Badly implemented AI & IA in ITSM

However, adopting AI and IA across ITSM introduces:

• Operational fragility, where rigid automations break when underlying systems change. [rezolve.ai]
• Inclusion risks, where poorly designed AI creates barriers for employees or customers. [itsm.tools]
• Governance risks such as hallucinations, privacy breaches, and opaque decision making. [rezolve.ai]

Badly implemented AI & IA in ITSM can seriously damage your business bottom line.

Gartner reported that by the end of 2026 40% of enterprise applications will feature task specific AI agents (up from 5% in 2025).

ITSM solutions are at the forefront of this trend and AI agents, and IA (Intelligent Automation) are seen as a must have to enhance the user experience.

A lot of organisations have started the journey with the following “easy” wins

• Enabling self service password reset.
• Setting up automated onboarding/offboarding checklists.
• Using auto routing of tickets based on keywords.

The second stage of the AI and IA journey, using these to replace more complex operations, is often fraught with common pitfalls.

Organisations are, often, too quick to try and automate their existing processes without stopping to reflect if that process is robust and correct and if the data, and systems, which support it are in a fit state.

These oversights can lead to bloated and unwieldy automations that are all too easily brought down or lead to false routing or even barriers to use for users.

Poorly thought through implementations are also at risk of completely failure when source systems or data are not fully considered so external change factors stop the AI or IA functioning correctly.

Let’s reflect on how your ITSM affects the business.

Poorly implemented ITSM doesn’t just cause IT inefficiencies, it has direct and measurable impacts on business performance, employee productivity, customer experience, cost, and risk exposure. Here are the most significant consequences:

1. Increased Downtime and Operational Disruption

When ITSM processes are weak, especially Incident, Problem and Change Management, downtime becomes more frequent and longer-lasting. Research shows organisations implementing AI or automation without strong foundational processes increase their operational risk and create failure points. [itsm.tools], [rezolve.ai]

Business impact:

• Lost revenue during outages
• Delays in customer service and order fulfilment
• Reduced employee productivity
• Higher recovery costs

2. Failed or Broken Automations (Scaling Failures Faster)

Automation and AI are now embedded across Service Desks, triage, workflows, change risk assessment, and more. However, poor ITSM governance leads to automations that break silently, creating larger-scale failures. [rezolve.ai], [cxtoday.com]

Business impact:

• Hidden manual work and shadow processes
• Inconsistent customer or employee experiences
• Risk of widespread system failure if automated workflows malfunction

3. Poor Digital Employee Experience (DEX) and Lower Productivity

ITSM now sits at the centre of employee experience. When support is slow, inconsistent, or poorly designed, employees lose time, trust, and morale. Over-reliance on poorly governed AI creates “digital barriers” and exclusion for users. [itsm.tools]

Business impact:

• Lower productivity due to unresolved or recurring issues
• Increased frustration and disengagement
• Higher shadow IT usage as employees try to work around IT processes

4. Talent and Skills Risks Amplified

Weak ITSM practices worsen talent shortages by:

• Burning out IT teams (high ticket loads, manual processes)
• Creating reliance on outdated practices
• Failing to build modern skills needed for AI enabled environments

Industry analysis highlights an ageing ITSM workforce, talent gaps, and lack of structured development. [itsm.tools]

Business impact:

• Inability to support digital transformation
• Rising cost of recruitment/retention
• Loss of institutional knowledge

5. Poor Change Management Leading to More Incidents

When organisations attempt to implement new technologies, especially AI and automation without mature change processes, failure rates increase.

Rigid or incomplete ITSM processes create cascading Incidents after changes. [rezolve.ai]

Business impact:

• Higher Incident volumes
• Costly service degradation following changes
• Slow or halted innovation because teams fear change failure

6. Misalignment Between IT and Business Outcomes

Leaders now expect ITSM to contribute to productivity, resilience, and strategic goals. Poor ITSM means IT cannot clearly demonstrate value or support business direction.

Research shows organisations risk staying trapped in outdated mindsets rather than modernising effectively. [itsm.tools]

Business impact:

• IT seen as a cost centre, not an enabler
• Slower decision-making and transformation
• Increased stakeholder dissatisfaction

7. Customer Experience (CX) Failures

Poor ITSM directly impacts CX because customer-facing systems depend on IT stability. When infrastructure is slow, unreliable, or unmonitored, the contact centre becomes the visible failure point.

Complex CX stacks mean a single failure can degrade the entire experience. [cxtoday.com]

Business impact:

• Lost customers due to system failures
• Lower NPS/CSAT
• Reputational damage

8. Higher Security and Compliance Risk

Weak processes – especially in change, asset, and configuration management – increase exposure to cyber incidents.

Poorly governed AI can also introduce privacy and ethical risks. [rezolve.ai]

Business impact:

• Increased vulnerability to attacks
• Fines or legal implications
• Data loss and reputational impact

9. Rising Operational Costs

Poor ITSM creates hidden inefficiencies:

• Manual rework
• Redundant Incidents
• Inefficient resource allocation
• Reliance on legacy tools

Automation fails when processes are dysfunctional, increasing costs rather than reducing them. [itsm.tools]

Business impact:

• Higher support costs
• Wasteful spend on tools with low ROI
• Budget diverted towards firefighting instead of innovation

In Summary

Poor ITSM damages the business through:

• More downtime
• More failed automations
• Lower employee productivity
• Slower innovation and digital transformation
• Higher costs and operational inefficiency
• Greater risk exposure
• Worse customer experience

In 2026’s AI-driven, cloud-heavy environment, the gap between strong and poor ITSM has grown dramatically. Strong ITSM is now a strategic differentiator, while poor ITSM has become a business-wide liability.

Agentic AI and automation are seen as key components, but organisations are struggling to successfully deploy in a lot of cases.

Agentic AI Adoption Has Surged – But Not into Production

• 79% of enterprises have adopted AI agents in some form, but only 11% have them running in production – a massive 68 percent production gap.
• 88% of AI agents fail to reach production, mainly due to governance, infrastructure, and evaluation weaknesses.
• 40% of agentic AI projects will fail by 2027 because companies automate broken processes instead of redesigning workflows.

Agentic AI is not failing due to model quality; it fails due to:

• Weak Change Management
• Poor data hygiene
• Lack of observability
• Manual bottlenecks in critical workflows
• Broken or undocumented processes

Benefits of getting it right

Getting it right, after analysing your sources, systems and processes leads to real returns and direct influence on the bottom line:

ROI When Agentic AI Reaches Production

Successfully deployed agents deliver 171% average ROI, [prioxis.com]

This ROI stems from:

• Fewer manual interventions
• Autonomous workflows
• Reduced downtime
• Faster resolution cycles
• Higher worker productivity

ITSM Ticket & Workload Impact

• Early rollouts show up to 60% reduction in ticket volume driven by autonomous agents.[fortunebus…sights.com]

MTTR Improvements

• Agentic AI can reduce MTTR by 40–60%, based on real enterprise deployments.
  L1 Support Automation
• Up to 80% of Level 1 tasks can be automated with agentic layers.

The Bottom Line

1. ITSM is Now a Revenue Protection Function

Downtime and slow support directly cost organisations hours of employee productivity, SLA penalties, customer churn, and revenue impact.

2. Automation Is No Longer Optional

AI-driven automation is the only scalable way to manage rising ticket volumes without increasing headcount.

3. Poor Processes Undermine Technology Investment

High AI failure rates show that without solid ITSM processes, data management and governance, enterprises cannot realise the value of automation, AI, or digital transformation.

Guy Halton

Senior Consultant, Illuminet

Guy Halton | LinkedIn