APAC CIOOutlook
About UsConferencePartner With Us
  • Technologies
    • Blockchain
      Data Intelligence and Management
      Digital Transformation
      FinTech
      Generative and Agentic AI
      Low Code No Code
      Mobile Application
      Networking
      Robotics
      Storage
      Wireless
  • Industries
    • Automotive
      Aviation
      Banking
      Construction
      E-Commerce
      Food and Beverages
      Healthcare
      Insurance
      Logistics
      Manufacturing
      Retail
      Supply Chain
      Travel and Hospitality
  • Platforms
    • Microsoft
      Salesforce
      SAP
  • Strategic Solutions
    • Business Intelligence
      Contact Center
      Corporate Finance
      CRM
      Cyber Security
      Data Center
      Enterprise Asset Management
      Enterprise Performance Management
      IT Infrastructure and Services
      Managed Services
      Procurement
      Unified Communication
      Workflow
  • Home
  • CXO Insights
  • Leadership Perspectives
  • Innovation Insights
  • Research
  • News
  • Whitepapers
  • CXO Awards
#

Apac CIOOutlook Weekly Brief

×

Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from Apac CIOOutlook

Subscribe

loading

THANK YOU FOR SUBSCRIBING

  • Home
  • News

Importance and Benefits of ML in IT Service Management

The traditional IT service management (ITSM) solutions have become ineffective in maintaining customer satisfaction levels and meeting the rising customer demands in a fast-paced digital world. 

By

Apac CIOOutlook | Friday, January 24, 2020

The traditional IT service management (ITSM) solutions have become ineffective in maintaining customer satisfaction levels and meeting the rising customer demands in a fast-paced digital world.

FREMONT, CA: The service desk acts as a 'go-to' place in an organization for every IT related issues and needs such as managing incidents, service disruptions, changes, or requests.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

The scope of work in the service desk is enormous and wide-ranging, depending on the nature and size of the organization. Hence, as a part of the critical function, the service desk needs to be managed appropriately. The traditional IT service management (ITSM) solutions have become ineffective in maintaining customer satisfaction levels and meeting the rising customer demands in a fast-paced digital world. Thankfully, technology has changed the way work is done across all industries around the world.

SolarWinds IT Trends Report 2019: Skills for Tech Pros of Tomorrow points out that due to interruptions with day-to-day support-related issues, 79 percent of IT managers weren't able to spend sufficient time on value-added business activities or initiatives. As a result of which they end up making incorrect manual entries into a problem log leading to misinformed decision-making. An overburdened manager is more likely to fall the victim of manual or human errors.

With the changing landscape of IT enviromments, it's crucial for IT service desks to adopt emerging technologies. Data explosion in recent years has exaggerated the pressure for IT professionals. The sigh of relief is that automated processes and ML have alleviated the pressure significantly. Gone are the days when AI and ML were just buzzwords. Industries across the world are incorporating these technologies to enhance and improve operational efficiencies.

Be it predictive analytics, performance monitoring of networks, business intelligence, applications, and systems, or even for its importance in self-driving cars, AI and ML are transforming the IT space. It is interesting to note the applications of ML when it comes to ITSM. The service desk, being an essential business operator, can employ ML to streamline processes, reduce time-intensive and manual tasks, which frees up time for other projects and training to deliver business-wide transformation.

Efficient Handling of Incidents

ML has the potential to cut down the incident resolution time almost to half. With the use of ML, technicians are no more required for incident resolution, and users can easily search for solutions themselves. Chatbots have taken over the role of voice technicians and can give information to end-users by providing easy access to relevant knowledge base articles based on their queries, without them having to log a ticket. ML can help desks to route tickets to the appropriate technician or support group through their past experiences.

Asset Management

Traditional and obsolete IT assets can cause performance degradation for employees who rely on traditional assets to do their jobs. Organizations spend a lot of money on software and hardware because of asset management solutions with poor transparency. Asset management can turn this around with solutions like ML technology that can help to track their performance based on insights from performance levels or incidents associated with a given asset.

