10 ways AI can help managers get better at giving feedback

AI can improve how managers handle feedback, making the process better and way less stressful. Here are ten clever ways your managers can use AI to up their feedback game, complete with prompts and practical tips for using them responsibly.

1. Crafting clear + constructive feedback

AI can help you cut through the fluff and nail feedback that’s sharp, actionable and easy to digest. It’s like having an editor who knows exactly what you’re trying to say without the awkward phrasing. AI keeps feedback clear and on point, helping you managers get their messages across.

Why creating clear + constructive feedback is helpful: When your feedback is straightforward, employees can actually act on it. No confusion, no wasted time.

Sample prompt for crafting clear + constructive feedback: Draft feedback for an employee struggling with meeting deadlines. Focus on constructive suggestions for improvement.

Note: Don’t feed AI names, project details or anything else your HR team would side-eye.

Other considerations: Run AI suggestions by a trusted peer or tweak them to fit your style.

2. Providing tone analysis

AI can be a tone-check buddy, flagging language that might sound a little too sharp or wishy-washy. Let AI fine-tune your tone so your feedback sounds constructive instead of confrontational.

Why feedback tone analysis is helpful: A feedback conversation is already loaded. The wrong tone can derail the message entirely.

Sample prompt for feedback tone analysis: Analyze the tone of this feedback: ‘[insert drafted feedback message here]’ Suggest improvements for a supportive tone.

Note: Don’t use AI to analyze real emails. Paraphrase a hypothetical example instead.

Other considerations: Always add your personal touch. AI is great, but empathy doesn’t come preloaded.

3. Preparing for feedback conversations

AI can map out a game plan for feedback sessions, so you’re not fumbling through what to say. With AI on prep duty, you’ll feel more in control heading into tough conversations.

Why preparing for feedback conversations is helpful: A little prep can take the nerves out of a feedback session and make sure you cover all the bases.

Sample prompt for preparing for feedback conversations: Outline a step-by-step approach for delivering feedback to a team member about their declining performance.

Note: Don’t input specifics. Keep it general and hypothetical.

Other considerations: Use AI’s plan as a skeleton. Flesh it out with examples and solutions specific to your team.

4. Simulating difficult conversations

AI makes a decent practice partner for running through sticky feedback scenarios before the real deal. Practicing with AI lets you work out the kinks in your delivery before facing the real deal.

Why simulating difficult conversations is helpful: Practice helps you find the right words — and it keeps your foot out of your mouth when things get tricky.

Sample prompt for simulating difficult conversations: Simulate a conversation where I provide feedback to an employee who disagrees with their performance review.

Note: Keep the details broad. No names, no direct references to real-life situations.

Other considerations: After practicing with AI, ask a mentor to role-play for a real-world perspective.

5. Generating examples of balanced feedback

AI can whip up examples that combine constructive feedback with a healthy dose of acknowledgment for what’s going well. Balanced feedback keeps your team motivated without skirting the issues.

Why generating examples of balanced feedback is helpful: Employees need to know what they’re doing right so they don’t feel like they’re always under a spotlight for mistakes.

Sample prompt for generating examples of balanced feedback: Provide an example of balanced feedback for an employee who met most goals but missed a key deadline.

Note: Don’t include actual metrics or project names.

Other considerations: Use examples as a guide, but always tailor your delivery to the person in front of you.

6. Creating follow-up strategies

AI can suggest follow-up actions that keep employees moving in the right direction after feedback. These follow-up plans keep the momentum going after feedback, so it’s not just talk.

Why creating follow-up strategies is helpful: Feedback without follow-up is like a to-do list you never check again. Progress needs a plan.

Sample prompt for creating follow-up strategies: Suggest a follow-up plan after giving feedback to an employee about improving their communication skills.

Note: Don’t treat AI-generated plans as plug-and-play solutions. Adapt them to fit the employee and the context.

Other considerations: Schedule regular check-ins to make sure things don’t fall through the cracks.

7. Customizing feedback for different learning styles

AI can help you tailor feedback so it lands better with how each employee processes information. Tailored feedback meets employees where they are, not where you think they should be.

Why customizing feedback for different learning styles is helpful: Some people want step-by-step instructions. Others just need the big picture. Either way, tailored feedback is more likely to stick.

Sample prompt for creating feedback for different learning styles: What are some ways to tailor feedback for a visual learner versus a verbal learner?

Note: Don’t overthink learning styles on the spot. Focus on broad adjustments that align with what you already know about the employee’s preferences.

Other considerations: Periodically ask employees how they like to receive feedback. Preferences can shift over time, and keeping up shows you care about meeting their needs.

8. Reducing bias in feedback

AI can help spot unintentional bias in your language, keeping your feedback objective and focused on what really matters. Less bias means your feedback is more fair and professional.

Why it’s helpful to remove bias from feedback: Biased feedback undermines trust and can hurt morale faster than a late Friday email.

Sample prompt for reducing bias in feedback: Review this feedback for potential bias: ‘[insert feedback language here]’ Suggest a more objective phrasing.

Note: Keep examples fictional. Double-check AI’s suggestions with your company’s HR team if you want another review.

Other considerations: Consider bias training alongside using AI for a more rounded approach.

9. Tracking patterns in feedback

AI can analyze anonymized trends in your feedback over time, showing you where you’re killing it and where you need work. AI helps you see the big picture so you can refine your feedback game.

Why tracking feedback patterns is helpful: Spotting patterns lets you fix the stuff that isn’t working and double down on what is.

Sample prompt for tracking patterns in feedback: Analyze this anonymized data: ‘[insert data here]’ What trends do you see?

Note: Aggregate data only. Anything identifiable stays out.

Other considerations: Pair insights from AI with self-reflection and feedback from peers.

10. Building confidence in giving feedback

AI can suggest practical ways to keep your cool when delivering feedback, no matter how tough the situation. With prep and guidance from AI, you can stay calm and composed, making tough conversations just a little easier.

Why building confidence in giving feedback is helpful: Confidence keeps you steady, even when the feedback you’re giving feels like walking a tightrope.

Sample prompt for building confidence in giving feedback: What are some tips for delivering feedback with confidence in high-pressure situations?

Note: Focus on general advice, not specific workplace dynamics.

Other considerations: Test AI tips in a low-stakes setting to see what actually works for you.
Using AI for feedback doesn’t make your managers less human — it makes their feedback more effective. Just help your managers remember to keep it ethical, tweak what AI suggests and use their own judgment on the final plan for delivering feedback their teams can actually put to use.

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