The Pivotal Role of AI in Performance Management

Updated April 9th, 2026

Performance management is a double-edged sword: essential for employee growth but often time-consuming and resource-intensive. Managers, tasked with balancing performance evaluations alongside their own responsibilities, frequently struggle to deliver high-impact feedback and guidance. These challenges highlight a pressing need for innovation — and artificial intelligence (AI) in performance management is stepping in to fill the gap.

Research from Betterworks' annual State of Performance Enablement report reveals both the stakes and the opportunity: while 2 in 3 managers still need more support to effectively manage performance, the payoff for getting AI right is significant. According to Betterworks' 2026 State of Performance Enablement report, employees in AI-enabled performance systems report high satisfaction at a rate of 89% — compared to only 40% among those without AI in their process. Yet the same research found that 78% of the employees most proficient with AI are actively looking for new jobs, revealing a critical gap between AI adoption and performance enablement.

Traditional performance management systems can be painstaking and time-consuming, says Cheryl Johnson, chief product and technology officer at Betterworks. According to Betterworks' 2026 report, 90% of HR leaders say AI has already redefined what "high performance" means — yet only 42% of organizations have updated their goals or review criteria to reflect that shift. 'Incorporating AI, particularly generative AI, into performance management can relieve this burden from managers, offer deeper, objective insights into past employee performance, remove the bias from the calibration process, and inform career growth and skill-building,' Johnson says. 'But the technology alone isn't enough. The organizations that win are the ones that build the performance enablement structure around it.'

AI in performance management is more than a technological advancement. Learn how to harness AI to empower managers, enhance employee development, and drive organizational success. 

AI’s role in modern performance management

AI is transforming performance management into a more dynamic and high-‌impact process. While traditional methods often rely on manual tracking and subjective insights, AI-driven solutions offer a data-backed approach to understanding employee performance in real time. 

Generative AI (GenAI), in particular, has the potential to revolutionize how HR leaders and managers can streamline, automate, and enhance HR processes. Adoption is accelerating rapidly. Gartner reported in 2025 that 44% of HR leaders intend to adopt agentic AI — autonomous systems that can plan and execute HR tasks without constant human prompting — within the next 12 months. Meanwhile, 75% of organizations now plan to integrate AI into their review processes, and the global performance management software market is projected to grow from $5.82 billion in 2024 to $12.17 billion by 2032 (Fortune Business Insights). The question for most HR teams is no longer whether to adopt AI in performance management, but how to do so effectively and responsibly.

At Betterworks, for example, we’ve integrated AI into the performance review process to help you overcome common challenges like bias, inefficiency, and lack of engagement. By leveraging AI-driven insights, Betterworks empowers managers and employees to focus on what truly matters — development and collaboration. For example, AI can identify patterns and provide recommendations for goal alignment, coaching opportunities, and performance improvements, all within the flow of work.

The Next Frontier: Agentic AI in Performance Management

Most current AI in performance management is generative — it responds to prompts, drafts feedback language, and summarizes data when asked. The emerging layer is agentic: AI systems that can autonomously identify a skill gap, assign a learning module, draft a coaching plan, and flag a retention risk — all without waiting for a manager to initiate the process.

According to Mercer's 2025 HR trends research, agentic AI is transforming HR from reactive to proactive. Rather than analyzing past performance, agentic systems continuously observe, predict, and recommend — creating what analyst Josh Bersin calls a vision of "HR 2030," where AI agents operate alongside employees as ongoing performance partners. For HR leaders, this means the performance management tools you evaluate today should be assessed not just on their current GenAI features, but on their roadmap toward agentic capability.

“With AI, managers and employees will get the full benefit of performance management,” Cheryl says. “All the things that we are advocating for — team alignment, employee engagement, continuous coaching and development, succession planning, and talent clarity.”

Instead of replacing human decision-making, Betterworks’ AI works alongside users, supporting managers with intelligent suggestions, delivering comprehensive summaries of feedback, and enabling employees to craft meaningful goals that align with broader organizational objectives. “In our view, AI is the co-pilot,” says Doug Dennerline, CEO of Betterworks. “This capability saves managers a lot of time and frees them to focus on strengthening relationships with their employees and doing strategic work.” This ensures that every performance conversation is backed by data while still retaining the human touch.

From setting objectives to delivering feedback, AI-powered tools like those from Betterworks are designed to simplify and scale processes, allowing you to create a culture of continuous growth and development. By making performance management more precise and actionable, AI helps organizations foster better alignment, engagement, and overall productivity.

5 Use Cases for AI in Performance Management

AI has great potential for HR leaders, but like any technology, it’s most effective when applied thoughtfully. Here are three areas where we expect GenAI to influence performance management.

Providing better feedback

Fair, effective, and actionable feedback is essential to a great employee experience and better performance. According to Betterworks’ 2024 State of Performance Enablement report, 20% of employees don’t get regular conversations with their managers and 2 in 5 receive no peer feedback. 

