Data sharing, processing, and security in AI Control Tower

  • Release version: Australia
  • Updated March 12, 2026
  • 5 minutes to read
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    Summary of Data sharing, processing, and security in AI Control Tower

    The AI Control Tower in ServiceNow provides configurable settings to manage data sharing, processing, and security for AI models, particularly large language models (LLMs). These settings help improve AI accuracy, handle datacenter traffic efficiently, monitor data integrity, detect security threats, and ensure privacy compliance.

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    Data Sharing and Processing

    • Data Sharing: Enabled by default to contribute anonymized data to ServiceNow for enhancing AI accuracy and user experience. Customers can opt out if they prefer not to share data, but this disables their contribution to AI improvements.
    • Data Overflow Processing: Manages Now Assist traffic within ServiceNow datacenters by default, with automatic redirection to Microsoft Azure datacenters during traffic spikes to maintain performance. Customers can opt out to restrict traffic exclusively to ServiceNow datacenters. This feature is inactive by default.
    • Read-Only Access: For multi-instance setups, data sharing and overflow processing settings are available in sub-production instances in read-only mode.

    Security & Privacy Configurations

    • Data Integrity Incident Detection: Tracks potential violations of LLM guardrail policies via a dashboard chart. Customers can activate or deactivate data collection. Configurable options include:
      • Security categories aligned with OWASP Top 10 and OpenAI model specifications
      • Sampling rate to balance AI call volume with data accuracy
      • Maximum AI calls per execution to manage resource usage
      • Single versus multiple LLM analyses for policy violation detection, with multiple analyses using majority consensus across supported LLMs
    • Agent Goal Deviation: Monitors AI agents for deviations from intended objectives, including unauthorized actions or prompt injections. Configuration parallels data integrity settings with options for activation, sampling rate, max calls, and analysis types.
    • Output Screening: Detects AI output containing potential Personally Identifiable Information (PII) or security vulnerabilities such as injection attacks. Settings allow enabling collection and dashboard display of:
      • Security vulnerability patterns like XSS or SQL injection
      • Extended PII patterns including US driver’s licenses, passports, vehicle IDs
      • Standard PII patterns such as phone numbers and credit card numbers
    • Sensitive Data Input and Anonymization: Identifies and anonymizes sensitive information in LLM prompts based on data privacy patterns. Requires the Data Privacy plugin. Aids troubleshooting of sensitive data detection and anonymization charts.
    • Score Weight: Allows customization of how various LLM guardrail categories impact the overall security and integrity score, by adjusting or disabling categories. Scores are averaged across all managed AI assets.

    Practical Benefits for ServiceNow Customers

    • Enable data sharing to improve AI model accuracy and ServiceNow AI product capabilities, or opt out if data privacy is a priority.
    • Manage traffic overflow to maintain performance during spikes without losing control over data residency.
    • Monitor AI agent behavior and output for compliance with security policies and privacy regulations using configurable dashboards.
    • Customize detection sensitivity and analysis methods to balance accuracy, performance, and resource usage.
    • Ensure sensitive user data is detected and anonymized to meet privacy requirements.
    • Adjust scoring models to reflect organizational priorities in AI security and data integrity governance.

    Explore the Data sharing, processing, and Security & privacy sections.

    These settings help you improve AI models, manage datacenter traffic, and enabling metrics to measure the integrity of your data model and monitor potential threats in large language model (LLM) input and output.

    Data sharing

    By default, Data sharing is active. You can opt out to share your data with ServiceNow to improve AI accuracy, enhance user experiences, and gain a better understanding of business needs.

    Data sharing on the Configurations screen.

    Data sharing helps enhance ServiceNow products, but if you choose to opt out of the ServiceNow data sharing program, you’ll no longer be able to contribute data to improve ServiceNow AI products.

    For information on data sharing opt-out, see Opt out of data sharing.

    Data overflow processing

    By default, all Now Assist traffic is managed within ServiceNow datacenters. If there are traffic spikes, the system automatically redirects to Microsoft Azure datacenters to maintain performance. You can opt out of this feature to keep all Now Assist traffic exclusively within ServiceNow datacenters. By default, data overflow processing is inactive.

