Data readiness for implementing Now Assist on the ServiceNow AI Platform

  • Release version: Zurich
  • Updated October 14, 2025
  • 3 minutes to read
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    Summary of Data readiness for implementing Now Assist on the ServiceNow AI Platform

    High-quality, complete, accurate, and contextually relevant data is essential for Now Assist on the ServiceNow AI Platform to deliver precise, meaningful, and trustworthy AI-driven responses. Data readiness ensures AI features such as summarization, recommendations, and workflow guidance operate effectively, enabling faster issue resolution and improved self-service experiences.

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    Well-prepared data allows Now Assist to interpret user queries accurately, supporting complex tasks like incident summarization, resolution note generation, and knowledge article creation. Conversely, incomplete or vague data compromises AI output quality, reducing user trust and adoption.

    Key Recommendations for Data Readiness

    • Audit task records for completeness, clarity, and consistent resolution summaries.
    • Avoid vague or generic language in task descriptions and updates.
    • Maintain a clean, structured knowledge base with articles linked to resolved cases.
    • Audit Service Catalog items for conversational readiness.
    • Use the Now Assist Readiness Evaluation app to automate data assessment and receive actionable recommendations.
    • Leverage the Now Assist Data Kit to curate, cleanse, and manage custom data sets for AI evaluation when base system skills need customization.
    • Align stakeholders (data owners, product managers, engineers) on shared standards for AI-ready data governance.

    Tools to Support Data Readiness

    Now Assist Readiness Evaluation app: Automates data readiness assessments by analyzing catalog entries, cases, and incidents. It identifies issues, provides direct links for remediation, and helps evaluate the impact of instance customizations on implementation.

    Now Assist Data Kit: Enables customization of datasets and data collections for AI skill evaluation when out-of-the-box capabilities require extension.

    Expected Outcomes

    • Accelerated implementation with reduced rework and smoother AI feature deployment from day one.
    • Higher ticket deflection rates and improved operational efficiency by enabling teams to focus on strategic tasks.
    • Enhanced user trust and confidence through consistent, reliable, and context-aware AI responses.
    • Maximized return on investment via improved user satisfaction and long-term AI performance.

    High-quality data that is complete, accurate, and contextually relevant is the foundation for delivering precise, meaningful, and trustworthy AI responses.

    Now Assist requires high-quality data

    To unlock the full potential of Now Assist on your instance, the quality of your data is paramount. For AI to deliver accurate, context-aware, and actionable outputs, it must be trained and operate on high-quality data that is complete, consistent, and structured. When your data is well-prepared, Now Assist can interpret user queries with greater accuracy, enabling faster resolutions and more effective self-service experiences.

    Whether it's summarizing complex incidents, generating resolution notes, or creating knowledge articles, Now Assist relies on detailed records that reflect the full lifecycle of a task. Short or incomplete cases often lack the depth needed for meaningful AI interpretation, which can result in vague or unhelpful responses. The importance of data readiness extends beyond technical accuracy—it directly impacts user trust and adoption.

    Clean, ready data also accelerates implementation. It minimizes the need for rework, reduces deployment friction, and ensures that AI features like summarization, recommendations, and workflow guidance operate smoothly from day one. This leads to higher ticket deflection rates and improved operational efficiency, allowing teams to focus on strategic tasks rather than repetitive support.

    Moreover, high-quality data fosters trust in AI outputs. When users consistently receive reliable and context-aware responses, their confidence in the system grows—driving adoption and maximizing return on investment. Ultimately, investing in data quality is an investment in user satisfaction, AI performance, and long-term success.

    Follow these tips to assess your organization's data readiness:

    For more information, see Now Assist Data Readiness Checklist.

    Now Assist Readiness Evaluation app

    Data readiness assessments can be time-consuming and manual, especially when evaluating whether catalog items are conversational or if knowledge articles are embedded in inaccessible formats like PDFs. The Now Assist Readiness Evaluation app helps automate this process by analyzing service catalog entries, cases, and incidents, and then providing actionable recommendations to prepare data for AI use. It also enables you to assess whether updates, installations, or customizations of your instance could affect implementation. The assessments provide direct hyperlinks to improve any issues found.

    For more information, see Now Assist Readiness Evaluation.

    Install Now Assist Readiness Evaluation by requesting it from the ServiceNow Store. Visit the ServiceNow Store website to view all the available apps and for information about submitting requests to the store. For cumulative release notes information for all released apps, see the ServiceNow Store version history release notes.

    Now Assist Data Kit

    If the base system Now Assist skills don't fit your needs, use the Now Assist Data Kit to curate, cleanse, and manage data for AI evaluations. You can create custom datasets and data collections that can be used in Now Assist Skill Kit for evaluation. For more information, see Now Assist Data Kit.