Managers can struggle with feedback for many reasons, including insufficient training, time, or resources. In fact, this research revealed that nearly a quarter of managers say they have fewer 1:1s with direct reports and 17% spend less time on providing qualitative feedback.

AI in performance management eliminates the pain and second-guessing associated with delivering candid, supportive, and action-oriented feedback. 

“Feedback is riddled with bias,” Doug says. ”Most of us are not psychologists. We don’t necessarily know what motivates or demotivates our people. With data and GenAI, we can remove the bias, remove the opinions, and actually give employees actionable feedback.” 

AI-powered performance management processes collect data from multiple sources for a fuller and unbiased individual performance summary. Within Slack or Microsoft Teams, for example, AI tools can recognize when conversations include feedback or recognition and pull that interaction into the performance management platform to provide actionable suggestions that are personalized for each employee.  

Betterworks’ Feedback Assist, for example, takes user feedback in any form and provides leaders with personalized, constructive, and unbiased feedback for employees, leading to greater trust, focused career pathing, and better outcomes. Feedback Summary streamlines the review process by condensing feedback, identifying critical themes, and pinpointing strengths and areas for development. This saves time for managers and enhances their ability to coach effectively.

LivePerson, a Betterworks customer, has adopted Feedback Assist and Feedback Summary to speed and simplify its managers’ feedback, allowing managers to scale. “It takes five minutes to do quality stakeholder feedback, which is important,” explains Matthew Meech, talent development manager at LivePerson. “Some of our leaders get 20 or 30 because they work cross-functionally, and they need to be able to deliver that feedback.” Using Feedback Summary, managers have been able to reduce the amount of time it took managers to complete performance reviews by 50%-75%.

Facilitating ongoing conversations

Managers are busy, often serving as individual contributors in addition to being team leaders. They can struggle to find the time for ongoing, meaningful conversations with their team members, much less know what to focus on in individual conversations. 

Betterworks facilitates ongoing conversations by equipping managers with AI-driven conversation prompts tailored to an employee's goals, past performance, and feedback history. These intelligent suggestions provide managers with specific talking points, making it easier to engage in meaningful discussions that drive alignment and growth. This capability not only saves time but also ensures every interaction contributes to continuous performance improvement.

Developing powerful goals

Setting the right goals can be challenging for employees. Personal goals should align with the goals of the worker’s team, department, and overall business. They should leverage each team member’s unique skills and abilities, strike the right balance between achievability and ambition, and provide a pathway for skill development. The best employee goals are stretch goals, which include practice in the skills employees need to achieve their career aspirations. 

Betterworks’ Goal Assist uses AI to help employees and managers create personalized performance goals that align with broader organizational objectives. By analyzing an employee’s role, responsibilities, past goals, and career aspirations, alongside team and organizational priorities, Goal Assist provides tailored recommendations that make goals more relevant and actionable.

This personalized approach doesn’t end at goal-setting; Betterworks also integrates performance reviews into the process. Employees and managers can track progress toward goals and incorporate feedback seamlessly into performance evaluations. This ensures that goals remain central to the review process, fostering a culture of accountability and continuous improvement.

LivePerson has begun using Betterworks Goal Assist, and has already seen an impact. “My experience is that employees don’t always know how to create a performance goal that is meaningful to them or the organization,” says Deanna LaPierre, senior director of talent development at LivePerson. “Goal Assist helps the employee by looking across a broader set of goals like a manager’s goal, top-level goals, and the employee’s job title, and suggests meaningful goals that are specific to the individual employee. It is pretty clear to see that employees who used Goal Assist had a higher level of quality than those who didn’t.”

Evaluating Employee AI Proficiency

As AI becomes a core work tool, performance management must evolve to assess how well employees use it. A 2025 McKinsey study found that employees are three times more likely to use AI for 30% or more of their work than their leaders realize — creating a measurement blind spot. Forward-thinking organizations are now incorporating AI proficiency into performance reviews, evaluating not just whether employees use AI tools, but how effectively they apply them to improve output quality, speed, and decision-making.

Key considerations for evaluating AI proficiency fairly include: assessing outcomes rather than tool usage frequency, ensuring equal access to AI training and tools across the workforce, and establishing clear rubrics that distinguish strategic AI use from task-level automation. Worklytics' 2025 framework recommends measuring AI proficiency levels, ethical usage practices, productivity improvements, and the quality of AI-assisted outputs — not just adoption rates.

Predicting and Preventing Employee Attrition

One of the most consequential — and underutilized — applications of AI in performance management is using performance data to identify flight risk before employees decide to leave. Betterworks' own 2025 research uncovered a striking paradox: 78% of the highest-frequency AI users in organizations are actively looking for new jobs. This cohort — your most digitally capable employees — are also your most in-demand externally.

AI-powered performance systems can surface this risk early by correlating engagement signals, goal completion patterns, feedback sentiment, and skill development activity. When performance data is integrated with engagement tools, managers can identify the early warning signs and intervene with targeted coaching, career development conversations, or expanded responsibilities before a valued employee decides to leave.

