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Introduction
The inflection point has arrived. After years of incremental improvements to ticketing systems and process frameworks, IT service management is experiencing a fundamental transformation that will reshape how organizations deliver value through technology services.
When three forces converge
Something remarkable happens when artificial intelligence, experience analytics, and cloud-native architectures mature simultaneously. We're not talking about adding chatbots to service desks or implementing another monitoring tool. We're witnessing the emergence of intelligent, self-healing service platforms that predict problems before users notice them and resolve issues before tickets are created.
The numbers tell part of the story: the global AIOps market is projected to grow from $11-16 billion in 2025 to more than double by 2030. But market size doesn't capture the operational reality. Consider the ITSM team drowning in thousands of daily alerts from monitoring tools, where critical signals are buried in noise. Machine learning now aggregates, deduplicates, and correlates these alerts into actionable incidents automatically, reducing alert fatigue while improving mean time to resolve.
This is predictive incident management in practice: when your monitoring system forecasts a storage capacity breach three days in advance, your team shifts from firefighting to strategic problem prevention. The explosion of telemetry data from containerization, microservices, and multi-cloud complexity makes manual event management unsustainable. AIOps provides the essential layer of intelligent automation needed to maintain visibility and control.
The service desk gets intelligent
While AIOps operates behind the scenes, generative AI disrupts the most visible face of ITSM: the service desk. But implementation patterns reveal two distinct transformation vectors working in tandem.
AI copilots are augmenting human agents in ways that meaningfully reduce cognitive load. GenAI summarizes tickets, proposes contextually relevant responses, drafts knowledge articles from resolved incidents, and suggests similar historical cases — all in real-time during agent interactions. Early implementations show 2040% reductions in ticket volume through improved self-service and 15-25% improvements in agent efficiency.
Simultaneously, advanced virtual agents handle growing shares of Level-1 requests. The technology finally matches user expectations: conversational AI that understands context, handles multi-turn dialogues, and gracefully escalates to human agents when necessary.
The storytelling connection becomes clear: together, AIOps and GenAI create end-to-end intelligence across the service lifecycle. AIOps predicts and prevents incidents before they occur; when incidents do surface, GenAI accelerates resolution through intelligent agent assistance. The result is a service experience that feels simultaneously more proactive and more responsive.
By 2026, the "AI-first service desk" will be the reference model, where every interaction is mediated or augmented by AI. Human agents will focus increasingly on complex, emotional, and cross-domain cases that genuinely require human judgment and empathy.
AI copilots are augmenting human agents in ways that meaningfully reduce cognitive load. GenAI summarizes tickets, proposes contextually relevant responses, drafts knowledge articles from resolved incidents, and suggests similar historical cases — all in real-time during agent interactions. Early implementations show 2040% reductions in ticket volume through improved self-service and 15-25% improvements in agent efficiency.
Simultaneously, advanced virtual agents handle growing shares of Level-1 requests. The technology finally matches user expectations: conversational AI that understands context, handles multi-turn dialogues, and gracefully escalates to human agents when necessary.
The storytelling connection becomes clear: together, AIOps and GenAI create end-to-end intelligence across the service lifecycle. AIOps predicts and prevents incidents before they occur; when incidents do surface, GenAI accelerates resolution through intelligent agent assistance. The result is a service experience that feels simultaneously more proactive and more responsive.
By 2026, the "AI-first service desk" will be the reference model, where every interaction is mediated or augmented by AI. Human agents will focus increasingly on complex, emotional, and cross-domain cases that genuinely require human judgment and empathy.
Beyond IT: service management without boundaries
While AI captures headlines, enterprise service management quietly reshapes organizational boundaries. The expansion of ITSM practices into HR, facilities, legal, and other business functions reflects a deeper insight: structured service delivery, workflow automation, and knowledge management principles apply across all enterprise services, not just IT.
When employees access IT support, submit HR requests, book facilities, and request legal approvals through unified portals, organizational friction decreases significantly. This isn't empire building—it's practical efficiency pulled by employee experience initiatives and the need to support distributed, hybrid workforces with coherent digital journeys.
By 2026, ESM platforms will act as orchestration layers on top of multiple departmental tools, with AI-driven routing and knowledge reuse across domains. The connection to experience management becomes evident: when service management spans IT and business functions, experience metrics must span these domains too.
When employees access IT support, submit HR requests, book facilities, and request legal approvals through unified portals, organizational friction decreases significantly. This isn't empire building—it's practical efficiency pulled by employee experience initiatives and the need to support distributed, hybrid workforces with coherent digital journeys.
By 2026, ESM platforms will act as orchestration layers on top of multiple departmental tools, with AI-driven routing and knowledge reuse across domains. The connection to experience management becomes evident: when service management spans IT and business functions, experience metrics must span these domains too.
