Accelerated Innovation

Using Stakeholder Feedback to Improve GenAI Agents

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Using Stakeholder Feedback to Improve GenAI Agents

Description

Collecting and acting on stakeholder feedback helps teams continuously improve the quality, performance, and usefulness of GenAI agents. This capability focuses on designing structured feedback loops that capture input from end users, reviewers, and subject matter experts across real-world use.

Why it's Important

Even the best-designed agents require refinement after deployment. Stakeholders provide essential insights about whether agents are accurate, helpful, trustworthy, or aligned with business goals. Without clear mechanisms to gather and apply this input, agents stagnate or drift off course. By integrating feedback directly into product and model development cycles, teams can close performance gaps, boost adoption, and increase user satisfaction. Feedback-driven improvement turns GenAI into a responsive system that evolves based on real-world usage and stakeholder needs.

Why it's Challenging @ Scale

  • Unstructured or inconsistent feedback. Without standardized input formats, it’s difficult to interpret or compare feedback across users and teams.
  • Low participation rates. Users often skip feedback prompts or provide minimal input, especially if there’s no clear incentive or follow-up.
  • Delayed or manual processing. Feedback may sit unused if there’s no system in place to route it to product, design, or model teams for action.
  • Difficulty linking feedback to behavior. Without context (e.g., what prompt was used, what tool was called), it’s hard to trace issues back to root causes.
  • Lack of feedback visibility. Teams may miss patterns if feedback remains siloed or is not aggregated for shared review.

Complexity

High. Maturing this capability requires cross-functional workflows, integration into agent platforms, and scalable systems to collect, tag, route, and apply insights from feedback.

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Taking Action

Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.

The most important part of any journey is starting… To move from “Exploring” to “Experimenting”, focus on the following key actions:
  • Explore Key Concepts & Best Practices: Complete the Building Extensible GenAI Solutions (Routers, Tools & Agents) workshop (2 hrs.) to understand foundational key concepts and explore applied best practices
  • Exploring Extensibility in GenAI Architectures
  • Reviewing Core Router, Tool, and Agent Concepts
  • Identifying Use Cases for Modular Expansion
  • Aligning Extensibility to Business and Tech Goals
  • Planning for Long-Term Maintainability
  • Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy.
  • Align on your Current State and define your Target State
  • Create an actionable enablement plan
  • Define target timeline and measures of success
  • Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame.
  • Launch lightweight feedback forms: Embed a simple thumbs-up/thumbs-down or 1-5 rating system into a GenAI pilot to begin capturing user sentiment.
  • Tag and route early feedback manually: Set up a shared inbox or spreadsheet where feedback is collected, labeled, and reviewed weekly.
  • Identify one feedback-to-action example: Choose a clear user insight and use it to revise a prompt, modify agent instructions, or retrain a model response.
To move from Experimentation to “Lifting-Off,” prioritize the following actions:
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Core Concepts & Capabilities of AI Agents
  • Selecting Your Agent Architecture
  • Curating Your Agent Data
  • Defining Agent Workflows with Prompts & Outputs
  • Baselining & Optimizing Your Agent Performance
  • Visualizing Agent Interactions & Data
  • Automating & Integrating AI Agents in Workflows
  • Integrating AI Agents into your Business & Go-to-Market Strategy
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale
  • Assess Your Proposed Solution or Process: Review how feedback is being collected, tracked, and applied within your current GenAI pilot efforts.
  • Define in-scope Processes and Guardrails: Establish clear criteria for what types of feedback require immediate action, escalation, or deferral.
  • Close any Data or Measurement Gaps: Link user feedback to specific prompts, tools, or outputs to identify patterns and target improvements.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units
  • Define Your Phased Implementation Plan: Expand feedback collection to multiple use cases or user segments with common data formats.
  • Build Awareness and Finalize Enablers: Provide teams with simple mechanisms (e.g., templates, dashboards) to review and act on feedback.
  • Operationalize Your Comms Plan: Let stakeholders know how their input is being used to improve agent quality and functionality.
To move from Lifting-Off to “Accelerating,” prioritize the following actions:
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases
  • Standardize Feedback Taxonomies: Define clear categories (e.g., accuracy, tone, relevance) to classify and route incoming feedback.
  • Create Feedback-to-Action Workflows: Build repeatable processes that link feedback intake to specific update or escalation actions.
  • Integrate Feedback Review into QA: Ensure that structured stakeholder input is reviewed regularly alongside performance metrics.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers
  • Automate Feedback Capture in Production: Collect structured feedback through live interactions, embedded widgets, or follow-up surveys.
  • Share Feedback Trends with Teams: Create visibility into common requests or issues through dashboards or regular insight reports.
  • Empower Teams to Act on Feedback: Equip product, content, and engineering teams with the tools and authority to implement fixes or enhancements.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum
  • Showcase Improvements Based on Input: Share before-and-after examples where stakeholder feedback directly improved agent performance.
  • Highlight Feedback Champions: Recognize users or team members who consistently provide valuable, actionable insights.
  • Track and Share Impact Metrics: Report how feedback integration has led to reduced error rates, higher satisfaction, or improved usability.
The “Accelerating” stage represents “Target State” for many capabilities. “Breaking Away,” on the other hand, suggests that the specific capability represents a clear competitive advantage for your business.
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine
  • Embed Feedback Loops into Authoring Tools: Allow prompt designers and product teams to view recent feedback while editing agent content.
  • Close the Loop with Users: Automate messages that let stakeholders know when their input led to a meaningful change.
  • Make Feedback a Default Interaction: Normalize feedback collection as part of every GenAI touchpoint, including chat, voice, and document generation.
  • Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort
  • Auto-tag and summarize feedback: Use NLP models to categorize and prioritize open-ended feedback for human review.
  • Trigger real-time routing: Automatically send urgent feedback (e.g., safety issues or functional errors) to the appropriate triage team.
  • Update agent instructions dynamically: Enable systems that adapt prompts or outputs based on aggregated, validated feedback signals.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases
  • Track Feedback Quality Over Time: Measure the richness, usefulness, and actionability of feedback across different user types or use cases.
  • Build Cross-Team Feedback Networks: Create shared processes for collecting and applying feedback across multiple agent initiatives.
  • Benchmark Feedback-Driven Improvements: Monitor and compare the performance of agents before and after feedback-driven changes to validate impact.

Key "Watchouts"

As you take action you’ll want to avoid:

  • Collecting feedback with no follow-through: Asking for input without making changes reduces trust and discourages future participation.
  • Failing to route feedback to the right teams: Without clear ownership, even high-value insights may sit untouched.
  • Over-indexing on one-off comments: Isolated feedback can be misleading if it isn’t supported by broader patterns or data.
  • Creating feedback fatigue: Repetitive or poorly timed requests can frustrate users and reduce engagement.
  • Lacking visibility into feedback outcomes: Teams need shared views of what feedback was received, acted on, or dismissed and why.

Targeted Benefits

While Using Stakeholder Feedback to Improve GenAI Agents can be challenging, its benefits are clear and compelling, including:

  • More relevant and usable outputs: Feedback helps tailor agents to real-world needs and expectations.
  • Faster identification of blind spots: Users often catch issues that internal testing may miss.
  • Higher satisfaction and trust: Stakeholders are more engaged when they see their input making a difference.
  • Improved cross-functional collaboration: Feedback processes bring product, design, and engineering teams into closer alignment.
  • Continuous, data-informed evolution: Real-time feedback supports agile updates and keeps agents improving after launch.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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