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 business orchestration and automation technologies (BOAT) as a consolidated software platform that delivers enterprise process automation by enabling capabilities including orchestration of business processes, enterprise connectivity, low code development and agentic automation. A BOAT platform includes a cross section of certain capabilities from different markets such as business process automation (BPA), low-code application platforms (LCAP), integration platform as a service (iPaaS), intelligent document processing (IDP), robotic process automation (RPA), collaborative workflow management and document management. However, this list is not necessarily all-encompassing.
Gartner defines conversational AI platforms (CAIPs) as SaaS products that primarily enable the development of applications simulating human conversation across multiple channels and media. CAIPs leverage composite AI, including generative AI (GenAI) and natural language technologies. Conversations can use a mix of modalities such as text, voice and visual content. To support the building of conversational applications, platforms provide extensive coding options, from pro-code to no-code. Application areas include chatbots, virtual assistants (VAs) and conversational AI (CAI) agents. CAIPs are used to create, deploy and manage AI-driven conversational interfaces. These platforms enable businesses to develop VAs and conversational AI Agents that facilitate both customer-facing and internal interactions through pro-code/low-code/no-code tools. CAIPs empower businesses to centralize and democratize the development and management of multiple, diverse CAI initiatives, leading to more cohesive and efficient operations. The blend of capabilities provided by CAIPs is distinctive compared to those offered by other CAI solutions, such as targeted extensions for CAI found in other enterprise applications (e.g., CRM systems, contact center platforms) or stand-alone GenAI-native apps. In comparison, CAIPs are a better fit for strategic and scalable enterprise-grade CAI adoption.
Gartner defines the generative AI (GenAI) knowledge management apps/general productivity submarket as technologies that enable companies to better retrieve and contextualize information and insight from their knowledge bases, including enterprise AI search, conversational AI platforms, and productivity tools for communications and content development.
Generative AI (GenAI) model providers focus on developing and providing generative AI technologies and make them available to other developers, businesses and general public through APIs or commercial licenses. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. This layer of vendors offers access to commercial or open-source foundation models such as LLMs and other types of generative algorithms (such as GANs, genetic/evolutionary algorithms or simulations). These models can be provided for developers to embed into their applications or be used as base models for fine-tuning customized models for their software offerings or internal enterprise use cases. This helps businesses gain the benefits of advanced generative AI technologies while avoiding the high costs, expertise requirements and time needed to develop these technologies in-house. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Gartner defines intelligent document processing (IDP) solutions as specialized data integration tools that enable automated extraction of data from multiple formats and various layouts of document content. IDP solutions ingest data for dependent applications and workflows and can be provided as a software product and/or as a service. Organizations receive and process documents in multiple formats to enable activities such as onboarding new suppliers, receiving applications for loans or insurance claims. This results in large volumes of documents, the content of which is designed for human comprehension rather than machine processing. Extracting data from content is essential for document processing and the automated activities this supports. IDP solutions fulfill this role, augmented by and potentially replacing people. Documents are received in physical form, typically paper, which must be scanned for digitization, or in digital form, such as emails and PDFs. The content of these documents has varying layouts, ranging from structured formats, such as tabular or outline (e.g., list or hierarchy of headings) or invoices or contracts, to unstructured formats (i.e., free-flowing, such as an email). Layouts that fall between structured and unstructured, or mixing the two, are often referred to as semistructured.
Gartner defines robotic process automation (RPA) as software that automates tasks within business and IT processes using software scripts that emulate human interaction with the application UI. RPA enables a manual task to be recorded or programmed into a software script, which users can develop through programming or by using the RPA platform’s low-code and no-code GUIs. This script can then be deployed and executed into different runtimes. The runtime executable of the deployed script is referred to as a bot or robot.
Gartner defines task mining as a combination of techniques to infer useful information from low-level event data available in UI logs derived from the underlying operating system or through observing application UI interactions. This data comes from individual users or a cohort in the form of screen recordings, keystrokes, mouse clicks and data entries. Additional mining capabilities interpret the data by applying natural language processing (NLP), optical character recognition (OCR) and artificial intelligence (AI) techniques to correlate data in different ways. Task mining helps an enterprise identify inefficiencies and automation opportunities, increase worker productivity, and enhance the employee experience.