performance management.
Step three: Secure employee trust to boost adoption and satisfaction
Trust is a top barrier to AI adoption. This is why building a foundation of trust is important when integrating GenAI in performance management. CHROs and talent management leaders can build employee trust by increasing visibility into decision-making and establishing an open dialogue about GenAI.
HR leaders should start by equipping managers and employees with the rationale for how and why the organization is introducing GenAI in performance management. A simple view into the “why” behind a decision helps employees accept and trust the decision. Employees also need to understand how decisions will directly impact their roles, so they can process, adapt, and move forward in good faith.
Lastly, leaders should establish mechanisms for employees to share feedback on GenAI in performance management to build trust and improve processes. These kinds of mechanisms help leaders identify when there is an erosion of trust, so they can rectify it by incorporating more human touch.
Effective performance management leads to better organizational performance
Improving performance management boosts employee engagement and business success. Gartner research shows that when HR aligns performance management with employee and business needs, organizations see higher perceptions of fairness and accuracy. They also see increases in employee performance (40%), engagement (59%), and overall workforce performance (60%). Increasing performance management utility drives better outcomes for everyone.
With employees starting to see the potential of GenAI in performance management, now just might be the ideal time to integrate this technology.
