AI-Powered Features Guide

Overview

Sizemotion uses AI throughout the platform to help you work smarter, write better feedback, identify patterns in performance data, and get actionable insights from reviews. Our AI features save time while improving the quality and fairness of your feedback and decision-making.

AI Features Available

• Feedback Writing Assistant: Generate draft feedback based on key points
• OKR AI Summaries: Automated progress reports and insights for objectives
• Standup AI Summaries: Daily team activity digests and blocker identification
• Review Cycle AI Summaries: Aggregated feedback themes and patterns
• Retrospective AI Insights: Action item suggestions and sentiment analysis
• 1:1 Brief AI Insights: Pre-meeting preparation with discussion topics
• Real-Time Meeting Support: Live AI assistance during discussions
• Tone Analysis: Ensure feedback is constructive and balanced
• Performance Insights: Identify trends and patterns across reviews
• Sentiment Analysis: Understand emotional tone of feedback
• Bias Detection: Flag potentially biased language
• Theme Extraction: Discover common patterns in feedback data

How AI Helps

• Save time: Draft feedback 5x faster, get instant summaries
• Consistency: Similar quality across all reviews and updates
• Fairness: Reduce unconscious bias in performance evaluations
• Specificity: AI prompts for concrete examples and evidence
• Discovery: Surface insights and patterns you might miss manually
• Preparedness: Walk into meetings with AI-generated briefs and context
• Actionability: Transform data into specific next steps

Feedback Writing Assistant

How It Works

1. Start writing a performance review or review cycle feedback
2. Click the "AI Assistant" button
3. Enter bullet points or rough notes
4. AI generates polished, professional feedback
5. Edit and customize the output
6. Insert into your review

Example: From Notes to Feedback

Feedback Types

The AI assistant adapts to different feedback contexts:

• Performance reviews: Balanced, forward-looking feedback
• Review cycles: Peer-appropriate tone and specificity
• Promotion cases: Evidence-focused, achievement-oriented
• Development plans: Coaching and growth-oriented

Customization Options

Adjust the AI output:

• Tone: Direct, supportive, formal, casual
• Length: Brief summary or detailed narrative
• Focus: Emphasize strengths, areas for growth, or balanced
• Style: Bullet points or prose

Tone Analysis

After writing feedback, click "Analyze Tone" to get:

• Positivity score: Balance of praise vs. criticism
• Specificity check: Are you giving concrete examples?
• Actionability: Does it suggest next steps?
• Readability: Is it clear and easy to understand?

AI-Generated Summaries

Sizemotion automatically generates intelligent summaries across multiple modules, saving you hours of manual report writing and synthesis.

OKR AI Summaries

Get automated progress reports for your objectives and key results:

What's Included

• Overall progress assessment: High-level summary of objective status
• Key result analysis: Which KRs are on track, at risk, or behind?
• Trend identification: Velocity changes and momentum shifts
• Risk flagging: Early warning for objectives unlikely to hit target
• Achievement highlights: Completed KRs and major milestones
• Blockers summary: Common obstacles mentioned in updates
• Recommended actions: Specific next steps to get back on track

When Summaries are Generated

• Weekly digest: Automated summary of all active OKRs
• Check-in reports: After key result updates are submitted
• End of quarter: Comprehensive OKR cycle retrospective
• On-demand: Click "Generate AI Summary" anytime

Example OKR Summary

Standup AI Summaries

Daily and weekly digests of team standup activity:

Daily Team Digest

• Team activity overview: What everyone is working on today
• Cross-team dependencies: Who's waiting on whom
• Blocker identification: All blockers mentioned, grouped by type
• Velocity indicators: Team momentum and progress patterns
• Celebration moments: Completed work and wins to recognize
• Missing updates: Who hasn't submitted a standup (for managers)

Weekly Insights

• Top themes: Most common work areas across the week
• Productivity patterns: High-output days and focus areas
• Recurring blockers: Systemic issues needing attention
• Collaboration heat map: Who's working with whom
• Participation trends: Consistency of standup submissions

Use Cases

• Skip-level check-ins: Understand team progress without micromanaging
• Resource allocation: Identify bottlenecks and redistribute work
• Retrospective prep: Data-driven discussion topics
• Stakeholder updates: Quick status reports for leadership

Review Cycle AI Summaries

Comprehensive analysis of multi-rater feedback cycles:

Individual Summaries

• Consensus themes: What multiple reviewers agree on
• Divergent feedback: Areas where opinions differ
• Strengths synthesis: Top 3-5 confirmed strengths
• Development priorities: Most mentioned growth areas
• Career readiness: Evidence for promotion or role change
• Blind spots: Self-assessment vs. peer perception gaps
• Suggested talking points: Topics for review discussion

