Building a Business Case for AI in Service

Deploying AI isn’t just a technical decision—it’s a decision that requires widespread belief and support across the business that it’s the right thing to do. However, AI initiatives can face resistance, from skeptical executives questioning ROI to frontline teams concerned about disruption. 

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As a service leader, how do you turn hesitation into enthusiasm? Here are the three most important components of building a business case for AI in service.

1. Conduct AI Discovery Workshops

Deploying AI for service is an investment; and it’s a big change to how things are currently done. To set yourself up for success, it’s critical to hold very intentional workshops for input and strategic mapping.

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These workshops should include service and support leaders, subject matter experts, and key stakeholders. Participants should identify strategic objectives (examples include improving agent/technician training and onboarding, improving access to information, reducing warranty costs, and reducing escalations), and justify those objectives with reliable internal and external data and research. Participants should then map those objectives to measurable KPIs.

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Then comes prioritization. Which KPIs will have the most traction? The biggest impact? The most measurable result? What are the quantifiable metrics and the long term metrics of each strategic objective and its mapped KPI?

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Then, identify, define, and prioritize use cases based on strategic objectives and business needs. Look closely at the measurable value of each use case and the potential return on investment it can offer, whether that’s increasing profitability, reducing risk, or contributing to business growth.

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By coming together as a service leadership team and mapping out where you need to go and why, using reliable data to determine a reliable ROI, you’ll set the foundation for a strong business case.  

2. Customize Your AI Pitch for Maximum Buy-In  

Once you’ve defined your strategic objectives and key metrics, the next step is ensuring every stakeholder sees AI’s value—on their own terms. Ensure all service leaders understand how it will improve productivity and retention, as a first step. For finance, demonstrate how it will cut costs. Explain to your CEO and other executive leaders how it will help drive growth. A tailored stakeholder approach turns AI from a risk into a clear choice.

Understanding that different departments have distinct priorities, Dave Hartley, Vice President of Customer Care at TransLogic, a Swisslog Healthcare Company, emphasized the specific benefits for each stakeholder. For example, he demonstrated to engineering how AI-driven call deflection reduces escalations, and to finance how it could reduce parts wastage by 10% in the first year—an immediately noticeable ROI.

To executive leadership, Hartley shared how dramatically increasing the speed of many resolutions would boost customer satisfaction, leading to stronger customer relationships and ultimately increased sales. “If I have a happy customer, they’re more willing to purchase more equipment from us,” says Hartley.

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This strategic alignment not only facilitated the adoption of AI for customer service, but also ensured that all teams were invested in its success.

3. Turn Service Teams into AI Advocates

For most organizations, AI for service isn’t going to replace the need for human work and interaction. In fact, it’ll more likely be a partnership between AI and those directly responsible for handling customer service issues. 

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But introducing the idea of AI into a field service technician or a customer service agent’s typical workflow can create uncertainty and anxiety—and they may fear being replaced by AI. 

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However, most organizations using it will attest AI makes work life better for service professionals. It can reduce their frustrations around finding the right solutions for customers, reduce or eliminate unwanted overtime hours, and free team members to do more meaningful work. It can also help new agents learn their jobs more quickly and improve job satisfaction—ultimately helping service leaders with employee retention.

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But if how AI will be used and its benefit for service teams isn’t clearly communicated while you're building the business case, the mere idea of it could seed enough doubt and uncertainty to prevent broader organizational support from ever gaining traction. 

So recognize the potential to turn your agents and technicians into AI proponents —because ultimately, AI for service can make everyone’s work lives easier.

AI in Service is a Win-Win

Organizations that successfully integrate AI into service will gain a competitive edge, improving efficiency, customer experience, and employee satisfaction. The key? Getting the business case right from the start. With these three steps, you can build a business case that demonstrates how AI in service is a win for everybody.

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