Value templates in AI Control Tower
Value templates define how business value is measured and attributed to AI systems. They enable customization of value metrics to align with organizational priorities.
Value templates overview
Value templates serve as the foundation for value calculation. They define:
- What value means for your organization (hours, money, process efficiency, quality, risk reduction, etc.)
- How value is calculated from AI system activity (formulas, rules, data sources)
- Which systems contribute to specific value metrics (system-to-template mapping)
- How value is measured consistently across your AI portfolio
Without templates, dashboards would show generic metrics. With well-designed templates, dashboards communicate business value meaningful to your stakeholders.
Types of value templates
- Default templates
- Pre-configured templates provided by ServiceNow that apply automatically to all AI systems unless overridden. Examples include productivity gains templates, cost tracking templates, and generic engagement templates.
- Custom templates
- Organization-specific templates that you create to measure unique aspects of value relevant to your business. Examples might include customer satisfaction impact, risk reduction, compliance improvement, or domain-specific metrics.
- Industry templates
- Pre-built templates designed for specific industries (healthcare, finance, manufacturing, etc.) that capture industry-specific value metrics.
- System-specific templates
- Templates tailored to individual AI systems or system categories that measure value most relevant to those specific capabilities.
Template structure and components
Each value template contains:
- Template name: Unique identifier (e.g., "Customer Service Productivity", "Code Generation Speed")
- Description: Business context and use case
- Value metrics: The specific metrics calculated by this template (e.g., hours saved, quality improvement %, customer satisfaction )
- Data sources: Where measurement data comes from (AI system logs, business process metrics, external data)
- Calculation rules: Formulas or algorithms that derive value from raw data
- Associated systems: Which AI systems use this template
- Scope: Whether template is enterprise-wide or limited to specific systems/departments
- Owner: Person or team responsible for template maintenance
Template examples
- Example 1: Customer Service Productivity Template
- Measures how much human effort is saved by AI chatbots handling customer inquiries.
- Metric: Hours saved per resolved interaction
- Data source: ChatBot conversation logs, average handle time benchmarks
- Formula: (Avg human handle time - AI handle time) × Number of interactions handled
- Associated systems: Customer Service ChatBot, Support Agent
- Example 2: Code Generation Productivity Template
- Measures productivity gains from AI-assisted code generation.
- Metric: Developer hours saved, defect reduction
- Data source: Code generation tool usage logs, QA defect tracking
- Formula: (Lines generated by AI / Developer code generation rate) + (Defects prevented × Cost per defect)
- Associated systems: CodeAssist, Developer Agent
For more information about configuring the Value templates in AI Control Tower, see Configure Value insights.