Problem Prediction and Prevention

Using large datasets of past performance, ML can make an analysis of incidents to predict future problems. This predictive capability of ML can help save money, time, and effort for the entire organization as steps can be taken before the severity or impact of the incident increases.

Automated Ticket Routing Supported by ML

To ensure accurate routing, automation rules rely heavily on data like categories and subcategories when end users submit a ticket. ML helps facilitate this process by providing end-users with suggestions for the most relevant categories and subcategories for a given ticket.

See Also: Top IT Service Management Solution Companies

More in News

The Strategic Value of Strong Supplier Relationships

...Read more

Quantum Technology: Driving APAC Industrial Transformation

Quantum technology is significantly advancing the fields of computation, communication, and sensing, thereby creating opportunities that were previously considered theoretical. Various organizations and research institutions are engaged in competition to develop more reliable qubits, implement effective error correction techniques, and establish scalable systems capable of addressing challenges that surpass the capabilities of classical computers. Emerging practical applications span a range of areas, including the acceleration of drug discovery, enhancement of cybersecurity measures, and optimization of complex logistical operations. Although challenges such as hardware fragility, environmental sensitivity, and substantial development costs remain, ongoing innovations in materials, cooling systems, and quantum algorithms are progressively mitigating these issues. Consequently, quantum technology is a domain where promise and progress are evolving in tandem. How Does Quantum Technology Benefit Industries Today? Quantum technology is starting to deliver real benefits across several industries by solving problems that were previously too complex or time-consuming for classical systems. In pharmaceuticals, quantum simulations are helping researchers model molecular interactions more accurately, speeding up drug discovery and reducing trial-and-error testing. Finance companies are exploring quantum algorithms to optimize portfolios, manage risk, and detect fraud faster than traditional systems. Even logistics and manufacturing are seeing advantages, with quantum-based optimization improving supply chain efficiency and resource allocation in ways that were once impossible at scale. Beyond computational speed, industries are also benefiting from advances in quantum sensing and communication. Quantum sensors offer unprecedented precision in fields like navigation, energy exploration, and environmental monitoring, while quantum encryption promises highly secure communication channels that could transform data security. By integrating these capabilities, businesses can make smarter decisions, reduce costs, and innovate faster. While adoption is still in early stages, the combination of computation, sensing, and secure communication is already giving forward-looking companies a competitive edge, showing that Quantum technology is moving from theory into tangible industry impact. What Innovations Are Shaping the Future of Quantum Technology? The future of Quantum technology is being driven by innovations that make quantum systems more stable, scalable, and practical for real-world use. Advances in qubit design, materials, and error-correction techniques are improving reliability, while hybrid quantum-classical algorithms allow businesses and researchers to harness quantum capabilities even before fully fault-tolerant machines are ready. This is opening early applications in areas like finance, logistics, and healthcare, where complex problems can be solved faster and more accurately than ever before. Moreover, breakthroughs in quantum communication, sensing, and software are expanding its reach. Quantum networks promise ultra-secure data transfer, while quantum sensors deliver unmatched precision in navigation, energy, and environmental monitoring. Cloud-based platforms are also making quantum tools accessible to smaller organizations, democratizing experimentation and innovation. Together, these advancements are positioning Quantum technology as a transformative force that can reshape industries, accelerate scientific discovery, and unlock entirely new possibilities. ...Read more

Mastering PPP project analysis, financing, contracts & transaction management techniques