    Note:
    The Data sharing and Data overflow processing features are available for a sub-prod instance in read-only mode, when Multi-instance setup is configured and active.

    Security & privacy

    Data integrity incident detection
    These configuration settings control the Data integrity incident detection chart, which is designed to help show potential violations of certain LLM guardrail policies in LLM responses. To show data for this chart on the dashboard, select Configure, and then select Active. If you want to discontinue collecting data for the chart, clear Active.
    Note:
    If you inactivate the chart, past data shows on the chart for 90 days.
    You can configure these settings:
    • Categories – Security and content moderation policies grouped into categories that reflect industry practices that align with OWASP Top 10 Risk & Mitigations for LLMs and Gen AI Apps and the OpenAI model specification.
    • Sampling rate – The percentage of transactions that are evaluated. Selecting a rate lower than 100% results in fewer AI calls, but potentially less accurate data.
    • Max skill calls per execution – The amount of AI usage per call. The minimum is 10 calls; the default is 1,000 calls. Entering a lower number results in fewer AI calls, but potentially less accurate data.
    • Single or multiple analysis – Single analysis uses the default LLM to determine whether the model's output or behavior violates predefined security policies. Multiple analysis uses the results from three or more LLMs that ServiceNow supports to make a determination, using the majority result from the LLMs. Multiple analysis requires an odd number of LLMs.
    Agent goal deviation
    These configuration settings control the Agent goal deviation chart, which shows when AI agents may be deviating from their intended role or objective. For example, unauthorized actions or prompt injection attempts. To show data for this chart on the dashboard, select Configure, and then select Active. If you want to discontinue collecting data for the chart, clear Active.
    Note:
    If you inactivate the chart, past data shows on the chart for 90 days. Due to the probabilistic nature of the data model, not all occurrences may be identified.
    You can configure these settings:
    • Sampling rate – The percentage of transactions that are evaluated. Selecting a rate lower than 100% results in fewer AI calls, but potentially less accurate data.
    • Max skill calls per execution – The amount of AI usage per call. The minimum is 10 calls; the default is 1,000 calls. Entering a lower number results in fewer AI calls, but potentially less accurate data.
    • Single or multiple analysis – Single analysis uses the default LLM to determine whether the AI agent's or skill's response diverges from the expected output. Multiple analysis uses the results from 3 or more LLMs to make a determination, using the majority result from the LLMs. Multiple analysis requires an odd number of LLMs.
    Output screening
    These configuration settings control the AI agent output with PII detected and Agentic output injection detection charts, which show when agents' LLM output contains potential PII or potential security-vulnerable patterns. To show data for these charts on the dashboard, select Configure, select Active, and then select a setting for the data to collect. If you want to discontinue collecting data for the charts, clear Active.
    Note:
    If you inactivate the charts, past data collected shows on the charts for 90 days.
    You can configure these settings:
    • Output Security Vulnerability – Collect and show data in the Agentic output injection detection chart. The data is collected by analyzing LLM output for known potential vulnerable patterns and potential corresponding attack vectors. For example, HTML tags shouldn't have scripts associated with them for cross-site script attacks (XSS), or stacked SQL queries could result in SQL injection attacks.
    • Output Extended PII – Collect more potential PII data occurrences and show in the AI agent output with PII detected chart. The data is collected by analyzing LLM output for additional potential PII data patterns beyond those specified in Data Privacy. These PII data patterns include U.S. CA drivers license, U.S. passport number, and vehicle ID number.
    • Output PII Violation – Collect and show data in the AI agent output with PII detected chart. The data is collected by analyzing LLM output for potential PII sensitive data patterns specified in Data Privacy. For example, U.S. phone number or credit card number.
    Sensitive data input and anonymization
    This section shows the data patterns enabled in Data Privacy to detect and anonymize information in LLM prompts. Use this view as a quick reference when troubleshooting Sensitive data detected and Sensitive data anonymized charts. This feature requires the Data privacy plugin to be installed. For more information on how the data is sent and stored, see User data usage policy for Now Assist.
    Score weight
    This setting controls how the LLM guardrail categories that comprise the score are weighted. You can change the default weights or remove categories from the score by deactivating them. The score formula is an average across all managed AI assets.
    AI asset security score configuration with default weights shown.