Driving operational excellence remains a top strategic priority for organisations across industries. One of the most powerful enablers of this is embedding artificial intelligence into service management workflows - especially when applied via a unified platform such as ServiceNow. In this blog we will lay out how AI powered ServiceNow solutions can transform service delivery, accelerate efficiency, drive cost savings and elevate both employee and customer experience, supported by metrics, case evidence and practical guidance.

The Challenge: Siloes, Manual Processes & Rising Expectations

Many enterprises today struggle with legacy service management systems, disconnected departmental workflows and high volumes of repetitive requests. According to a blog by ServiceNow on their own deployment at Globalia (a travel group), prior to standardising they had multiple systems and manual handoffs; automation of workflows yielded enormous time savings: “digital workflows have saved us about 95% of time … event management has reduced the number of operator controlled events by 98%.”   

Beyond this case, broader ecosystem statistics emphasise the urgency:

• According to ServiceNow’s “45 generative AI statistics” page, 75% of knowledge workers were using AI in 2024 (vs ~46% six months earlier).   

• In the context of AI in ITSM and operations, one summary source reported organisations leveraging AI on the ServiceNow platform saw reductions in operational costs of 2025%, resolution times by 4060% and ticket volumes by ~30%.   

• From another source: 89% of enterprises expect AI to transform IT operations within three years.   

These figures underline that the problem isn’t just about digitising service processes but about elevating them via intelligence and automation. That’s where ServiceNow’s AI powered capabilities become relevant.

How AI at ServiceNow drives operational excellence

Here are the key levers through which AI within ServiceNow drives real-world operational impact:

1. Self service, virtual agents & task deflection

By embedding virtual agents and intelligent routing, organisations can deflect high volumes of repeatable requests, freeing up human agents for higher value work.

For example, at Griffith University in Australia, the deployment of the ServiceNow AI platform resulted in self-service rates increasing by 87% and first contact resolution boosting by 43%.   

This shows how deflection and automation reduce load and improve service quality.

2. Predictive intelligence & proactive workflows

Beyond reactive service, AI can anticipate issues, automatically classify/triage incidents, escalate when needed and resolve without human intervention. For example, combining configuration management database (CMDB) data with AI helps detect anomalies and root cause issues faster.   

In many organisations the use of predictive intelligence means less firefighting and more proactive management - a key pillar of operational excellence.

3. Unified data model & workflow fabric

ServiceNow’s platform approach (single data model across IT, HR, facilities, customer service) means that AI doesn’t sit in isolation but flows through unified workflows. One article described the concept of “AI is the new UI” for ServiceNow’s AI Experience: a knowledge graph + workflow data fabric powering unified operations.   

This matters because the real value comes when AI touches multiple domains, not just IT tickets.

4. Measurable cost, speed & quality improvements

It’s one thing to talk about “automation” and “AI” - but measurable impact is what leadership cares about.

• The Griffith University case: reduction in time to resolution was expected to drop by up to 25% with further AI rollout.   

• The Deloitte ServiceNow case: a European ecommerce organisation saw a 50% reduction in HR cases created via email, a 200% increase in self-service HR cases, and a 20% decrease in general enquiry cases.   

These metrics all point to operational excellence delivered via AI enabled service workflows.

What “Operational Excellence” Looks Like in Practice

When AI powered ServiceNow solutions are deployed effectively, you will see several tangible shifts:

• Faster resolution times: Tickets are auto classified and routed; virtual agents handle standard requests; human agents handle complex cases.

• Higher first contact resolution & self-service adoption: Users get answers quickly without needing agent involvement.

• Reduced costs: Fewer manual hours, fewer escalations, reduced overhead.

• Improved employee & customer experience: Staff aren’t bogged down; users get consistent service; satisfaction scores improve.

• Data driven continuous improvement: With unified metrics and AI driven analytics you can monitor, refine and scale.

Digile Success Story: Multi-Tenant ITSM Transformation

A global digital infrastructure and interconnection provider operating across 76 metro areas and six continents implemented a multi-tenant ITSM solution on ServiceNow to overcome fragmented tools, onboarding delays, and operational inefficiencies. With over 13,800 employees and a vast ecosystem of partners, the organization faced slow, manual client onboarding processes, broken service workflows, poor user experiences, and duplicated incidents due to siloed systems.