Infocus International is delighted to bring one of their best virtual workshops,  Public-Private Partnership (PPP)  that will be set to commence  17 August 2026 . We need new infrastructure. Roads, airports, schools, hospitals and housing: the list is enormous and growing. Yet severely limited budgets, economic uncertainty caused by volatile commodity prices, and deficits continue to prevent government at all levels from delivering the kinds of structural change that has always been needed. In response, some countries have developed successful PPP programmes. Merely grasping the concepts of PPP does not do justice to our great responsibility of having an ownership in the country’s future. We already know what we need to do, now is the time to really discover HOW. One of our participants from  Electricity Generation Company (Malawi) Ltd  shared that, “ The facilitator was very knowledgeable on the subject matter, very responsive to questions and innovative in the delivery of the PPP training program. The knowledge gained will assist me in productive participation in ongoing and planned PPP Projects in my country.” Another participant from  PNG Ports Corporation  also mentioned that,  “This is an excellent course for anyone involved in PPP. Highly recommended.” Benefits of Attending • Use best practices from international case studies of successful PPP transactions and common practical pitfalls to avoid • Design and manage PPP legal, regulatory & institutional frameworks to attract investors and complete PPP transactions • Apply models for the efficient design and completion of PPP feasibility studies • Understand project financing requirements and evaluate PPP financial models for both affordability and bankability • Evaluate and apply different credit enhancement techniques to ensure PPP bankability, including blended financing, viability gap funding (VGF), partial guarantees, risk insurance products, output-based aid (OBA) and other financial instruments • Design PPP transaction implementation plans and manage & oversee PPP transaction advisors for reaching commercial closure and financial closure • Models for PPP tender documents, including PPP Project Information Memoranda (“InfoMemos”), Requests for Qualifications (RFQs), Requests for Proposals (RFPs) • International models for designing and drafting PPP contracts & agreements • Environmental & social impact mitigation techniques to structure sustainable private investments in public infrastructure • Plans for managing sustainable PPP contracts including ensuring technical performance, quality of service delivery, price review & adjustment regulatory models, legal contract management and alternative dispute resolution (ADR) techniques Want to learn more? Simply email  media@infocusinternational.com  to register your attendance. For more information, please visit  https://www.infocusinternational.com/ppp-online ...Read more

Deploying Big Data Analysis to Develop IoT Solutions

Data from various sources forms the basic foundation of businesses. In the present times, the improvement of connectivity in the IoT space has resulted in the transfer of huge chunks of data. Therefore, there is a need for big data analytics in IoT in order to address the challenges related to management of large-scale, through the data pipeline architecture. To begin with, data pipeline is the process concerned with the movement of data through an organization. Once data enters into an organization, the stage is referred to as data ingestion. Next in the process is the stage of data transportation from the data ingestion stage to the other stage is known as data collector. Followed by this, the data moves through the processing stage wherein appropriate measures are taken to store it. Data storage stage steps up to the data query stage where it is analyzed through interactive queries. The final stage is concerned with valid presentation of data in different forms of business infographics, such as graphs or statistics. Data generated in the IoT space requires a data management system with the following qualities: •  It should be adapted to manage and process a huge number of data sources, keeping pace with the continuous increase of IoT devices. •  The data management system must have a prompt response time in order to notify the concerned segment of the business in case of failures while processing or storing data. •  The system must be able to scale data on multiple parameters such as a number of devices, storage, and messages. •  Diversity and flexibility are required to process use cases and simultaneously accommodate new use cases. •  The data management system should be cost-effective. All the above criteria suggest that IoT requires interacting with big data analytics tools in order to manage such big chunks of data. ...Read more

I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info

APAC CIOOutlook
Follow on LinkedIn

About

  • Home
  • About Us
  • Partner With Us

Stay Connected

  • Subscribe
  • Newsletter
  • Sitemap

Contact Us

  • editor@apacciooutlook.com
  • sales@apacciooutlook.com
  • marketing@apacciooutlook.com

Legal

  • Editorial Policy
  • Privacy Policy
  • Terms of Use

© 2026 APAC CIOOutlook. All rights reserved. Headquarteblue in Fort Lauderdale, FL, USA.

This content is copyright protected

However, if you would like to share the information in this article, you may use the link below:

https://www.apacciooutlook.com/news/importance-and-benefits-of-ml-in-it-service-management-nwid-7288.html