Aug 6, 2026

How do you move beyond AI experimentation and identify the use cases that deliver real business value? In episode 56 of Syncing with ServiceNow, Fred Reynolds is joined by XenTegra Senior Solution Architect Kristin McDonald to discuss the key strategies for successfully implementing agentic AI workflows in ServiceNow. They explore how to prioritize high-impact use cases, ensure your data is AI-ready, secure executive sponsorship, and scale AI initiatives with a thoughtful roadmap. Whether you’re just beginning your AI journey or looking to expand existing capabilities, this episode offers practical guidance for turning AI into measurable business outcomes.

How to Identify, Prioritize, and Scale AI Use Cases

Artificial intelligence is no longer a future initiative—it’s becoming a business imperative. But for many organizations, the challenge isn’t deciding whether to adopt AI; it’s determining where to begin.

In the latest episode of Syncing with ServiceNow, XenTegra’s Fred Reynolds sits down with Senior Solution Architect Kristin McDonald to discuss how organizations can move beyond AI experimentation and build a roadmap that delivers measurable business outcomes. Rather than chasing the latest AI trend, they focus on identifying the right use cases, preparing your data, and scaling AI in a way that drives long-term success.

AI Success Starts with the Right Use Case

Many organizations have already implemented ServiceNow’s out-of-the-box AI capabilities and are now asking the next logical question:

What’s next?

According to Kristin, the answer isn’t simply implementing more AI—it’s identifying the right opportunities.

While traditional evaluations often focus on ROI, automation potential, and existing pain points, organizations should also consider how AI initiatives can build upon one another.

For example, an AI agent that triages incoming incidents doesn’t just save time today. It also generates valuable data that can improve future AI agents, creating a foundation for increasingly intelligent workflows over time.

Focus on Core Business Workflows

Not every process is a good candidate for AI.

When evaluating opportunities, prioritize workflows that are:

• High volume
• Repeatable
• Business critical
• Easy to measure

These core processes typically provide the greatest return because improvements are multiplied across thousands of transactions, tickets, or requests.

Rather than automating occasional tasks at the edge of the business, organizations should begin with workflows that employees interact with every day. This creates faster ROI while establishing confidence in future AI initiatives.

AI Should Empower People—Not Replace Them

One of the most important themes discussed throughout the episode is that successful AI isn’t about replacing employees.

It’s about making them better.

Instead of asking AI to completely perform someone’s job, organizations should use AI to:

• Gather relevant information
• Summarize complex data
• Provide recommendations
• Reduce repetitive manual work
• Deliver context before a human makes the final decision

This human-in-the-loop approach not only increases user adoption but also improves trust, accuracy, and overall business outcomes.

Rather than replacing expertise, AI amplifies it.

Great AI Requires Great Data

No AI initiative succeeds without quality data.

As Kristin explains, AI is only as effective as the information it can access.

That means organizations should evaluate:

• Knowledge articles
• Resolution notes
• Historical tickets
• Documentation
• Systems of record

If your documentation is incomplete or inconsistent, AI has little reliable information to learn from.

Think of AI like onboarding a new employee. The better your documentation, the faster that employee becomes productive—and the same principle applies to AI agents.

Executive Sponsorship Is Critical

Technology alone doesn’t drive successful AI adoption.

Organizations also need strong leadership.

Successful AI projects require executive sponsors who can:

• Remove roadblocks
• Make timely decisions
• Align stakeholders
• Communicate organizational goals
• Champion adoption across the business

Because AI often changes how people work, executive sponsorship becomes just as important as the technology itself. Organizations that invest in change management alongside implementation typically see stronger adoption and greater long-term success.

Crawl, Walk, Run

One of the biggest mistakes organizations make is trying to deploy AI everywhere at once.

Instead, XenTegra recommends a structured approach:

1. Identify and prioritize high-value use cases.
2. Select one project with measurable ROI.
3. Implement and refine it.
4. Measure results.
5. Expand into the next opportunity.

This phased strategy allows organizations to learn from each implementation while building confidence and organizational momentum.

Why Partner with XenTegra?

AI adoption isn’t simply about enabling new technology—it’s about aligning technology with business objectives.

With decades of combined ServiceNow experience, XenTegra helps organizations:

• Assess AI readiness
• Identify high-value use cases
• Develop AI roadmaps
• Implement ServiceNow AI capabilities
• Accelerate adoption through proven frameworks and real-world experience

Whether you’re just beginning your AI journey or looking to expand existing ServiceNow capabilities, XenTegra can help you move from ideas to measurable business outcomes.