How automation can turn a mistake into a customer retention opportunity

Major incidents are increasing in frequency and complexity. Our recent survey of 300 IT operations decision makers found that 65% have experienced a #majorincident in the past 12 months while 52% see incidents taking longer to resolve than they did before. Download our Major #IncidentManagement Report to gain critical insights into: 📈 Incident frequency: Understanding the recent rise in major incidents and the underlying factors fueling this increase 🤔 Current approaches: An assessment of how enterprises are currently operating their major incident management functions 👍 Strategic evolution: How organizations are evolving their processes and tooling to effectively face greater operational threats ✅ Defining best practice: A detailed look at the core characteristics of best-in-class major incident management 🤖 The #AI opportunity: The key benefits and concerns around introducing Artificial Intelligence (AI) into the major incident management lifecycle Download the report now to benchmark your organization's strategy against peers and prepare for the future of incident resolution. https://lnkd.in/ei-7Xje3

OPERATIONAL REALITIES CRYING OUT FOR INTELLIGENT AUTOMATION RIGHT NOW, AND NO ONE IS LISTENING. Part 2: Service Desk Triage: The $260K Annual Time Sink Experienced analysts spend 30-40% of their time reading tickets, categorising requests, and routing them. It's mind-numbing work that burns talent. Incident Management: Predicting Fires Before They Start Traditional incident management is reactive firefighting. Modern infrastructure generates vast telemetry data humans cannot process in real time. Knowledge Management: Finding Needles in Digital Haystacks Decades of knowledge scattered across platforms. Analysts waste hours hunting information or reinventing solved problems. Traditional search is keyword-dependent and context-blind. Change Management: Risk Assessment at Machine Speed Manual change risk assessment is time-consuming and prone to blind spots. AI analyses thousands of previous changes, identifying patterns that predict success versus failure. Capacity Planning: From Guesswork to Precision Traditional capacity planning involves spreadsheets, historical trends, and hopeful extrapolation. Always reactive and frequently wrong. AI analyses usage patterns, seasonal variations, and business cycle impacts simultaneously. Security Operations: Finding Threats in the Noise Security teams drown in alerts. Thousands of daily events, mostly benign. Alert fatigue leads to complacency, and complacency leads to breaches. Documentation Generation: Capturing Knowledge Automatically Engineers solve complex problems brilliantly, then document poorly or not at all. Dangerous knowledge gaps emerge. AI generates first-draft documentation from system logs, ticket resolutions, and change records. The Reality Check These seven areas deliver immediate ROI with manageable implementation complexity. You need targeted automation solving specific pain points. Winners aren't doing everything simultaneously. They pick two or three high-impact areas, implement thoughtfully, prove value, then expand. Start with your biggest pain points Where do talented people waste time on repetitive work? Where do incidents keep recurring? Where does knowledge get lost? That's where AI earns its keep. Read Article Here: https://lnkd.in/exSfmhiD

New SolarWinds report: Gen AI significantly drops incident response time for ITSM teams Bill Tanner | 5 November, 2025 SolarWinds has released its 2025 ITSM Report, which outlines a clear delineation between Information Technology System Management systems that leverage GenAI in their operations and those that do not. The report analysed more than 2,000 ITSM systems and more than 60,000 aggregated and anonymised customer data points. Over the past year, IT teams have moved from experimenting with automation to actively integrating Generative AI into their workflows – reshaping how they diagnose issues, resolve incidents and deliver service. The GenAI effect: Faster resolutions, smarter service The data shows that organisations using GenAI in ITSM significantly reduce incident resolution times. SolarWinds analysts examined key AI-driven capabilities – such as automated ticket responses, knowledge article recommendations and incident summaries – and compared resolution times before and after enabling GenAI. The results revealed: • The average resolution time before GenAI: 27.42 hours • After GenAI enablement: 22.55 hours • Average time saved per incident: 4.87 hours • Relative reduction: 17.8% The report also reviewed the resolution times of organisations that have yet to implement GenAI into their ITSM functions. The data showed a much wider gap between GenAI enablement/non-enablement than the group mentioned above: • Average incident resolution time (non-GenAI customers): 32.46 hours • Average for GenAI customers post enablement: 22.55 hours • Time difference: 9.91 hours per incident • Relative improvement: 30.5% GenAI adopters represent more mature, innovation-driven ITSM operations. This consists of teams already embracing self-service, knowledge management and automation. Their adoption signals a culture ready to drive broader organisational innovation and transformation. Reclaiming time and producing ROI When IT teams significantly reduce time spent on manual tasks, they reclaim valuable hours that can be redirected toward strategic initiatives – turning efficiency gains into tangible ROI for the organisation. According to the data, which culminated all incidents logged from August 1, 2024 to July 31, 2025, GenAI-enabled organisations saved a cumulative 323,343 hours after GenAI enablement. “By leveraging GenAI, ITSM teams can reclaim time and resources once spent on routine tasks, enabling them to focus on strategic initiatives that drive real business value,” said Lauren Okruch, Senior Manager for ITSM, SolarWinds. “Looking ahead, embracing technologies like GenAI isn’t just about efficiency – it’s a strategic imperative for organisations aiming to innovate, stay ahead of change and transform IT from a support function into a proactive driver of growth.” For more on the 2025 State of ITSM Report visit: https://lnkd.in/giAprr9U https://lnkd.in/gJBNicwv

