AI and the ambitious future of IT service management

How AI will transform IT service management

News By Deepesh YK published 20 September 2024

Companies are rushing to address IT and business challenges by implementing AI strategies. But their roadmaps are leading in dozens of directions amid a barrage of AI hype and hope. We’re fast realizing that putting AI to work, including machine learning and generative AI, in an effective and cost-efficient way requires accurately diagnosing deep-seated enterprise problems.

While the depth of problems can vary from organization to organization, enterprises experience considerable friction due to cloud migration complications and constantly evolving core technologies, platforms, and ITSM tools. Diving deeper, cross-enterprise challenges also include a broad lack of maturity in automation adoption, digital labor, systems-driven operational models, and AI-enabled tools themselves. All of this is often wrapped up in failures to understand core process issues that have stalled digital transformation and acceleration initiatives.

Enterprises can become frustrated with little measurable success, despite major investments of time and money. The future of IT service management depends on the accurate examination of this impasse — and fine-tuning AI, guided by human oversight and evaluation, to navigate processes better and achieve higher quality results faster than we currently do.

Deepesh YK

Head of Intelligent-Infra Services, SLK Software.

Challenges multiply when enterprises fail to understand process issues

When organizations fail to fully identify and understand issues with their business and technical processes, they also waste time and resources trying to identify and implement the right solutions for the organization, at the right time. While executives and management often have a solid awareness of the impact of technology adoption and process problems on the business, they typically lack visibility into the root causes of, say, skyrocketing cloud spend, poor data management, or inefficient workflows and tooling.

A lack of process and procedural “hygiene” is responsible for much of the inefficiency and noise. That bad hygiene can manifest as a lack of discipline in organizations to log tickets for every issue handled, to capture proper issue-related details in the tickets, and to capture proper work notes and resolution notes. These seemingly small details can wreak havoc on the health of enterprise systems and larger business objectives. This is a manifestation of the “watermelon effect” at work: everything may look green on the outside, but the issues surface in red when you cut deep. Intentionally or unintentionally, a healthy assessment might be conveyed to higher tiers of management and to the public, while rot is taking hold deep in the system.

What’s more, many organizations focus on operational-level KPIs rather than business-level KPIs, which means the needle may not be moving toward better business performance. Organizations can also suffer due to inadequate technical expertise, domain expertise, and staffing relative to capacity. Undocumented and “tribal” knowledge locked within incumbents inside the organization contributes to siloed IT approaches and solutions that detract from achieving business objectives. Tribal knowledge may also, at times, be locked in archaic approaches and technologies which further hinder modernization.

Other factors that can drag enterprises down include inefficiencies in hybrid or work-from-home models, the ongoing tightening of compliance and regulatory standards, and a lack of unity and clarity across the organization in long-term growth and modernization strategy.

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