--- sourceDocument: Australia Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/australia/intelligent-experiences Release : - australia ft:locale : - en-US ft:publication_title : - Australia Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Engagement dashboard # ServiceNow AI Engagement dashboard {#ariaid-title1} Release version: Australia Updated August 3, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of ServiceNow AI Engagement dashboard The ServiceNow AI Engagement dashboard delivers comprehensive insights into user adoption, utilization patterns, and performance of AI systems within your ServiceNow instance. It enables administrators and stakeholders to monitor real-time and historical engagement metrics, helping identify adoption opportunities, underutilized systems, and productivity improvements driven by AI automation. Show full answer Show less Accessible via AI Control Tower (All \> AI Control Tower \> Home \> Insights \> ServiceNow AI \> Engagement), this dashboard offers a centralized view to track how AI capabilities are being leveraged across your organization. ## Key Features * **Total AI Actions:** Displays the cumulative number of LLM-related actions initiated over a selected period, with trend and percentage change indicators to assess overall AI adoption velocity and usage trends. * **Average AI Users:** Shows the average unique users engaging with AI systems, with trends to monitor growth or decline in user adoption over weekly or monthly intervals. * **AI Systems with No Usage:** Lists AI systems without recorded user interactions during the selected period, helping identify underutilized systems that may need additional enablement or configuration. * **Percentage of Tasks Closed Using AI Systems:** Indicates the share of tasks completed with AI assistance, tracking how AI adoption influences task completion efficiency over time. * **AI Adoption by Country:** Breaks down AI usage by geographic region, highlighting highest and lowest adoption areas to prioritize regional enablement and benchmarking efforts. * **Usage by Department:** Visualizes AI engagement across top organizational departments, showing unique user counts and proportional usage to target enablement and recognize adoption leaders. * **Top 5 AI Systems by Department:** Identifies the most frequently used AI systems by department, supporting resource allocation and aligning AI systems with departmental needs. * **Task Closure Efficiency Gain:** Measures improvement in task completion times when AI is used, providing a quantifiable metric for productivity benefits and business value of AI automation. ## Key Outcomes * Gain visibility into AI system adoption trends and user engagement across your ServiceNow environment. * Identify underutilized AI systems and geographic or departmental adoption gaps to inform targeted enablement strategies. * Measure and communicate the impact of AI on task efficiency and productivity improvements to stakeholders. * Optimize resource allocation and investment by understanding which AI systems deliver the most value by department. The ServiceNow AI Engagement dashboard provides visibility into user adoption, utilization patterns, and performance metrics across all AI systems in your ServiceNow instance. Monitor AI action volume, user engagement trends, departmental usage, and task efficiency gains to identify adoption opportunities and system effectiveness. ## Engagement dashboard overview {#md-servicenow-ai-engagement__engagement-overivew} The ServiceNow AI Engagement dashboard displays real-time and historical metrics that help administrators and stakeholders understand how AI systems are being adopted and used across the organization. Use this dashboard to track engagement trends, identify underutilized systems, and measure the productivity improvements delivered by AI automation. To view the ServiceNow AI Engagement dashboard on AI Control Tower, navigate to AllAI Control TowerHomeInsightsServiceNow AIEngagement. ## Total AI actions {#md-servicenow-ai-engagement__total_ai_actions} This metric displays the total number of LLM-related actions initiated during the selected period across all AI systems in your instance. The trend line shows cumulative action volume over time, and the comparison indicator displays the percentage change from the previous period. Use this metric to assess overall AI system adoption velocity and identify upward or downward trends in AI utilization across your organization. ## Average AI users {#md-servicenow-ai-engagement__average_ai_users} This metric shows the average number of unique users engaging with AI systems across all platforms during the selected period. The trend visualization indicates how user engagement is changing week-over-week or month-over-month. Track this metric to measure user adoption growth and to identify periods of increased or decreased engagement with AI capabilities. ## AI systems with no usage {#md-servicenow-ai-engagement__ai_systems_no_usage} This section lists all AI systems that did not record any user interactions or actions during the selected period. Each system is displayed as a separate item in the list. Use this section to identify underutilized or unused AI systems that may require additional enablement, user awareness, or configuration review. Common reasons for no usage include insufficient user adoption, lack of awareness, or systems awaiting initial roll out. ## Percentage of tasks closed using AI system {#md-servicenow-ai-engagement__pct_tasks_closed_ai} This metric displays the percentage of tasks that were completed with the assistance of an associated AI system during the selected period. The trend line illustrates how task closure efficiency changes over time, showing whether organizations are increasingly leveraging AI for task automation. Use this metric to evaluate the impact of AI systems on task completion workflows and to understand the correlation between AI adoption and operational efficiency. ## AI adoption by country {#md-servicenow-ai-engagement__ai_adoption_by_country} This section breaks down AI system adoption by geographic region, displaying both the highest and lowest adoption countries. Each country is represented with its adoption rate and the percentage change from the previous period. Use this geographic view to identify regional adoption gaps, prioritize enablement efforts in lower-adoption regions, and benchmark regional performance. ## Usage by department {#md-servicenow-ai-engagement__usage_by_department} This visualization shows the distribution of AI system usage across the top departments in your organization. The donut chart displays the number of unique users from each department interacting with AI systems and their proportional contribution to total usage. Use this section to identify which departments are leading AI adoption, to target enablement efforts toward lower-usage departments, and to recognize department-specific adoption champions. ## Top 5 AI systems by department {#md-servicenow-ai-engagement__top_5_ai_systems} This section displays the five most frequently used AI systems across the organization, broken down by the departments that use them. A horizontal bar chart shows usage volume for each system, with color coding to distinguish contributions by department (Customer Support, Engineering, and Others). Use this section to understand which AI systems are delivering the most value, to identify system-to-department alignment, and to guide resource allocation and investment decisions. ## Task closure efficiency gain {#md-servicenow-ai-engagement__task_closure_efficiency_gain} This metric measures the percentage of improvement in task completion time when AI systems are used. The trend line shows how efficiency gains are changing over the selected period, indicating whether AI system improvements or increased adoption are delivering measurable productivity benefits. Use this metric to quantify the business value delivered by AI automation and to communicate ROI to stakeholders. *[\>]: and then