ServiceNow Now Assist

Now Assist integrates into ServiceNow’s modules, offering precise automation and intelligent support across various service areas.

Now Assist utilizes natural language processing (NLP) to analyze customer interactions in real-time, generating case resolution notes that summarize key actions and decisions made during the interaction. This summary isn’t just a simple log; it’s an AI-driven synthesis of the conversation, highlighting critical issues, resolutions, and any follow-up actions required. The chat summarization feature goes beyond basic transcription, identifying and emphasizing the most relevant parts of the conversation, ensuring that customer service agents have a comprehensive understanding of the issue before moving on to the next step.

In HR operations, Now Assist uses context-aware AI to automatically generate resolution notes that reflect the nuances of each case, such as specific employee concerns or regulatory requirements. This ensures that HR professionals can quickly access a concise, accurate summary of the interaction without missing any critical details. The interaction summaries are designed to highlight patterns in employee requests, enabling HR teams to preemptively address recurring issues and improve overall service delivery. This process leverages machine learning algorithms that continuously adapt to the unique language and context of HR communications.

Incident management within ITSM demands detailed and accurate documentation. Now Assist automates the creation of incident resolution notes by applying predictive text generation based on the historical data of similar incidents. This allows IT professionals to have a complete, actionable summary of an incident, including root cause analysis, steps taken to resolve the issue, and recommendations for preventing future occurrences. The chat summarization feature extracts relevant technical details from support interactions, ensuring that every critical piece of information is captured and readily available for review or audit purposes.

Now Assist transforms complex work orders into clear, actionable summaries using task-specific AI models. These models understand the context of each task and distill instructions into concise directives for field technicians. This not only reduces the time spent interpreting work orders but also minimizes errors in task execution. The summaries include prioritized steps, potential hazards, and necessary tools or materials, all generated by AI that has been trained on thousands of similar tasks, ensuring reliability and precision.

In IT operations, timely response to alerts is crucial. Now Assist enhances alert management by employing event correlation algorithms that filter out noise and focus on actionable alerts. The system uses machine learning to identify patterns in alert data, grouping related alerts together and prioritizing them based on their potential impact on the system. This allows IT teams to respond to critical issues faster, with a clear understanding of the underlying cause and the steps needed to resolve it. Now Assist also provides real-time recommendations on how to address these alerts, based on historical data and best practices.

Now Assist leverages sentiment analysis and data mining techniques to extract actionable insights from customer feedback. This information is then presented in a way that allows portfolio managers to quickly assess the success of ongoing projects and make data-driven decisions. The system identifies trends and patterns in feedback that might not be immediately obvious, providing a strategic advantage in aligning projects with organizational goals. By integrating these insights into the project management workflow, Now Assist ensures that resources are allocated to initiatives that offer the highest potential value.

For developers, Now Assist integrates generative AI models directly into the Now Platform development environment. These models assist in writing code, suggesting optimizations, and even automating repetitive coding tasks. The AI is trained on vast amounts of code, allowing it to suggest context-aware improvements that align with best practices and the specific requirements of the project. This not only accelerates development but also ensures that the applications built are robust, scalable, and tailored to the organization’s needs.

Now Assist’s AI Search transforms the way data is retrieved on the ServiceNow platform. By deploying domain-specific large language models (LLMs), this feature cuts through irrelevant information, delivering precise, context-aware results in seconds.

This ensures that IT teams, service agents, and HR professionals can find critical knowledge articles, historical data, or resolutions without delay, reducing response times and enhancing decision-making accuracy. The result is a streamlined search experience where only the most relevant information surfaces, directly supporting faster issue resolution and more informed actions.

Advanced Conversational AI
The Virtual Agent within Now Assist redefines user interactions by embedding generative AI that creates nuanced and contextually appropriate conversations. This goes beyond simple query handling; it involves understanding user intent, offering real-time solutions, and adapting to complex inquiries as they unfold.

The integration of LLM topic authoring enables these agents to manage intricate service requests, reducing the need for human intervention in routine cases while ensuring that responses remain accurate and aligned with organizational standards. This capability not only supports continuous service availability but also enhances user satisfaction through efficient, automated interactions.

