Gartner defines artificial intelligence applications in IT service management as tools that augment and extend IT service management (ITSM) workflows using AI. These analyze ITSM data and metadata (primarily found in ITSM platforms) to provide intelligent advice and actions on ITSM practices and workflows, such as IT service desk and support activities. This software can either be a stand-alone product, capabilities within an ITSM platform or an add-on to an ITSM platform.
Gartner defines IT service management (ITSM) platforms as software that offers cohesive workflow management and automation for organizations to plan, deliver, support and improve integrated IT services. ITSM platforms provide a system of record for ITSM practices, including request, incident, problem, change, knowledge, service level and configuration management. Typically offered as SaaS, ITSM platforms are also available for on-premises deployments as per organizational needs. ITSM platforms are key tools used to manage IT support issues and aid employee productivity. IT leaders require robust ITSM platforms to drive business value in the services they provide, and are increasingly looking for these products to support digital business transformation outside IT. By capturing, tracking and reporting on service-related activities across the estate, the platform acts as a coherent system of record for ITSM-related actions. ITSM platforms boost infrastructure and operations (I&O) teams’ efficiency through automating processes, streamlining decision making and providing seamless integration with third-party applications. As organizational needs grow, advanced multichannel support features enhance the end-user experience, helping IT services remain agile and aligned with business goals.
Gartner defines manufacturing execution systems as a specialist class of production-oriented software that manages, monitors and synchronizes the execution of real-time physical processes involved in transforming raw materials into intermediate and/or finished goods. These systems coordinate the execution of work orders with production scheduling and enterprise-level systems like ERP, product life cycle management and quality management systems. MES applications also provide feedback on process performance, and support component and material-level traceability, genealogy and integration with process history, where required.
Software asset management (SAM) tools aim to decipher the complex and ever-changing world of software licensing. Core capability of SAM tools include discovery, normalization, reconciliation, optimization and reporting. SAM tools help address these common use cases: Discovery of software on on-premises, virtual and cloud platforms; Software entitlement management through a central repository, to track purchase data and contractual commitments; Spend management through demand forecasting, downgrading of entitlements, and reallocating of unused licenses or licenses assigned to leavers; Provision of software data insights by identifying licenses allocated to users and devices, software metering, providing usage data to procurement teams, and rightsizing. Ability to share data on software rationalization opportunities; Risk identification by detecting shadow usage, as well as end-of-life and end-of-support software; Increased collaboration between teams that participate in the software application life cycle, including all stakeholders internal and external to IT; Creation of reporting dashboards for operations teams and management.