--- sourceDocument: Australia Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/intelligent-experiences Release : - australia ft:locale : - en-US ft:publication_title : - Australia Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Data sharing, processing, and security in AI Control Tower # Data sharing, processing, and security in AI Control Tower {#ariaid-title1} Release version: Australia Updated March 12, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 5 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 Data sharing, processing, and security in AI Control Tower This guide details key settings in the AI Control Tower that help ServiceNow customers manage data sharing, processing, and security related to large language models (LLMs). These configurations enable customers to improve AI model accuracy, maintain datacenter performance, and monitor potential security and privacy issues arising from AI outputs and inputs. Show full answer Show less ## Data Sharing and Processing * **Data Sharing:** Enabled by default, allowing ServiceNow to use customer data to enhance AI accuracy and user experience. Customers may opt out, but opting out disables contribution to AI improvements. * **Data Overflow Processing:** By default, AI traffic is managed within ServiceNow datacenters. During traffic spikes, some processing may redirect to Microsoft Azure datacenters to sustain performance. Customers can opt out to restrict all AI traffic to ServiceNow datacenters only. This feature is inactive by default. * **Sub-production Instance Support:** Data sharing and overflow processing settings are available in read-only mode when multi-instance setups are active on sub-production instances. ## Security and Privacy Controls * **Data Integrity Incident Detection:** Configurable to monitor LLM responses for potential violations of security and content policies aligned with industry standards (e.g., OWASP Top 10). Settings include activation, sampling rate, max AI calls per execution, and single versus multiple LLM analysis to enhance detection accuracy. * **Agent Goal Deviation:** Tracks AI agents' behavior deviations such as unauthorized actions or prompt injection attempts. Configurable similarly to incident detection with options for activation, sampling, call limits, and analysis methodology. * **Output Screening:** Monitors AI output for potential personally identifiable information (PII) and security vulnerabilities. Settings allow activation and specify types of data collected, including extended PII patterns and security-vulnerable output patterns like cross-site scripting (XSS) or SQL injection vectors. * **Sensitive Data Input and Anonymization:** Detects and anonymizes sensitive information in LLM prompts using data patterns defined in the Data Privacy plugin. This assists in troubleshooting sensitive data detection and anonymization charts. * **Score Weight Configuration:** Allows customization of how different LLM guardrail categories contribute to overall security and integrity scoring. Categories can be re-weighted or deactivated to tailor monitoring to customer needs. ## Practical Benefits for ServiceNow Customers * Improve AI model quality and user experience through controlled data sharing. * Maintain optimal AI service performance by managing datacenter traffic and overflow. * Enhance security posture by monitoring and detecting potential AI output and behavior risks. * Protect sensitive data and comply with privacy requirements using built-in anonymization and detection features. * Customize monitoring and scoring to align with organizational risk tolerance and compliance standards. 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 {#data__section_z1l_qrx_nhc} 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 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](https://www.servicenow.com/docs/DzGSpaSodzXHT~j43IafOw "Data sharing improves ServiceNow AI products. You can opt out of data sharing from the Now Assist Admin console Settings page."). ## Data overflow processing {#data__section_qxf_vg4_hhc} By default, all ServiceNow Otto 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__section_aq5_kg4_hhc} 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](https://genai.owasp.org/llm-top-10/) and the [OpenAI model specification](https://model-spec.openai.com/2025-12-18.html). * 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. {#data__ul_ww1_j5h_k3c} 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. {#data__ul_s5l_bsh_k3c} 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. {#data__ul_p4y_2vh_k3c} 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](https://www.servicenow.com/docs/qscZx8UF0rUD3YfIMbfjOQ "Your data is safe and secure with ServiceNow user data usage policy for generative AI. You can also mask sensitive data or opt-out of sharing data for model improvements."). 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.