5 benefits of AI-driven performance management

The primary role of AI in performance management is to increase manager effectiveness so that managers can transform simple employee interactions into powerful drivers of business impact. Here are a few of the benefits of using AI to support better performance management.

Reduced risk of recency bias and other biases

Human biases can skew a manager’s perception of performance. When giving a performance evaluation, recency bias can prompt managers to place more emphasis on recent events, good or bad. If an employee recently struggled with deadlines, for example, their manager may give them a more negative review—even if their overall performance track record was outstanding.

AI can help managers combat unintended recency bias in conversations and feedback by making it easy to refer to historical employee performance data. “Managers are not going to miss those things that might have been captured already or captured six months ago because it’s all there for them,” Cheryl says.

By providing a comprehensive view of an employee’s accomplishments, skills, and capabilities,

AI also helps guard against other unconscious biases, such as affinity bias and the “halo and horns effect,” that can affect performance reviews and calibrations. 

Improved employee productivity

Performance feedback is most useful when delivered in the flow of work, giving employees the chance to apply it in real time. However, managers often struggle to deliver real-time employee feedback, especially in remote and hybrid settings, when they may not have as much visibility into performance.

Augmenting performance management with AI can increase employee productivity by facilitating personalized feedback and performance insights — all in the flow of work. GenAI-powered performance reviews can help managers deliver better feedback more consistently, while employees get sound advice they can immediately implement for better outcomes.

Increased fairness and objectivity

Fairness is a key element of a great employee experience. In fact, fairness was the most important workplace quality for respondents in our 2024 State of Performance Enablement report — ahead of characteristics including good work culture, flexibility, and growth. AI helps managers and peers leverage feedback given across time and place for a more complete and objective picture of employee performance. This reduces the likelihood of subjective judgments because managers are relying on data-driven feedback and documented conversations.

Higher-quality human relationships

One of the greatest benefits of implementing AI at work is its ability to make work more human. Applying AI in performance management can streamline or automate administrative and time-consuming tasks for managers, creating more time for meaningful conversations and coaching that keep employees engaged, productive, and performing at their highest level.

Greater organizational success

Because AI helps organizations improve their performance management through data-driven insights, your managers can make better judgments about coaching employees to improve and develop their strengths. This can ultimately lead to increased organizational success, as employees are focused on the areas with the biggest payoff and deliver better outputs for the business.

Risks and Responsible AI in Performance Management

AI's potential in performance management is real — but so are its risks. Organizations that deploy AI in people processes without proper governance expose themselves to legal liability, employee distrust, and feedback quality that's worse, not better, than what a thoughtful manager would produce.

Automation Bias When AI generates a performance summary or feedback recommendation, managers may accept it without scrutiny — a phenomenon known as automation bias. The SHRM 2025 Talent Trends report found that 67% of employees disagree that their organization has been proactive in training them to work alongside AI. Without training on when to override AI output, managers risk rubber-stamping assessments that are inaccurate or unfair.

Bias Amplification AI models trained on historical performance data can encode and amplify the biases already present in that data — including gender, race, and age bias. Regular algorithmic audits, diverse training datasets, and third-party bias testing are not optional safeguards; they are baseline requirements for responsible deployment.

Legal and Regulatory Compliance The EU AI Act, which began enforcement in 2024 with escalating requirements through 2026, classifies AI systems used for employment decisions — including performance evaluation — as "high-risk." This requires transparency documentation, human oversight mechanisms, and the ability to explain AI recommendations to affected employees. In the United States, the EEOC has issued guidance on AI in employment decisions, and several states have enacted or are considering legislation requiring bias audits for AI HR tools.

The Transparency Imperative Betterworks' 2026 State of Performance Enablement report found that only 8% of employees say their company has communicated a clear AI vision. This opacity fuels anxiety: nearly 50% of employees are not yet comfortable using AI at work. Regular, honest communication about how AI is used in review processes — and how employees can query or contest AI-generated assessments — is essential to maintaining trust.

Responsible AI Deployment Checklist

Before deploying any AI tool in your performance management process, ensure you can answer "yes" to each of the following:

• Has the vendor demonstrated how their model is tested for bias?

• Do employees know that AI is being used in their performance process?

• Is there a human review step before any AI-generated assessment is finalized?

• Is the AI's output explainable — can a manager articulate why a recommendation was made?

• Has legal counsel reviewed for EEOC compliance and, if applicable, EU AI Act requirements?

• Is there a feedback mechanism for employees to flag inaccurate AI-generated content?

Applying AI in performance management

GenAI presents a powerful opportunity to improve performance management outcomes for employees, managers, HR leaders, and organization‌s.

AI can help your managers unlock the performance potential of your workforce by streamlining tasks, summarizing key information, and freeing up time for one-on-one interactions. When you understand how to thoughtfully implement AI, you can enter a new era of transformational performance management.

Want to learn more? Explore 3 Ways AI Transforms Work According to HR Leaders.