AI Coach can support a wide range of people leadership and communication topics, including:

AI Coach is most effective when used to:

AI Coach helps people leaders act with clarity, confidence, and speed by providing:

AI Coach is designed to reduce cognitive burden and bias by quickly synthesizing various performance data sources to develop an objective, robust view of an employee's performance over time.

The guidance underlying AI Coach in Performance is rooted in Culture Amp’s research and established best practices for high-impact performance conversations. The goal is to facilitate review writing that drives sustainable high performance and employee engagement.

AI Coach applies the same feedback characteristics that our Suggest Improvements AI feature uses to help craft effective performance feedback; in addition it also uses evidence-based practices to make reviews clearer, fairer, and more useful. It emphasizes objective evidence, bias reduction, and psychologically safe dialogue.

It does this by encouraging managers to:

Employees want performance reviews that feel open, honest and meaningful. AI Coach's guidance prioritizes this approach to support and help maintain psychological safety - which Culture Amp has found is essential for sustainable high performance. The underlying principle is that performance reviews should focus on an employee's value and growth, not just assessment.

This is achieved by guiding managers to:

Further reading: 60 phrases for performance review feedback

Employees consider performance reviews high quality when appropriate recognition is included. Culture Amp research shows that recognition is also one of the top drivers of engagement.

AI Coach encourages managers to:

AI Coach encourages a review structure that is based on research which identifies the topics most critical for employee development and future value. This ensures the written review is meaningful and comprehensive. AI Coach prompts managers to reflect on the full picture of performance (what happened, how it happened, and what’s next), using evidence from the review period.

Managers can also use the review to reinforce that the employee’s work matters, and to share clear next steps or future opportunities which employees value alongside appropriate recognition and developmental support.

When addressing areas for improvement, AI Coach promotes established frameworks to ensure feedback is effective and motivational:

Reviews are perceived as higher quality when they include appropriate recognition and reference specific examples from the review period, rather than generalities.

Employees also value managers who show interest in their aspirations, provide development opportunities, offer appropriate recognition, and help them understand future career possibilities - signals AI Coach encourages managers to include in their review and follow-up conversation.

AI Coach in Performance prepares the manager for a fair, constructive conversation once a review is complete, using the same core coaching principles as General AI Coach.

AI Coach in Performance uses personalized, contextual, and science‑backed coaching to help the manager move from reflection to action with confidence, in a similar way to General AI Coach.

AI Coach in Performance draws on familiar, practical tools so the manager can structure messages, practice delivery, and land clear next steps. These are the same that underpin our General AI Coach.

By combining these principles with coaching frameworks and practical tools, AI Coach in Performance helps the manager hold a constructive conversation that reinforces strengths, addresses growth areas, and ends with clear actions.

Self-reflections give employees a chance to bring their own perspective into the review, sharing context and achievements a manager might otherwise miss. But writing one well means looking back across months of work, and pulling that together from memory is hard. Recency bias pulls focus to the last few weeks, and the evidence is scattered across feedback, Shoutouts, and earlier reflections. To assist, Coach pulls relevant feedback from across the review period and groups it into themes so the employee has clear evidence to support their writing.

Coach reads the questions on the employee's reflection and pulls relevant content from the past 12 months across peer and upward feedback, previous self-reflections, anytime feedback, Shoutouts, past manager reviews, and performance ratings. It works only with data that the employee already has permission to see.

It groups what it finds into themes around strengths, impact, challenges, and growth areas, with citations back to the original feedback so the employee can verify what they're reading. The 12-month window can be shortened by asking Coach directly, for instance to focus on a single review cycle.

Example prompts the employee might use:

If there isn't enough feedback data to draw on, Coach will say so, and the employee can still use the drafting prompts to get started on the process.

Coach helps employees draft concise, evidence-based responses to reflection questions. The most useful self-reflections are specific, grounded in outcomes, and written in the employee's own voice. Their purpose is to give managers context and perspective they wouldn't otherwise see, providing better evidence to work from.

Coach starts by asking the employee for their own observations, then weaves in supporting examples from their feedback. All the while, the reflection stays in the employee's voice. By design, Coach won't write a finished reflection on someone's behalf, recommend a performance rating, or make calls on HR decisions. It will adjust tone, length, or wording on request.

For the boundaries that apply across all of Coach, see What AI Coach Can't Do.

Example prompt the employee might use:

A reflection works best when it's honest and specific. Ultimately, the employee, not Coach, decides what's worth including.

Once the reflection is submitted, Coach's focus shifts to helping the employee prepare for the performance conversation with their manager. The purpose is not to script the conversation, but to help employees organize their thinking, anticipate likely discussion points, and participate in the conversation with more clarity and confidence.

The default prompts change after submission to match this new task:

In practice, Coach can help employees review the themes in their reflection, clarify the points they most want to communicate, think through how to talk about challenges or areas where their manager may see things differently, and prepare to ask for support, development, or new opportunities. The benefit is a more balanced two-way conversation: when employees come in prepared, the discussion can focus on growth and next steps rather than one-way feedback delivery.