Team-Wide Summaries

• Completion rate: Review cycle participation metrics
• Quality score: Depth and specificity of feedback given
• Sentiment distribution: Overall positivity across reviews
• Common themes: Organizational strengths and gaps
• Top performers: Consistently high-rated individuals
• Support needed: Employees flagged for additional coaching

Example Review Cycle Summary

Retrospective AI Insights

Turn retrospective discussions into actionable intelligence:

During Retrospective

• Theme clustering: Group similar feedback items automatically
• Sentiment analysis: Overall team mood and energy level
• Priority ranking: Which items got most votes/discussion
• Pattern detection: Recurring themes from past retros

Post-Retrospective Report

• Top insights: 3-5 most important takeaways
• Action item suggestions: Concrete next steps for each theme
• Owner recommendations: Who should drive each action
• Success metrics: How to measure if actions worked
• Timeline suggestions: Realistic deadlines for follow-through
• Risk assessment: Potential obstacles to implementation

Trend Analysis

• Recurring issues: Problems mentioned in multiple retros
• Improvement velocity: How fast team resolves issues
• Action item completion: Follow-through rate on commitments
• Sentiment trajectory: Is morale improving or declining?

1:1 Brief AI Insights

Walk into every one-on-one fully prepared with AI-generated briefs:

Pre-Meeting Brief Includes

• Recent activity summary: What they've been working on (from standups, OKRs)
• Performance snapshot: Latest review feedback and ratings
• Goal progress: OKR status and trajectory
• Blocker history: Recurring obstacles they've mentioned
• Career timeline: Time in role, promotion eligibility
• Previous 1:1 action items: What was committed last time
• Peer feedback themes: What others are saying about them
• Suggested topics: AI-recommended discussion areas

Suggested Discussion Topics

AI recommends topics based on:

• Time-sensitive: Upcoming deadlines, pending decisions
• Development focus: Skills they're working on
• Wins to celebrate: Recent accomplishments
• Concerns to address: Declining metrics or repeated blockers
• Career growth: Next role, promotion readiness
• Team dynamics: Cross-functional challenges

Example 1:1 Brief

Real-Time Meeting Support

AI assists you during live conversations and meetings:

Live 1:1 Assistant

During one-on-one meetings, AI provides:

• Smart note-taking: Automatically capture key points and decisions
• Action item detection: Flag commitments and follow-ups
• Topic suggestions: "Don't forget to discuss X" reminders
• Context retrieval: Quick access to relevant past notes
• Follow-up prompts: "Ask about progress on [previous action item]"

Retrospective Facilitator

AI helps guide retrospective discussions:

• Icebreaker suggestions: Questions to warm up the team
• Quiet voices: Detect who hasn't contributed, prompt for input
• Time management: Keep discussion on track with time alerts
• Parking lot: Automatically capture off-topic items
• Action generation: Convert discussions into concrete next steps

Review Conversation Guide

When delivering performance reviews:

• Talking point reminders: Ensure you cover all feedback themes
• Response tracking: Note employee reactions and concerns
• Development planning: Real-time suggestions for growth areas
• Sentiment monitoring: Gauge emotional response during conversation
• Next steps generation: Build action plan collaboratively

How It Works

1. Open the meeting view (1:1, retrospective, or review)
2. Click "Enable AI Assistant"
3. AI panel appears alongside your notes
4. Receive suggestions and prompts in real-time
5. Accept, edit, or dismiss AI recommendations
6. AI generates meeting summary at the end

Performance Insights

Individual Insights

For each employee, AI analyzes:

• Trend over time: Is performance improving, declining, or stable?
• Strengths: Most frequently mentioned positive themes
• Development areas: Common coaching points across reviews
• Feedback consistency: Do different reviewers see similar patterns?
• Promotion readiness: Alignment with next-level expectations

Team Insights

For managers and HR, see team-wide patterns:

• Top strengths: What's the team great at?
• Skill gaps: Where does the team need development?
• Sentiment trends: Is morale up or down?
• High performers: Who's consistently exceeding expectations?
• At-risk employees: Who might need more support?

Company Insights

Organization-wide analytics:

• Culture themes: What values emerge from feedback?
• Leadership effectiveness: How are managers perceived?
• Diversity of opportunity: Equal growth paths for all?
• Promotion equity: Fair advancement across demographics?
• Retention risk: Patterns correlated with turnover

Review Analysis

Sentiment Analysis

AI evaluates the emotional tone of feedback:

• Positive: Praise, recognition, strengths
• Negative: Criticism, concerns, areas for improvement
• Neutral: Factual observations
• Mixed: Both positive and negative elements

Use sentiment analysis to:

• Ensure balanced feedback (not too harsh or too soft)
• Spot overly negative reviews that might demoralize
• Identify genuine praise vs. generic positivity

Bias Detection

AI flags potentially biased language:

• Gender bias: "Aggressive" (often used for women), "Bossy"
• Age bias: "Digital native", "Old school"
• Personality-based: Focus on traits vs. behaviors
• Vague criticism: "Not a culture fit", "Difficult to work with"