We've all felt that AI should be making a difference, but now we have the data: SolarWinds ITSM teams using GenAI are saving an average of 4.87 hours per incident. That's an almost 18% drop in resolution time! For me, this is huge for the process of turning IT from a cost center to a strategic business partner—it's not about replacing people, it's about giving them back nearly 5 hours to work on the big stuff, not just the ticket queue. A huge thank you to Michael Vizard and the Techstrong.IT team for the great chat and insights about AI and our report. 👉 Read the article: https://lnkd.in/ewbCFmUr 📋 Get the full State of ITSM report: https://lnkd.in/ed-kYCW3 #SolarWinds #ITSM #GenAI #ServiceDesk #AI #ITOps #Techstrong

Downtime isn’t an option anymore and manual incident response just can’t keep up 🤷♀️ With Servicely, we're built on AI (not bolted on), so our incident management capabilities speed through resolution to get you up and running faster ✨ In our latest blog, we look at how AI-powered incident management is transforming the game: automating detection, prioritising alerts, and even triggering fixes before issues spiral. 👉 Read it here now: https://lnkd.in/gwT59mtm

A new SolarWinds report reveals that IT service management teams using generative AI are saving an average of 4.87 hours per incident and an 18% reduction in resolution time. Based on data from over 2,000 ITSM systems and 60,000 anonymized data points, the findings suggest AI automation could save mid-sized IT teams managing 5,000 incidents annually more than 24,000 work hours or roughly $680,000 each year. Read the full analysis here: https://lnkd.in/eDwhmT7P #ITSM #AI #SolarWinds

🔗 Read the blog: https://lnkd.in/guBafS5a Quality isn’t just a department — it’s the foundation of trust and resilience. This blog explores how modern eQMS platforms, powered by Akitra’s Agentic AI, unify compliance, risk, and operational excellence into one intelligent ecosystem. From document control to CAPA automation, see how smart quality management drives continuous improvement and audit readiness. Reimagine quality for the era of automation and intelligence. #eQMS #AgenticAI #ComplianceAutomation #Akitra #QualityManagement #RiskManagement #ContinuousImprovement #AuditReadiness #OperationalExcellence

Automation isn’t just a feature. It’s foundational. Over the past few years, I’ve had the opportunity to lead enterprise-wide initiatives across federal and commercial environments where automation was the catalyst for transformation. Before Automation: At one federal agency, manual data reconciliation across siloed systems consumed over 1,200 staff hours monthly. Security incident triage was reactive, fragmented, and slowed by human bottlenecks. After Automation: By deploying automation for repetitive data validation and integrating SOAR tools for real-time alert correlation and response, we achieved:  ➡️ 85% reduction in manual processing time  ➡️ 60% faster incident response ➡️ $1.2M in annual cost savings These weren’t just technical wins but cultural shifts. Teams evolved from task execution to strategic, proactive initiatives. We started with a cross-functional discovery sprint to identify high-friction processes. Using a scoring framework (ROI, risk reduction, mission impact), we prioritized automation candidates. Our playbook then enabled repeatable success across departments. On the security front, we piloted workflows to automate threat intelligence ingestion, alert enrichment, and ticketing. The result? Faster response times, reduced analyst fatigue, and fewer false positives. Automation isn’t about replacing people. It’s about empowering them. (Let’s be honest, we don’t have enough cybersecurity talent as it is!) As we scale, we’re also investing in upskilling, governance, and AI frameworks to ensure sustainable transformation. How are you using security automation in your organization? Drop a comment below. I'd love to hear where you're seeing the most value. 

Is AI making a difference in ITSM? This report has some positive news... With data from more than 2,000 #ITSM systems and over 60,000 anonymized incident records, this year’s State of ITSM report from SolarWinds takes a close look at how service teams are adapting to new tools, especially generative #AI (#GenAI), and what measurable results they’re seeing. https://lnkd.in/ehpEAFtQ

"When “Incident Management” Becomes Personal Lessons from the hardest service I’ve ever supported. “Poor data drives poor decisions — in any service.” We repeat that mantra in ITSM all the time. But I only understood its full weight when I saw how bad data shaped my son’s care. During his hospital admission, every action and reaction was recorded as an “incident.” But as I read the reports, something crucial was missing — context. There was Behaviour and Consequence, but never the Antecedent. Without it, the picture was dangerously incomplete. To the untrained eye, the data showed risk. But viewed through the right lens, it revealed distress, miscommunication, and a system reacting to symptoms instead of causes. Many “incidents” weren’t incidents at all — they were communication attempts: • a gesture for space • a cry from sensory overload • resistance after being woken suddenly So I did what any Service Management professional would do: I analysed the data, reviewed classifications, and challenged definitions. What I found was a data quality failure — inconsistent categorisation and missing context. Once we redefined categories — separating true risk events from environmental triggers and communication behaviours — everything changed. Staff responses improved, restrictions eased, and after six weeks indoors… my son finally went outside again. 🌤️ It reminded me of a core ITSM truth: “Poor data drives poor decisions — in any service.” Incident Management shows what happens. But only with quality data, context, and follow-through via Problem Management do we uncover why — and drive meaningful improvement. This lesson hit home again this week at the itSMF UK conference, where discussions around AI in service management reinforced the importance of data quality. AI learns from the data we give it — and if that data lacks context or is misclassified, the AI will automate misunderstanding rather than insight. Before we adopt AI in ITSM, healthcare, or any human-centred field, we must invest in: ✅ Data integrity ✅ Thoughtful categorisation ✅ Human empathy AI readiness isn’t a technology milestone — it’s a data and governance milestone. Because whether it’s IT or healthcare — when we fix the data, we fix the system. #ITSM #IncidentManagement #DataIntegrity #ProblemManagement #ServiceManagement #ContinuousImprovement #Leadership #Neurodiversity #EmpathyInAction #HumanCentredDesign #ITIL #ServiceDesign #ThoughtLeadership #AIinITSM