IT teams are expected to drive innovation, strengthen resilience, and support growth while most of their time and budget remain committed to maintaining existing systems and services. Info-Tech Research Group’s recent blueprint, Harness AI to Reduce the Cost and Effort of KTLO in IT Operations, helps CIOs identify where targeted AI investments can reduce the KTLO burden, reclaim capacity for higher-value work, and build practical AI skills.
, /CNW/ — Routine IT operations and maintenance consume 82.6% of IT spend and 66% of IT teams’ time and effort, according to Info-Tech Research Group’s IT Spend & Staffing Benchmarking data. That allocation leaves only a fraction of IT capacity available for new technology initiatives, operational improvements, and transformation.
To help organizations address this imbalance, Info-Tech has published its Harness AI to Reduce the Cost and Effort of KTLO in IT Operations blueprint. The resource helps CIOs identify AI-enabled opportunities to reduce the cost and effort of keeping the lights on (KTLO), quantify their potential value, assess organizational readiness and risk, and build a portfolio of initiatives for launch.
“KTLO has always been treated as an unavoidable tax on IT, but that mindset is outdated,” says Fred Chagnon, principal research director at Info-Tech Research Group. “Targeted AI investments can help CIOs reduce low-value manual work, reclaim budget and staff time, and reinvest both in innovation. The result is an IT organization that runs smarter and has more capacity to deliver value.”
Info-Tech cautions that common cost-cutting responses can deepen the KTLO problem. Running hardware and software beyond end of life can increase technical debt and security risk; using outsourcing primarily as a cost-reduction strategy can overlook its value in reclaiming capacity and accessing specialized expertise; and eliminating growth or transformation initiatives can starve the business of future value.
Five AI Tactics for Reducing KTLO Cost and Effort
Info-Tech’s research identifies five AI-enabled tactics that IT leaders can assess based on their operational priorities, technology environment, and organizational readiness:
- Intelligent incident management and AIOps: Detect anomalies, correlate events across operational silos, support predictive maintenance, and automate common remediation activities.
- Autonomous patch and vulnerability management: Automate patch prioritization, deployment, and verification to reduce manual effort and support more consistent compliance.
- Smart data classification, cleaning, and curation: Reduce duplicate and outdated data, storage bloat, and manual data management while strengthening the governed data foundation required for AI.
- Generative AI service desk and conversational self-service: Deflect routine Tier 1 requests, improve access to support, and free service desk staff to focus on more complex work.
- AI-assisted script, documentation, and code generation: Accelerate scripting and documentation, preserve knowledge about legacy systems, and reduce the effort required to maintain them.
Info-Tech’s Four-Step Framework for AI-Enabled KTLO Reduction
Identifying a potential use case is only the starting point. CIOs also need to understand its expected value, implementation requirements, and organizational risks before committing resources. To guide that evaluation, the Harness AI to Reduce the Cost and Effort of KTLO in IT Operations blueprint applies a four-step assessment process across all five tactics:
- Uncover opportunities. Identify manual, repetitive, and resource-intensive KTLO activities that could benefit from AI and automation.
- Quantify the value. Estimate the labor time and costs associated with each activity, then project potential cost reductions, reclaimed effort, and time to value.
- Assess readiness and risk. Evaluate organizational constraints such as data quality, integration requirements, process maturity, skills, change readiness, and implementation risk.
- Blueprint for launch. Define viable initiatives, accountable teams, expected outcomes, and actionable milestones, then consolidate them into a Quantified KTLO Reduction Initiative Portfolio.
KTLO reduction can also serve as a workforce development opportunity. Applying AIOps, automation, and generative AI to familiar, measurable processes gives IT teams practical experience in a controlled environment and prepares them to lead broader AI initiatives across the organization.
The Harness AI to Reduce the Cost and Effort of KTLO in IT Operations blueprint and its supporting Quantified KTLO Reduction Initiative Portfolio provide CIOs with practical guidance for turning assessed opportunities into executive-level investment proposals. By connecting projected cost and effort reductions with readiness, risk, time to value, and implementation milestones, the research helps leaders move KTLO discussions from short-term cost cutting to measurable reinvestment in innovation.
For exclusive and timely commentary from Info-Tech’s experts, including Fred Chagnon, and access to the complete Harness AI to Reduce the Cost and Effort of KTLO in IT Operations blueprint, please contact [email protected].
About Info-Tech Research Group
Info-Tech Research Group is the “get things done” partner for over 30,000 IT, HR, and marketing leaders worldwide. The fastest growing research and advisory firm, Info-Tech enables leaders to make well-informed decisions and transform their organizations through AI, strategic foresight, step-by-step methodologies, practical tools, industry-leading advisory, and training programs. For nearly 30 years, tens of thousands of private and public organizations have trusted Info-Tech to lead their most important initiatives through periods of change and deliver outcomes that truly matter.
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SOURCE Info-Tech Research Group
