Accelerated Innovation

Making ‘Proceed to Dev’ GenAI Decisions

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Making 'Proceed to Dev' GenAI Decisions

Description

Making “Proceed to Dev” Decisions for GenAI solutions involves using clear, evidence-based criteria to determine whether a GenAI project should proceed to scaling, pivot for refinement, or stop altogether. This capability ensures that decisions are based on real-world data rather than intuition or internal momentum.

Why it's Important

Without disciplined go/no-go decisions, organizations risk over-investing in GenAI initiatives that lack impact, scalability, or strategic alignment. Data-driven evaluations help identify which projects are ready for scale, which require additional iteration, and which should be de-prioritized, saving time, reducing costs, and focusing resources on the most valuable GenAI solutions. This structured decision-making process builds stakeholder confidence and accelerates learning across the organization.

Why it's Challenging @ Scale

  • Incomplete or Inconsistent Data: Early-stage GenAI projects often lack standardized data collection, making it difficult to compare results objectively.
  • Emotional or Political Bias: Teams may become attached to projects, making it hard to say “no” even when the data suggests otherwise.
  • Misaligned Success Metrics: Different stakeholders may define success differently, leading to conflicting interpretations of results.
  • Evolving Market and Technical Conditions: What was a good idea at the start may no longer make sense given new technical constraints or market shifts.
  • Cross-Functional Decision Complexity: Go/no-go decisions require input from technical, business, compliance, and UX teams-often slowing the process.

Complexity

High: Making “Proceed to Dev” GenAI Decisions at scale requires aligned success metrics, transparent data collection, and the discipline to follow the evidence, regardless of internal momentum or bias.

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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 Developing High-Impact GenAI Solutions workshop (2 hours) to understand foundational key concepts and explore applied best practices.
  • Exploring GenAI Solution Patterns and Frameworks
  • Identifying High-Impact Use Case Characteristics
  • Aligning Solution Design with Customer and Market Needs
  • Planning for Experimentation and Iterative Development
  • Defining MVP Success Criteria and Hypothesis Testing
  • 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.
  • Draft Go/No-Go Decision Criteria: Define initial success metrics and stop/pivot/scale thresholds for GenAI pilots.
  • Launch a Pilot with Data Tracking: Run an early GenAI test case with built-in data collection to evaluate performance against criteria.
  • Document Early Learnings and Gaps: Capture lessons from the first few pilots to refine decision-making processes.
To move from Experimenting to Lifting-Off, prioritize the following actions:
  • Complete One or More Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Understanding Your GenAI Customer
  • Testing & Validating High-Potential GenAI Ideas
  • Developing & Supporting High-Impact GenAI Solutions
  • Accelerating Adoption of Your GenAI Solutions
  • Insights-Driven GenAI Solution Optimization
  • 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 whether the solution meets defined success metrics for technical feasibility, adoption, and business value.
  • Define In-Scope Processes and Guardrails: Create clear guidelines for when to stop, pivot, or scale based on real data, not stakeholder opinion.
  • Close Any Data or Measurement Gaps: Ensure consistent, repeatable data collection across GenAI pilots to support informed decision-making.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how go/no-go decision processes will be rolled out across teams, workflows, or business units.
  • Define Your Phased Implementation Plan: Expand decision-making frameworks from pilot projects to broader GenAI programs.
  • Build Awareness and Finalize Enablers: Provide templates, decision frameworks, and dashboards to support data-driven decisions.
  • Operationalize Your Comms Plan: Communicate decisions and their rationale transparently to build trust and alignment across teams.
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.
  • Publish a Go/No-Go Decision Framework: Create an enterprise-wide template for consistent GenAI decision-making.
  • Define Standard Success Metrics and Thresholds: Establish clear KPIs for technical performance, customer adoption, compliance, and business value.
  • Integrate Decision Reviews into Delivery Pipelines: Make stop/pivot/scale decisions a formal checkpoint in solution development workflows.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers.
  • Expand Decision Frameworks Across Teams: Ensure all GenAI initiatives follow the same go/no-go practices.
  • Enable Self-Service Decision Tools: Provide dashboards and calculators that help teams evaluate project data and recommend next steps.
  • Establish a Regular Review Cadence: Create monthly or quarterly meetings to review project data and make transparent go/no-go calls.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain momentum.
  • Highlight Decisions That Saved Resources: Share examples where stopping or pivoting prevented wasted effort or cost.
  • Showcase Successful Scale Decisions: Highlight projects that met criteria and delivered strong business outcomes after scaling.
  • Recognize Data-Driven Decision Champions: Celebrate individuals or teams who model objective, transparent GenAI decision-making.
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 Decision Frameworks into Product Management Tools: Allow teams to track success metrics and decision points directly in delivery platforms.
  • Provide Real-Time Performance Dashboards: Deliver live views of technical, adoption, and business impact data to inform decisions.
  • Align Decision Reviews with Strategic Planning Cycles: Ensure go/no-go decisions are part of quarterly and annual GenAI program reviews.
  • Leverage Automation: Using GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort.
  • Automate Success Metric Tracking: Use automated dashboards to collect and update performance data in real time.
  • Auto-Generate Decision Summaries: Use GenAI to draft executive summaries that recommend stop, pivot, or scale actions based on data.
  • Integrate Risk and Compliance Checks: Build automated reviews into decision workflows to assess risk alongside performance.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases.
  • Refresh Decision Criteria Based on Learnings: Use historical data to refine what success looks like for GenAI solutions.
  • Expand Data-Driven Decisions to New Domains: Apply stop/pivot/scale frameworks to all AI and emerging tech initiatives.
  • Benchmark Decision Maturity Against Competitors: Compare your decision-making processes to peers to identify areas for further acceleration.

Key "Watchouts"

As you take action, you’ll want to avoid:

  • Letting sunk cost bias drive decisions: Teams may push to scale solutions they’ve already invested in, even when the data says stop or pivot.
  • Defining success too loosely: Vague metrics lead to subjective decisions, make success thresholds clear and measurable.
  • Relying only on technical metrics: Adoption, usability, and business value must be part of the decision-not just model performance.
  • Overcomplicating decision frameworks: Too many inputs slow decisions and create analysis paralysis.
  • Failing to communicate outcomes transparently: Without clear explanations of go/no-go decisions, trust and momentum can erode.

Targeted Benefits

While Making “Proceed to Dev” Decisions for GenAI Solutions can be challenging, its benefits are clear and compelling, including:

  • Faster, more objective decision-making: Data-driven frameworks reduce bias and accelerate innovation cycles.
  • Higher ROI on GenAI investments: Resources are focused on the solutions that actually deliver value.
  • Stronger cross-functional alignment: A shared process builds collaboration between technical, business, and compliance teams.
  • Reduced risk of scaling the wrong solution: Disciplined stop/pivot/scale decisions help prevent large-scale missteps.
  • Clear competitive differentiation: An organization that makes faster, smarter decisions moves ahead of competitors.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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