COURSE CORRECT & SHARE OUT

Feedback Labs Members' Community Learning Site

Step 5: Course Correct & Share Out

In the Course Correct & Share Out step of an AI- and tech-enabled feedback loop, the goal is to turn insights into concrete, realistic changes and to clearly communicate those changes back to your community.

Course correction can mean anything from major strategy shifts to small but meaningful tweaks in how you work, guided by your earlier buy-in and design decisions, your resources, and what stakeholders actually asked for.

To avoid bottlenecks—like leaders only seeing reports weeks after a survey closes—you can use dashboards and tools to track actions, set SMART goals, assign owners, and schedule follow-ups. AI can help draft action plans, thank-you messages, community updates, and automate responsiveness, but humans remain responsible for checking every proposed goal, update, and message for feasibility, cultural sensitivity, and context.

Finally, sharing out what is changing—and what isn’t, and why—closes the loop, builds trust, and sets you up to open the next cycle of listening and improvement.

Typical Challenges Organizations Face

Here are two common challenges that we have found organizations experience in the Course Correction & Share Out stage of their feedback loop:

Reporting Delays

Leadership sees report 4 weeks after survey closes

Action Step

Bottlenecks and stoppage at one person or dept responsible for feedback process

Tech Tools & Use Cases

Here are two ways that we have found organizations using technology tools in the Course Correct & Share Out stage of their feedback loop:

Dashboards

Supporting Post Survey Engagement

Send automated community updates about how feedback was used
Responsiveness (automated thank-you or action alerts)

AI Tools & Use Cases

Here are two ways that we have found organizations using AI tools in the Course Correct & Share Out stage of their feedback loop:

Comprehensive organization and communication

Notion

SMART goal planning

Use generative AI to create action plans, develop SMART goals, determine output and deliverables, and set follow-ups/reminders to keep the organization on track

Ethical Considerations

Maintain Humanity and Control Workload

Course corrections need to be realistic
Humans are responsible for checking all potential goals, thank yous, etc.

Cultural Competence

Must maintain cultural sensitivity and context

Learn more about ethical considerations for using AI here.

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