Centralized AI-Driven Workflow Automation
At the core of Now Assist lies the Generative AI Controller, a centralized system that integrates AI across various ServiceNow workflows. This controller orchestrates tasks such as content generation, incident resolution, and workflow automation, ensuring consistency and accuracy across all operations.

By harnessing the capabilities of this controller, organizations can automate complex tasks, from drafting technical documentation to generating precise code snippets, without compromising on quality. This not only reduces manual workload but also guarantees that every AI-driven action adheres to predefined security and compliance protocols, crucial for maintaining operational integrity.

Getting Started with Now Assist: To set up Now Assist in your organization, start by verifying that your system meets the baseline requirements. Ensure that your ServiceNow platform is on Vancouver Patch 2 or higher, and that Next Experience and Configurable Workspaces are active. These elements are non-negotiable, as they lay the groundwork for a smooth Now Assist deployment. Focus initially on modules like ITSM, CSM, ITOM, or HRSD since these are key areas where Now Assist provides the most impact.

Before diving into configuration, make sure your instance’s primary language is set to English. This is crucial for optimal performance. Additionally, check that your organization is using Knowledge Management, Virtual Agent, AI Search, or Flow Designer—tools that work in tandem with Now Assist to deliver seamless service experiences.

Conduct a thorough audit of your existing infrastructure. Confirm compatibility with Now Assist, focusing on application dependencies and any integration points with third-party systems. Address any discrepancies before proceeding.

Begin by conducting a gap analysis to identify any existing bottlenecks or areas where Now Assist can have the most immediate impact. Engage your IT team early to ensure that the system’s architecture can handle the added functionalities of Now Assist without performance degradation. Consider running a pilot analysis on a smaller scale to predict potential integration issues.

Enable Now Assist by activating the appropriate plugins through the ServiceNow Store or your instance’s plugin manager. This includes AI-driven components that will power Now Assist’s functionalities.

When enabling plugins, focus on version control to ensure all components are up to date. Mismatched versions can lead to functionality gaps or performance issues. Collaborate closely with ServiceNow experts to confirm that all plugins are compatible with your specific environment, minimizing downtime during activation.

Tailor Now Assist to align with your organization’s specific workflows. Customize the configurations within ITSM, CSM, ITOM, or HRSD to ensure that Now Assist functions as an integral part of your service delivery process.

Customization should go beyond just configuring workflows. Look into creating custom dashboards that provide real-time visibility into Now Assist performance metrics. This approach enables ongoing adjustments based on actual usage data. Additionally, align customization efforts with your organization’s strategic goals to ensure that Now Assist supports long-term objectives.

Before going live, conduct rigorous testing across all departments that will use Now Assist. This step includes validating the accuracy of AI outputs, ensuring data integrity during processing, and checking the integration points for any issues. Address any blockers, such as compatibility issues with multilingual environments or portal configurations, during this phase.

In the testing phase, consider utilizing A/B testing to compare different configurations and identify which setup best meets your organization’s needs. Additionally, involve end-users in the testing process to gather feedback on usability and ensure the system is intuitive for those who will use it daily.

Once testing is complete, plan a phased rollout. Begin with a pilot program in one department to gather feedback and refine the implementation. Provide comprehensive training for end-users and administrators, focusing on how to maximize Now Assist’s capabilities in daily operations.

To maximize the effectiveness of training, develop role-specific training modules that cater to the needs of different user groups, from administrators to front-line employees. Use hands-on workshops or simulation environments where users can practice without risk to the live system. Follow up with refresher sessions post-rollout to address any lingering questions.

Post-implementation, continuously monitor Now Assist’s performance. Regularly review the system to ensure it aligns with evolving business needs and industry standards.

After implementation, set up automated monitoring tools that provide real-time alerts on performance issues or bottlenecks. Regularly review Now Assist logs and user feedback to identify areas for improvement.

Establish a human review process to validate AI-generated outputs and minimize risks. For data processing, ensure compliance with ServiceNow’s guidelines on data transfer, especially when dealing with multi-region data centers or third-party cloud providers like Microsoft Azure.

Compatibility is key—ensure all portals and tools are aligned with Now Assist’s requirements. Pay special attention to application dependencies and resolve any potential integration conflicts early on. Engage with a ServiceNow consulting partner to navigate complex configurations and ensure that your setup supports long-term scalability and performance.