Example flagged phrases:

⚠️ Potentially Biased	✅ Better Alternative
"She's too emotional"	"Could benefit from more data-driven decision making"
"Not a culture fit"	"Communication style differs from team norms"
"Abrasive"	"Could soften delivery when giving critical feedback"

Theme Extraction

AI identifies common themes across all feedback for a person:

• Technical skills: Most mentioned competencies
• Leadership: Influence, mentorship, decision-making
• Collaboration: Teamwork and communication patterns
• Ownership: Initiative and accountability
• Impact: Results and outcomes delivered

Smart 1:1 Suggestions

Before a 1:1 meeting, AI suggests discussion topics based on:

• Recent feedback themes
• Performance trends
• Career progression timeline
• Unresolved action items
• Peer feedback patterns

Privacy & Data Security

How We Use Data

• Your data stays yours: We don't train our AI on your company's reviews
• No sharing: Your feedback data is never shared with other customers
• Encrypted: All data encrypted in transit and at rest
• Anonymization: Team/company insights are aggregated and de-identified

AI Model

• Provider: OpenAI GPT-4 and Google Gemini
• Data processing: Temporary, not stored by AI provider
• Compliance: GDPR, CCPA, SOC 2 compliant
• Opt-out: Can disable AI features in settings

Control & Transparency

• Human in the loop: AI suggestions require your review
• Edit everything: All AI output is editable
• Audit trail: See when AI was used in a review
• Turn off anytime: Disable AI features per user or org-wide

Best Practices

✍️ Using the Writing Assistant

• Start with notes: Give AI context, don't rely on it from scratch
• Add specifics: Include examples, projects, metrics
• Edit output: Make it sound like you, not a robot
• Verify accuracy: AI can make up details—check everything
• Keep confidential info out: Don't include sensitive data in prompts

📊 Leveraging AI Summaries

• Review weekly: Make AI summaries part of your Monday routine
• Share with stakeholders: Use OKR and standup summaries in status updates
• Track patterns: Look for recurring themes across multiple summaries
• Drill down: Use summaries to identify areas needing detailed review
• Compare periods: Retrospective insights show progress over time
• Prepare efficiently: Read 1:1 briefs 10 minutes before meetings

🎯 Real-Time Meeting Support

• Enable at start: Turn on AI assistant before meeting begins
• Don't over-rely: AI assists, human connection still matters most
• Review suggestions: Quickly scan AI prompts during natural pauses
• Accept selectively: Use what's helpful, ignore what's not relevant
• Capture action items: Let AI track commitments while you focus on conversation

📈 Leveraging Insights

• Spot trends early: Use insights to catch issues before they escalate
• Inform development: Target training to team skill gaps
• Fair promotions: Use data to support promotion decisions
• Team planning: Understand strengths to assign projects
• Culture check: Monitor sentiment and adjust management style

⚖️ Bias Detection

• Don't ignore flags: Review and revise flagged language
• Focus on behaviors: Describe what people do, not who they are
• Be specific: Replace vague criticism with concrete examples
• Calibrate: Compare feedback across employees for consistency

💡 Pro Tips

• Iterate: Generate multiple versions, pick the best
• Mix AI + manual: Use AI for drafts, add personal touch
• Review insights quarterly: Spot trends you'd miss daily
• Share team insights: Help team understand collective strengths/gaps
• Benchmark: Compare your team to company averages (anonymously)
• Keep data fresh: AI summaries are only as good as your input data
• Experiment: Try different AI features to find what works for your workflow

Limitations & Considerations

What AI Can't Do

• Replace judgment: AI assists, you decide
• Understand context: Doesn't know team dynamics or history
• Be creative: Can sound generic without your editing
• Guarantee fairness: Can reduce bias but not eliminate it
• Replace relationships: Can't substitute for knowing your people

When Not to Use AI

• Sensitive situations: Write PIP or termination feedback yourself
• Highly personal: Unique achievements deserve personal recognition
• First impressions: Initial feedback sets tone—make it authentic
• Confidential matters: Don't include sensitive info in AI prompts

Getting Started

Enable AI Features

1. Go to Settings > AI & Insights
2. Toggle on the features you want to use
3. Set organization-wide preferences (admins only)
4. Review privacy and data usage policies
5. Save settings

User Permissions

• All users: Can use writing assistant for their own feedback
• Managers: Access insights for their teams
• HR/Admins: Company-wide insights and analytics

Next Steps

• Performance Reviews - Use AI writing assistant and insights
• Review Cycles - Get AI-generated feedback summaries
• OKRs - Automated progress summaries and insights
• Daily Standups - Team activity digests and blocker tracking
• Retrospectives - AI insights and action suggestions
• One-on-Ones - Pre-meeting briefs and real-time support
• Admin Settings - Configure AI features org-wide