Example prompts the employee might use:

Ultimately, Coach is a preparation aid, not a substitute for the conversation itself. The employee decides what to raise, how to raise it, and what context matters most.

Themes are recurring concepts or patterns across multiple survey questions. Focusing on themes helps you discover the relationships between data points instead of treating each question in isolation. Engagement outcomes are influenced by clusters of related experiences, so looking across signals leads to better diagnosis and more effective action planning.

AI Coach in Surveys identifies and prioritizes themes relevant to your context by considering question and factor scores, impact ratings to the index, questions recommended by the Focus Agent, user-selected questions flagged for focus, and topical relationships between questions.

For a full list of data used in AI Coach in Surveys, see What Data Does Coach in Surveys Use?

This complements your analysis by revealing connections that might be missed if you just focus on single questions. In most cases, you will see two to three underlying themes per session to keep guidance focused and actionable. You can ask for more or fewer themes, dig deeper to explore why patterns may have emerged or what they potentially mean, or explore a hypothesis that you might have.

Coach does not just summarize the whole survey to give you themes; it can help you answer very specific questions about team dynamics, particular topics, or challenges unique to your group.

Example prompts:

AI Coach in Surveys combines your survey signals with your context to suggest tailored actions or goals. It considers question and factor scores, impact ratings, Focus Agent recommendations, your role and organization context you provide, plus any additional details you share such as audience, constraints, timing, or stakeholders.

When generating actions or goals, AI Coach in surveys will ask clarifying questions or prompt you to add context. This helps refine recommendations so they fit your situation.

The intent is to turn the most influential drivers into specific, feasible behaviors. You should expect suggestions that:

Example prompts:

Provide more context:

AI Coach in Surveys can draft messages for different audiences and formats using the themes and actions identified, and any context you share about stakeholders, tone, or communication goals. The approach reflects principles that support buy-in and change:

You can request concise executive updates, team summaries, or all-company messages that explain what you learned and what will happen next.

Example prompts:

Employees may hold a narrower view of their strengths than the evidence supports, particularly when working from memory. When asked, Coach reviews the employee's feedback to surface concrete examples of strengths in action, then connects those strengths to the competencies in their career path, where available.

Contributions like mentoring and cross-functional collaboration are easy to overlook: they rarely attach to a single deliverable, and they tend to be under-recorded and may be undervalued as a result. When this kind of contribution does appear in the feedback, Coach gives it weight rather than passing over it. It can prompt the employee to weigh evidence they might have set aside in the past, instead of just looking at things that confirm their existing view.

Example prompts the employee might use:

If there's little or no feedback to draw on, Coach can't generate a Strengths in Action summary. It will advise the employee, then shift to the employee's own experience, asking a reflective question to surface strengths that aren't captured in the feedback.

A development objective sets the direction for the whole plan: where the employee wants to grow over the next six months, and why. It's the focus the later goal is built on, not the goal itself. Objectives are stronger when they sit at the intersection of individual aspirations, current capability, and business alignment.

Coach uses a coaching approach to help the employee explore what they care about, where they want to take their career, and what their feedback says about areas of potential. Once they've done that thinking, Coach can offer a draft objective to react to. If feedback consistently points to leadership as a strength or opportunity, for example, Coach may raise it as a direction worth exploring while leaving the decision with the employee.

Example prompts the employee might use:

Coach won't decide the objective for the employee. It can however offer a draft as a starting point, grounded in what they've surfaced, then invite them to adjust the focus or take it in a different direction.

Once the direction is set, Coach helps the employee decide which areas to prioritize. It surfaces relevant growth themes, drawing on what's in the plan and, where useful, the employee's feedback, and helps them weigh up which ones to focus on. Where the employee's role is mapped in Career Pathways, Coach adds another layer, connecting those themes to the competencies the role calls for so development lines up with what the role expects.

Either way, Coach can show what the feedback raises, but it can't know which areas matter most for a particular person in their situation. Those priorities are the employee's to set; and a good thing to talk through with their manager in the development conversation.

Example prompts the employee might use:

If the objective is where the employee wants to grow, the goals are the specific steps they'll take to get there. Coach helps the employee draft a development goal that sits at the intersection of their strengths, motivators, and growth areas, then keeps them in control of the result.

The focus stays on building a skill or capability rather than hitting a metric, because development grows what someone can do, not just what they produce.

Coach won't finalize a goal for the employee, as research shows that people commit more to goals they set themselves. No goal is saved to the plan until the employee has reviewed, edited, and confirmed that they're happy with it. While Coach can assist, ultimately the draft will reflect what the employee puts in. The more thinking they bring to the earlier steps, the more concrete and useful the goal that comes out.

Example prompts the employee might use:

Once a goal is drafted, Coach can also help the employee prepare to discuss it with their manager: clarifying their main ask, connecting the goal back to their motivators, strengths, and growth areas, thinking through likely obstacles, and agreeing when to check in. Coach guides the drafting and the preparation, while the decisions stay with the employee.

For the boundaries that apply across all of Coach, see What AI Coach Can't Do.

Coach helps the employee shape a goal in three parts: