Generative AI (GenAI) produces new content (text, code, structured data) by learning statistical patterns from vast training datasets. Traditional ML in ServiceNow predicts values from patterns in your own historical data. The distinction matters because they solve different problems and are configured and maintained differently.

• Trained on your instance's historical data (resolved incidents, categorisation patterns)
• Predicts discrete field values: which category, which assignment group, which priority
• Output is always a prediction with a confidence score, never generated text
• Gets better as your instance accumulates more resolved, correctly-labelled records
• Fully on-platform: no external model, no external API call

• Uses pre-trained large language models (LLMs) trained on vast datasets of human language
• Generates new content: summaries, draft replies, code, flow logic, knowledge articles
• Output is generated text or structured content, not a predicted value
• Quality depends on the LLM provider and the prompt, not on your instance data alone
• May involve an external API call (to Azure OpenAI, Claude, Gemini) unless using Now LLM

Now LLM is ServiceNow's proprietary large language model, currently on version 2.0 (released October 2025). ServiceNow built its own model to address three gaps that external LLMs cannot fully close.

When using Now LLM, customer data never leaves ServiceNow infrastructure. No external API call is made to any third party. This is the only option for organisations with absolute data residency or sovereignty requirements — zero-retention agreements with external providers still technically cross the platform boundary. Now LLM does not.

Now LLM is fine-tuned on ServiceNow-specific content: GlideRecord API patterns, table names, workflow structures, ITSM terminology, and platform-specific conventions. It generates more accurate ServiceNow-specific code and content than a general-purpose LLM working from a generic prompt.

Using an on-platform model removes dependency on third-party pricing changes, API rate limits, service disruptions, or model version updates from an external vendor that could alter production behaviour.

Now LLM v2.0 improvements over v1: longer context window, faster response latency, and training data updated through 2025.

The Generative AI Controller is the platform-level infrastructure layer that manages all connections between ServiceNow and LLM providers. It is the abstraction layer between the Now Assist skills that agents and developers use and the actual language models processing their requests.

• Stores and manages LLM connection credentials, API keys, endpoints, and deployment names for each configured provider, using ServiceNow Credential records (not hardcoded)
• Routes prompt requests from Now Assist and NASK skills to the correct LLM provider based on each skill's configuration
• Handles token limit management, retry logic, and rate limiting to maintain stable AI responses at scale
• Maintains audit logs of all LLM requests, response times, and error states for compliance and debugging

Because the Generative AI Controller decouples skills from their LLM provider, the same Now Assist skill can use Now LLM in a production environment and Azure OpenAI in a UAT environment without any change to the skill code. Only the provider connection record in the Controller changes. This also means switching LLM providers requires changing the Controller configuration, not modifying every skill.

ServiceNow supports multiple external LLM providers through the Generative AI Controller, allowing organisations to choose the provider that best fits their enterprise agreements, model performance requirements, or cost preferences.

• Azure OpenAI (Microsoft) – GPT-4o, GPT-4 Turbo via Azure endpoint. Most commonly deployed in large enterprise environments with existing Microsoft agreements.
• Anthropic Claude (via AWS Bedrock) – Claude 3 / 3.5 model family. Popular for its instruction-following accuracy and long-context handling.
• Google Gemini (via Vertex AI) – Gemini Pro and advanced models. Preferred in organisations with Google Cloud agreements.
• BYOLLM – Connect any compatible model via a custom endpoint. For proprietary or self-hosted models.
• Now LLM – ServiceNow's on-platform model. No external call, data residency guaranteed.

Provider selection can be set at multiple levels: globally for all Now Assist skills, for a specific department's skills, or per individual skill. A common enterprise pattern: use Azure OpenAI for ITSM summarisation (best model quality, existing agreement) and Now LLM for HR cases (data sensitivity requires on-platform processing).

Both are enterprise control options that address the two most common GenAI security concerns in regulated organisations: which model processes the data, and how the data is encrypted. They are separate controls and can be used independently.

Allows an organisation to connect a custom or self-hosted language model to the Generative AI Controller instead of using Now LLM or a listed partner provider. BYOLLM is the answer when an organisation has strict data residency requirements that prohibit any external provider (even with zero-retention), already owns enterprise licenses for a fine-tuned proprietary model, or needs a model specialised in a non-English language.

Configuration: set up the custom model endpoint as a Connection record in the Generative AI Controller, specifying the API format (OpenAI-compatible, custom schema) and authentication method.

Allows an organisation to provide their own encryption keys to control how GenAI data is encrypted at rest within the ServiceNow platform. BYOK adds an additional encryption layer without changing which LLM processes the data. It is a platform-level control managed through the ServiceNow security configuration, not the Generative AI Controller.

ServiceNow provides three distinct data protection options for organisations to choose from based on their compliance requirements and risk tolerance.

Data is processed entirely within ServiceNow infrastructure. No API call is made to any external service. This satisfies “data must never leave the platform” requirements, including government data sovereignty mandates, defence sector restrictions, and the strictest healthcare data residency requirements.

When using Azure OpenAI, Anthropic Claude, or Google Gemini, ServiceNow negotiates zero data retention agreements: the external provider processes the prompt but does not store, log, or train on the content. The data is transient, used to generate the response and immediately discarded. Suitable for most enterprise deployments where data residency within the platform is not a hard requirement.

Fields configured as sensitive (names, phone numbers, email addresses, national IDs, account numbers) are anonymised in the prompt before any external LLM call. The model processes “[CALLER_NAME]” instead of the actual name. The response is de-anonymised before displaying to the agent. Appropriate for organisations that want additional protection layered on top of zero-retention agreements.

No data from one ServiceNow instance is ever used as context or training data for another instance. Tenant isolation is enforced at the infrastructure level.

ServiceNow completed the acquisition of Moveworks in December 2025 for approximately $2.85 billion. Moveworks was an enterprise AI assistant platform deployed at hundreds of large organisations with deep expertise in conversational AI and cross-system enterprise search.

• Conversational AI front-end – A more polished, natural-language-first interface for employees to resolve IT and HR requests via Microsoft Teams, Slack, or email, with more nuanced multi-turn conversation handling than standard Virtual Agent.
• Cross-system enterprise search – Ability to answer queries by searching simultaneously across SharePoint, Confluence, Jira, ServiceNow, and other enterprise systems in a single query. Addresses the fragmented knowledge problem at enterprises with content in multiple systems.
• Autonomous task completion – End-to-end handling of password resets, access requests, and HR enquiries without human agent involvement, building on ServiceNow's workflow execution engine.
• AI research talent – Hundreds of ML engineers and AI researchers joined ServiceNow's product team, accelerating the AI roadmap across Now Assist, AI Agents, and the AI Platform.

Moveworks' capabilities are being absorbed into the ServiceNow AI Platform under the Autonomous Workforce initiative. Moveworks brings the front-end conversational experience; ServiceNow provides the back-end workflow engine, governance platform, and enterprise ITSM depth.