From measuring uptime to measuring outcomes
This brings us to perhaps the most fundamental shift: the evolution from service level agreements to experience level agreements. Traditional SLA metrics—uptime, response time, closure time—measure what IT delivers but not what users actually experience or value.
Digital employee experience monitoring tools now track end-user device health, application performance, and usage patterns, feeding this data into ITSM for proactive action. When DEX monitoring reveals that 40% of remote workers experience video conferencing latency above acceptable thresholds, ITSM teams can investigate and remediate before complaint tickets accumulate.
Experience level agreements tie metrics to end-user satisfaction and business outcomes. Instead of measuring "we restored service in 4 hours," XLAs ask "did this outage prevent salespeople from closing deals?" Machine learning models identify which infrastructure issues correlate with productivity drops, customer churn, or revenue impact—enabling ITSM teams to prioritize work based on actual business consequences.
Digital employee experience monitoring tools now track end-user device health, application performance, and usage patterns, feeding this data into ITSM for proactive action. When DEX monitoring reveals that 40% of remote workers experience video conferencing latency above acceptable thresholds, ITSM teams can investigate and remediate before complaint tickets accumulate.
Experience level agreements tie metrics to end-user satisfaction and business outcomes. Instead of measuring "we restored service in 4 hours," XLAs ask "did this outage prevent salespeople from closing deals?" Machine learning models identify which infrastructure issues correlate with productivity drops, customer churn, or revenue impact—enabling ITSM teams to prioritize work based on actual business consequences.
The value question
As ITSM becomes more automated, AI-driven, and experience-oriented, a critical challenge emerges: how do we know which improvements actually create business value? This is where the Value Management Database concept enters, extending the traditional CMDB by explicitly linking services, products, and IT initiatives to measurable business outcomes—revenue, cost avoidance, risk reduction, and experience scores.
Consider a practical example: your ITSM team invests in AIOps to reduce MTTR. Traditional measurement tracks technical metrics. A VMDB approach links these technical metrics to business outcomes: how did faster incident resolution impact customer satisfaction scores, sales productivity, or support costs? Did the investment hypothesis prove correct?
By 2026, leading organizations will operate ITSM around value streams with closed feedback loops, transforming service management from a cost center focused on efficiency to a value center focused on outcomes.
Consider a practical example: your ITSM team invests in AIOps to reduce MTTR. Traditional measurement tracks technical metrics. A VMDB approach links these technical metrics to business outcomes: how did faster incident resolution impact customer satisfaction scores, sales productivity, or support costs? Did the investment hypothesis prove correct?
By 2026, leading organizations will operate ITSM around value streams with closed feedback loops, transforming service management from a cost center focused on efficiency to a value center focused on outcomes.
The governance imperative
As AI capabilities pervade ITSM — from chatbots to AIOps and predictive analytics — governance becomes critical. ITSM leaders must understand how AI models triage tickets, recommend actions, or predict incidents, and ensure these decisions can be explained to stakeholders, regulators, and auditors.
Analyst guidance stresses treating AI in ITSM as a portfolio of products requiring lifecycle management: experimentation, validation, monitoring, periodic retraining, and decommissioning. Governance without measurement becomes compliance theater; measurement without governance creates uncontrolled risk.
The path forward
The transformation of ITSM from reactive, process-centric support to proactive, AI-driven, experience-oriented service orchestration is neither optional nor distant. It's happening now, driven by genuine technological capability and real business pressure.
For ITSM leaders, the strategic imperative is clear: begin the journey while maintaining operational excellence. Start with experience metrics that tie to business outcomes. Experiment with AI capabilities in low-risk areas. Extend service management practices where standardization creates obvious value. Invest in skills development so your team can operate in this new environment.
The organizations that thrive through 2026 won't be those with the most sophisticated technology— they'll be those that successfully blend technology, process, and people to deliver services that genuinely matter to their stakeholders. ITSM is evolving from keeping the lights on to powering business value.
The inflection point is here. The question isn't whether to transform—it's how quickly and effectively you can navigate the transformation while bringing your organization along on the journey.
For ITSM leaders, the strategic imperative is clear: begin the journey while maintaining operational excellence. Start with experience metrics that tie to business outcomes. Experiment with AI capabilities in low-risk areas. Extend service management practices where standardization creates obvious value. Invest in skills development so your team can operate in this new environment.
The organizations that thrive through 2026 won't be those with the most sophisticated technology— they'll be those that successfully blend technology, process, and people to deliver services that genuinely matter to their stakeholders. ITSM is evolving from keeping the lights on to powering business value.
The inflection point is here. The question isn't whether to transform—it's how quickly and effectively you can navigate the transformation while bringing your organization along on the journey.
Author: Andrea Cherubini, itSMF Switzerland President
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e-book «Service Management trends 2025-2026» written by President Andrea Cherubini.
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