AI in performance management: how to leverage it for team success

AI already is a reality reshaping performance management and the entire workplace. Yet, implementation challenges persist beyond just the technical setup. Our 2025 HR Insights Report shows that 61% of HR leaders say AI-driven role changes are urgent, while 60% cite employee resistance as a blocker.* If teams fear AI or don’t see its value, adoption stalls, and investment doesn’t deliver.

AI enhances performance management by automating admin tasks, extracting insights from feedback, and forecasting trends like promotion readiness. When implemented correctly and tailored to your business, AI can empower HR to support fair, data-driven decisions without increasing headcount or overburdening managers.

This article explores five practical ways to use AI in performance management, risks to consider, and how to implement AI responsibly.
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5 ways to use AI in performance management 

AI isn’t here to replace human judgment. But what it can do is make the hard parts of performance management faster, clearer, and scalable. That’s why 94% of HR leaders believe there are significant risks in not training internal employees in AI, including within HR.

Here are five practical ways HR teams are already applying AI and HR tools to reduce admin, improve consistency, and support better decisions.

1. Automate performance review summaries

AI tools that use natural language processing (NLP) can analyze written feedback from peers and managers and synthesize it into structured, readable summaries. This reduces the manual burden of drafting reviews (especially for managers with large teams) and helps ensure clear and consistent feedback across departments.

Summarization also minimizes variability between reviewers, improving fairness and speeding up review cycles. Platforms with built-in AI features like Leapsome can apply this approach directly within the review workflow, helping HR teams and managers focus more on interpretation and follow-up, not formatting. 

34% of HR functions are updating development plans to upskill employees to use AI and related technologies. That reflects how quickly AI is becoming embedded in day-to-day HR processes.
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💡 With Leapsome Reviews, managers can use AI to generate first-draft summaries of employee performance, making the review process faster without sacrificing nuance. Then, they can edit, adjust, or expand as needed to reflect the full context.

2. Conduct sentiment analysis of employee feedback

AI-powered sentiment analysis can identify tone, emotional language, and recurring themes within feedback channels — such as open-ended survey responses, review comments, or peer feedback. This allows HR teams to spot early signs of disengagement, frustration, or imbalance before they appear in turnover analysis and prediction metrics. That’s critical, since low-engagement teams typically face turnover rates that are 18% to 43% higher than highly engaged ones.

Sentiment analysis is particularly valuable when applied across large datasets or anonymized channels where patterns might go unnoticed. For example, a negative sentiment uptick in feedback from a particular region or team could trigger targeted check-ins or leadership support.

Some employee feedback tools can automatically apply this analysis to survey responses, helping teams move from data collection to action faster.
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💡 Leapsome Surveys includes AI-powered sentiment analysis that tracks how employee sentiment evolves. HR teams can segment results by group, monitor eNPS trends, and act faster on feedback that might otherwise be missed.

3. Predict performance trends using historical data

AI can model historical performance data alongside factors like feedback frequency, peer recognition, or goal achievement to flag patterns that suggest promotion readiness or burnout risk. ​​That’s especially relevant in 2025, with 66% of US employees experiencing some form of burnout. These signals support more proactive talent planning, like adjusting workloads, checking in with high performers, or identifying team members ready for a new challenge.

When integrated with an HRIS or HR process automation system, these insights help People teams build more data-informed development and succession plans. Importantly, this doesn’t replace manager insight, but is a way to guide attention and support better conversations.
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4. Generate & track goals

AI tools can help create effective objectives and key results (OKRs) by generating suggested goals based on inputs like job title, department focus, or recent performance themes. This reduces the friction managers often face when setting goals, especially across large or cross-functional teams.

Beyond goal creation, AI can also help track progress, highlight blockers, and suggest adjustments based on related performance data. These features support alignment and accountability, without adding complexity or introducing micromanagement.

According to WebMD Health Services, consistent recognition can add an incredible 3.5 years to an employee’s tenure. Plus, professionals who feel appreciated are 5x more likely to stay with their organization. Both things can be reinforced through well-structured, transparent goal-setting systems that spotlight achievements and impact.
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💡 With Leapsome Goals, you can generate OKRs with just a few clicks using AI, then receive real-time recommendations on refining them. It’s a quick way to improve alignment while minimizing lengthy planning cycles.

5. Personalize development plans at scale

AI can help tailor learning and development plans to individual needs. That matters more than ever, as 76% of employees are looking for opportunities to expand their careers and expect employers to support growth.

AI-supported competency frameworks can also save HR teams time, especially when building new roles or leveling guides.
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💡 Leapsome Competency Frameworks can be generated with AI in minutes, making it easier to define role expectations and support career progression. Pair this with Leapsome Learning to assign targeted courses and build ongoing development paths at scale.

How to implement AI in performance management responsibly

Introducing AI into performance processes can improve speed and consistency — but only if applied thoughtfully. HR leaders must ensure systems are fair, secure, and clearly understood. These four principles help lay the groundwork for ethical, effective implementation.
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1. Start with transparent data policies

Understanding the data AI systems use (and how that data is handled) builds trust from day one. HR teams should document what types of feedback, goals, and usage data feed into AI-powered features and communicate that clearly to employees and managers.
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🗒️ Leapsome publishes its security, privacy, and compliance commitments, including how data is processed, encrypted, and stored.

Monitor for bias in inputs & outcomes

AI can help reduce bias, but only if the data behind it is representative. According to McKinsey, only 20% (or less) of gen-AI-produced content is checked before use.

‍Consistently audit AI-generated outputs (e.g., review summaries, feedback suggestions) for signs of skewed language or unfair patterns across gender, location, or role level. Use these audits to refine inputs or flag systemic gaps.
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Combine AI with human discernment 

AI should never make the final call in performance evaluations. Its role is to provide context, uncover insights, and save time. Encourage managers to treat AI outputs as starting points for richer conversations, not hard conclusions.
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Train managers on interpreting AI insights 

A system is only as good as the people using it. Train people managers to read, validate, and act on AI-generated summaries or suggestions with confidence. Provide practical guidance on when to trust the output, when to dig deeper, and how to use the data in 1:1s or reviews.

For example, use goal-setting tools to help managers align with org-wide priorities while supporting individuals. The cascading goals framework helps link strategic direction with daily execution — but only if managers understand how to use it effectively.
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Turn AI from buzzword to performance driver

AI is changing performance management by giving managers better tools to support their teams. From drafting review summaries to identifying learning gaps and building development plans, AI can reduce the manual overhead and bring more consistency to people processes.

However, the impact depends on implementation. Companies that are seeing results are those using AI  to support performance management, combining smart tools with real human context.

Leapsome brings these capabilities together in one place. With features like AI-powered review summaries, goal generation, and competency framework creation, it’s built to help HR teams and managers work faster and smarter without sacrificing quality.
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💪 Support managers with the tools they actually need

Leapsome’s AI features take the admin off HR’s plate so they can focus on what really matters — growing their people.

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