Six strategies for advancing Autonomous Service Operations
There’s no one strategy for transforming a traditional, manual ITSM and ITOM approach to a unified, autonomous model. These six strategies will propel organizations in the right direction, getting them closer to the goal of Autonomous Service Operations while enabling more proactive and strategic IT.
Strategy #1 – Get your data house in order
The data foundation is the centerpiece from which everything flows. A unified ITSM and ITOM platform promises one version of the truth and shared visibility, but if the data is inaccurate or incomplete, the two groups are simply operating with an inadequate picture.
Start by cleaning up the configuration management database (CMDB), the central repository that houses all relevant data about an organization’s IT assets. A poorly maintained CMDB — flush with duplicate and stale data — can undermine system upgrade planning and lead to unintended IT outages. A consistent and complete CMDB will improve decision-making, reduce downtime, and make compliance easier. Automated discovery and identification engines can simplify this process by reconciling and curating data.
Accuracy is not enough: The right data is essential to support IT processes slated for automation. Business context is an important but often missing ingredient. It’s essential for drawing the right connections between the CMDB and business rules so that proper decisions and autonomous actions can drive intended business value. Governance guardrails help establish trust in autonomous actions and mitigate risks associated with AI specialists.
Challenge: A New Zealand dairy cooperative wanted a single technology platform to work seamlessly across the enterprise and help minimize disruptions to manufacturing operations.
Solution: Fonterra consolidated siloed ITSM, ITOM, and hardware asset management into a single AI platform using ServiceNow and its CMDB. Since implementing, average mean time to resolution (MTTR) for high-priority incidents has decreased by 92%, the overall volume of incidents has dropped by 66%, and the average time to fulfill requests has decreased by 54%.
Strategy #2 – Determine the right use cases
To maximize Autonomous Service Operations, it’s essential to understand where AI agents can have the most impact on eliminating manual and mundane work. By mapping the right use cases, organizations ensure IT service and operations teams can score the biggest wins working as a cohesive unit.
Accelerating incident resolution
Bolstering omnichannel self-service with AI-generated knowledge articles
Reducing the effort to triage and categorize incidents
As part of the exercise, take a strategic view of the entire IT service and operations estate and harmonize systems. Map budgets and systems used in IT service and operations and consolidate where it makes sense to reduce overall technical debt.
Strategy #3 – Target low-value activities in high-volume processes
To maximize AI ROI, focus on less critical workflows that occur in high volumes. For example, in ITSM, leverage AI to summarize resolution notes, provide AI-powered search, and generate transfer summaries. Operations teams can benefit from AI to correlate and prioritize signals tied to actual business impact, so they proactively address issues instead of scrambling after the fact.
These rather mundane tasks can consume an inordinate amount of time and resources. Transforming them with automation can be relatively straightforward compared to other, more complex endeavors. Execution of high-value use cases also creates proof points that help foster enthusiasm and build support for additional investment in Autonomous Service Operations and AI specialist expansion.
Strategy #4 – Unify ITSM and ITOM
IT service management and IT operations traditionally operate in different worlds. Syncing both with a unified platform and single data model, bolstered by AI, will establish shared visibility and eliminate disconnects. This ensures IT service and operations teams operate with the same picture, routing incidents with proper context.
This updated operating model also paves the way for an autonomous IT workforce, where AI specialists can be deployed to handle mundane, end-to-end tasks with human teams focused on advanced problem-solving. For example, ServiceNow’s L1 Service Desk AI Specialist comes with a set of pre-defined, out-of-box skills so it can self-assign based on those skills and other routing rules.
Strategy #5 – Don’t overlook change management
The change management agenda associated with promoting a new operating model often eclipses the technical aspects of deploying a unified ITSM and ITOM platform. As with any major initiative, establish cross-domain process owners who can identify the highest-value use cases, model new behaviors and process changes, and serve as champions to rally peers.
Often, operational and cultural change is harder to solve than technology deployment. Keep in mind there may not be clean before-and-after results with Autonomous Service Operations — the transition is gradual, and benefits accumulate over time.
Strategy #6 – Refine metrics for success
Old metrics don’t measure up for Autonomous Service Operations. MTTR, ticket volume, and SLA metrics were built to gauge the speed and volume of humans, not agents. While they still render an accurate picture of IT service and operations performance, they no longer tell the whole story when you start to introduce AI agents and AI specialists.
New performance criteria should be methodically introduced to complement traditional metrics as organizations gradually integrate and scale up AI. Some of the new additions include:
Automation coverage, for tracking the end-to-end resolutions performed by agents, not humans
Agent accuracy, which reflects whether AI performs at the same level as a skilled human
Prevented incidents, or the number of outages that never happen because anomalies are detected and prevented before they impact users
It's important to understand how the metrics fit into a new Autonomous Service Operations model as they will be instrumental in showcasing ROI to top business leadership. This helps build momentum for an expanded autonomous workforce.