The Challenge

The client’s existing ITSM environment was hindered by:

• Fragmented tools and onboarding friction: Multiple systems created delays and inefficiencies in client onboarding, often requiring manual data reconciliation.

• Broken workflows and poor user experience: Employees and clients had inconsistent access to product and service offerings, with slow resolution times and limited self-service capabilities.

• Operational noise and data issues: Redundant incidents, poor data integration, and siloed reporting impeded productivity and clarity across the organization.

The Solution

The ServiceNow expert team at Digile deployed a multi-tenant ITSM solution on ServiceNow with the following components:

• Incident, Change, Problem, and Request Management modules.

• Domain separation to ensure client data and process integrity in a shared environment.

• ITSM Agent Workspace for streamlined case management and resolution.

• Service Catalogs tailored for both internal and external users to simplify access to services.

• Standardized client onboarding workflows, enabling faster migration of new clients to a single platform.

• Centralized administration and reporting, enabling governance and compliance across tenants.

Key Technical Outcomes

• 60% improvement in user satisfaction through better UX and faster resolutions.

• 50% drop in error rate thanks to automated workflow execution.

• 20% reduction in ticket backlog and problem incidents due to optimized incident management.

Key Business Outcomes

• A single, unified portal for service access improved discoverability and transparency.

• Accelerated onboarding for clients across global geographies, minimizing delays.

• Centralized oversight with strict data segregation and compliance ensured operational control across business units.

This case study further illustrates how Digile delivered the transformative impact of AI-enabled, multi-tenant ServiceNow deployments resulting in achieving operational excellence at enterprise scale. 

Key Success Factors & Best Practices

To succeed with AIpowered ServiceNow solutions and achieve operational excellence, you should keep these best practices in mind:

• Start with clean data & unified modelling

AI’s value is grounded in the quality of your data and your workflow model. The CMDB, process maps, knowledge articles, service catalogue - all need to be well structured. As one research article emphasised, integration of AI + CMDB + ServiceNow requires “accurate, complete, and integrated data”.   

• Define high impact use cases

Pick use cases that are high volume, have strong ROI and clear user pain points (e.g., password resets, onboarding requests, facilities issues). Starting small helps build momentum.

Many implementations emphasise the value of a phased rollout rather than a “big bang”.

• Embed change management & governance

AI will change roles, workflows and expectations. As one article noted, upskilling employees, building guardrails and managing adoption are key.   

You must ensure governance (model transparency, ethics, accountability) and culture (empowering users) are addressed.

• Monitor metrics & iterate

Operational excellence is not a onetime outcome; it’s a continuous improvement cycle. Monitor first contact resolution, deflection rates, mean time to resolve, user satisfaction, cost per ticket, etc. In the Deloitte case, metrics like transfer rate went down, knowledge usage went up (+180%) as part of the continuous improvement.   

• Scale across functions

Once ITSM is mature, extend to HR service delivery, facilities, legal, customer service, projects. A unified platform makes this scaling feasible and efficient. Griffith University is an example where multiple functions (IT, library, parking, finance, HR) were onboarded in phases.   

Risks & How to Mitigate Them

Operational excellence via AI is compelling, but there are risks:

• Data siloes and poor metadata can lead to weak models and flawed automation.

• Over automation too early can degrade user experience (when virtual agents are weak).

• Change resistance: staff may feel threatened or unsupported.

• Governance/compliance issues: AI models may stray without guardrails.

• Lack of long-term ownership: initial ROI may plateau without continuous improvement.

Mitigation: build a strong foundation (data, catalogue, process), apply phased rollout, ensure ongoing training, embed governance, and align with business objectives.

Conclusion

In today’s fast-moving enterprise environment, “good enough” service delivery isn’t enough. Operational excellence means faster resolution, lower cost, and higher user satisfaction, and that demands more than workflow automation alone. Embedding AI into your service management platform is the true differentiator.

With ServiceNow’s intelligent capabilities including virtual agents, predictive intelligence, and unified workflow fabric, organizations can deliver quantifiable improvements across their service operations.

At Digile, we help enterprises harness the full potential of ServiceNow’s AI-powered ecosystem. From strategic implementation and workflow optimization to continuous improvement and governance, we ensure your service management platform becomes a driver of measurable business value and long-term success.

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