Accelerated Innovation

Participating in an AI Evaluation Community of Practice

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Participating in an AI Evaluation Community of Practice

Description

This capability focuses on building and participating in a cross-functional community dedicated to the continuous improvement of AI evaluation practices. It ensures knowledge is shared across teams, use cases, and maturity levels to support scalable and effective GenAI adoption.

Why it's Important

AI evaluation is a fast-moving and often fragmented space, where teams risk duplicating effort or missing emerging best practices. A well-supported Community of Practice (CoP) helps organizations avoid silos by creating shared norms, reusable artifacts, and trusted feedback loops. It enables peer learning, surfaces real-world insights, and fosters a culture of continuous experimentation. Most importantly, it ensures that evaluation excellence can scale with the business, regardless of org structure or use case diversity.

Why it's Challenging @ Scale

  • Lack of centralized knowledge-sharing practices: Without structured forums, teams may duplicate evaluation work or miss key lessons.
  • Siloed experimentation across teams: Evaluators often operate in isolation, limiting reuse of templates, tools, and learnings.
  • Limited visibility into what’s working: It’s difficult to scale practices when success stories and failures aren’t documented or shared.
  • Difficulty sustaining engagement over time: CoPs often lose momentum without dedicated ownership, incentives, or leadership sponsorship.
  • Inconsistent adoption of shared artifacts: Even when best practices exist, teams may resist change or prefer custom methods.

Complexity

High: Scaling a thriving Evaluation Community of Practice requires cultural change, aligned incentives, shared tooling, and sustained cross-functional engagement.

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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.

  • Explore Key Concepts & Best Practices: Complete the Enterprise Evaluation Driven Development As-a-Service (EDD EaaS) Best Practices workshop (2 hrs.) to understand foundational key concepts and explore applied best practices.
  • Defining EDD and its role in GenAI development.
  • Highlighting key metrics and evaluation objectives.
  • Introducing tools and architecture needed for EDD.
  • Scoping evaluation types across development stages.
  • Planning initial pilots to validate EDD frameworks.
  • 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 a CoP pilot forum: Stand up a lightweight pilot group focused on GenAI evaluation practices and shared learnings.
  • Share a starter kit of evaluation resources: Create and distribute curated starter assets like templates, FAQs, and case studies.
  • Spotlight early evaluation champions: Recognize team members who demonstrate leadership in AI evaluation efforts.
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Defining Your EDD EaaS Strategy & Governance Framework.
  • Pre-Production EDD EaaS Best Practices.
  • EDD EaaS CI/CD Integration Best Practices.
  • Enterprise EDD Production Guardrails & Monitoring.
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale.
  • Assess Your Proposed Solution or Process: Evaluate how current community efforts are driving behavior change and knowledge reuse.
  • Define in-scope Processes and Guardrails: Identify what participation norms, content standards, and governance policies will apply.
  • Close any Data or Measurement Gaps: Ensure participation metrics, engagement feedback, and CoP outcomes are being tracked.
  • 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: Start with high-priority evaluation teams, then expand CoP participation based on readiness.
  • Build Awareness and Finalize Enablers: Provide communication, tooling, and incentives to support consistent engagement.
  • Operationalize Your Comms Plan: Establish clear channels and cadences to promote CoP activities, goals, and impact stories.
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases.
  • Codify evaluation sharing protocols: Publish clear expectations for how and when teams contribute to the CoP.
  • Create reusable engagement templates: Develop standard templates for CoP meetings, knowledge shares, and evaluation playbooks.
  • Integrate CoP activities into workflows: Embed participation expectations into evaluation team OKRs or onboarding materials.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers.
  • Expand CoP to adjacent teams and functions: Broaden participation to include model developers, data owners, and governance leads.
  • Launch thematic working groups: Enable sub-communities to focus on specialized topics such as fairness, reliability, or cost-efficiency.
  • Introduce incentives for active contributors: Recognize and reward teams that regularly share assets, insights, or evaluations.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum.
  • Highlight CoP success stories: Share real examples of how community knowledge helped improve AI evaluation outcomes.
  • Feature contributors in internal channels: Use newsletters, demos, or showcases to elevate standout participants.
  • Track and publish CoP impact metrics: Report on adoption, engagement, and reuse to reinforce value across the org.
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine.
  • Standardize CoP integration into evaluation lifecycle: Make community checkpoints part of standard project processes.
  • Embed community engagement in performance reviews: Reflect participation and knowledge sharing in role expectations.
  • Design easy-to-access knowledge hubs: Ensure reusable evaluation resources are organized, searchable, and continuously updated.
  • Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort.
  • Automate tagging and indexing of shared content: Use AI to categorize and surface relevant evaluation assets within the CoP.
  • Enable smart recommendations for CoP members: Suggest relevant working groups, content, or collaborators based on interests and roles.
  • Monitor engagement and trends in real time: Track CoP activity using automated dashboards to identify gaps and guide programming.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases.
  • Continuously evolve the CoP charter: Update goals and focus areas as business priorities and evaluation needs shift.
  • Support thought leadership and external sharing: Encourage select teams to represent internal CoP insights in industry forums.
  • Benchmark against leading evaluation communities: Regularly compare structure, tooling, and engagement to best-in-class CoPs.

Key "Watchouts"

  • Treating the CoP as a side project: Without leadership support and dedicated time, engagement will quickly stall.
  • Over-engineering the structure too early: Excessive formality can stifle momentum in the early stages of community building.
  • Failing to deliver tangible value: If members don’t gain insights, tools, or collaboration from participation, interest will fade.
  • Limiting participation to technical roles: Valuable insights are lost when evaluators, business users, and operations teams aren’t included.
  • Neglecting to measure and communicate impact: Without visibility into CoP success, it’s harder to justify continued investment.

Targeted Benefits

  • Faster learning cycles through shared knowledge: Teams gain from others’ experiments, avoiding duplicated effort and reinvented wheels.
  • Higher evaluation quality at scale: Reuse of best practices and artifacts leads to more consistent, rigorous evaluations.
  • Greater organizational alignment on GenAI: A community fosters a shared vocabulary, mindset, and strategic focus.
  • Stronger culture of experimentation and feedback: Encourages psychological safety and openness in evolving evaluation practices.
  • Accelerated innovation via trusted collaboration: CoPs unlock new ideas and cross-functional insights that wouldn’t emerge in silos.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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