Reimagining ITSM Migration with AI-Powered Operations
A large US utility and broadband provider faced a firm deadline: replace a sunset IT service management platform within 120 days, preserve operational history and keep critical business functions running. The task was not simply to move records from one platform to another. The organization also had an opportunity to reconsider how service operations should work in the new environment.
| Client | Large U.S. utility and broadband provider |
| Industry / region | Energy & Utilities / United States |
| Platform / capability | agenTriniti Gold and Salesforce Agentforce |
| Business challenge | A conventional migration would have concentrated on moving data and workflows manually, potentially with selected accelerators. That could meet the narrow objective of platform replacement while carrying forward existing processes without asking whether they should be redesigned. The organization needed to meet the 120-day deadline, preserve history required for continuity and avoid disruption during go-live. |
| Airo’s approach | Airo approached the replacement through agenTriniti Gold, using a purpose-built 50-agent AI pod to support the migration lifecycle while human experts governed the work. AI-assisted discovery helped examine the existing environment; workflows were assessed and redesigned as part of the move; and the pod supported data migration, integration design and deployment. The destination was Salesforce Agentforce, with conversational intake, intelligent routing and automation active from day one. |
A conventional migration would have concentrated on moving data and workflows manually, potentially with selected accelerators. That could meet the narrow objective of platform replacement while carrying forward existing processes without asking whether they should be redesigned. The organization needed to meet the 120-day deadline, preserve history required for continuity and avoid disruption during go-live.
The business needed an approach that addressed the operating constraint itself, rather than simply making existing steps happen faster. That meant understanding where people were spending time, what needed to remain controlled and how the work could move through a more consistent path.
Airo approached the replacement through agenTriniti Gold, using a purpose-built 50-agent AI pod to support the migration lifecycle while human experts governed the work. AI-assisted discovery helped examine the existing environment; workflows were assessed and redesigned as part of the move; and the pod supported data migration, integration design and deployment. The destination was Salesforce Agentforce, with conversational intake, intelligent routing and automation active from day one.
The objective was not to introduce technology for its own sake. It was to change how the work moved from an initial request or input to a usable outcome. That required the solution to fit the existing business context while improving access, consistency, control or the ability to prevent recurring effort.
AI agents supported discovery of the legacy ITSM environment, including operational processes and workflows. This established the basis for migration planning and helped the team understand what needed to move, what needed to connect and where existing workflows could be reconsidered.
The migration was treated as an opportunity to assess and transform existing workflows instead of reproducing them unchanged on the target platform. Moving a legacy process to a new tool does not, by itself, improve the way service is delivered.
The agent pod supported migration of operational data and history from the legacy ITSM environment. Preserving this information was a core requirement for continuity and for ensuring that the new environment could support ongoing operations.
AI agents supported integration design required to connect the new service environment with surrounding enterprise systems. Human experts remained responsible for governing the migration and the work performed by the agents.
The new Salesforce Agentforce environment included conversational intake, intelligent routing and automation from day one. The destination was not only a replacement platform, but a service environment with new interaction and routing capabilities.
The work moved from discovery of the existing environment to workflow assessment, data and history migration, integration design and deployment. AI agents supported the lifecycle activities while human experts governed the process. At go-live, the new Salesforce Agentforce environment provided conversational intake, intelligent routing and automation.
| Starting point | Airo-enabled workflow | Human role | Operational intent |
| Existing system, data or work queue | Discovery, structuring, governed access, migration or root-cause improvement | Oversight, exception handling, review and decisions | A clearer and more consistent path from input to outcome |
The engagement connected a time-bound migration with a change in how service operations would work after the migration. Instead of treating the deadline as a reason to reproduce the legacy environment as quickly as possible, Airo used the migration to reconsider workflows and activate automation in the target environment. Human governance remained part of the delivery model, keeping responsibility for the migration with the people overseeing it.
A more structured operating path also creates clarity around responsibility. Teams can see which activities are handled through the workflow, where human review is still necessary and what the process is intended to improve. This makes the approach easier to manage as business needs change and gives the organization a more explicit basis for evaluating outcomes.
A successful implementation is not defined only by the technology introduced. It is defined by whether the new approach changes the way work gets done and whether that change can be sustained. The operating model connects the solution to the business process, clarifies the role of people and automation, and creates a repeatable pattern that can be reviewed and improved.
That is especially relevant when the objective is broader than a single task. A work-queue improvement needs a way to keep addressing recurring causes. An ITSM migration needs to leave the organization with a functioning service environment. Conversational analytics needs to make information easier to access without compromising governance. In each case, the business value depends on the process surrounding the technology.
Estimated savings in the first six months
Expected ROI in six months
Faster time-to-market
days / zero disruption Migration delivery
The results are presented after the business challenge and solution so the metrics are grounded in the change that was made.
$780K+ Estimated savings in the first six months
The source reports estimated savings of more than $780,000 in the first six months.
72% Expected ROI in six months
The source reports expected ROI of 72% in six months.
50% Faster time-to-market
The engagement reports 50% faster time-to-market.
120 days / zero disruption Migration delivery
The ITSM replacement was completed in 120 days with zero business disruption during go-live.
The case demonstrates how a platform migration can become an opportunity to improve the operating model rather than simply transfer it. The 120-day deadline remained non-negotiable, but the approach also addressed workflow design, integration and the service experience at launch. The result was a move to Salesforce Agentforce with conversational intake, intelligent routing and automation active from day one.
The underlying principle is consistent: technology creates the most useful business impact when it changes the path through the work. The aim is to reduce avoidable manual effort, preserve appropriate oversight and create a more reliable way to move from input to action. The case-specific outcomes above show how that principle applies to this engagement.
