Gartner defines the CRM customer engagement center (CEC) as a cohesive set of software built around core case management tools, dedicated to providing customer service and support by engaging with customers, and intelligently orchestrating the processes, data, systems, and resources of an organization. CRM CEC is a key software platform used in delivering end-to-end customer service and support experiences. It enables customers to engage and interact with an organization as well as for the organization to orchestrate its internal and external processes and resources to fulfill the customer’s expected outcome.
Gartner defines cloud-based CRM for government as systems that manage, streamline and automate interactions among agencies and citizens, broader constituents, businesses, and other organizations (defined here as constituents). These systems aim to improve service delivery, increase efficiency and strengthen trust by consolidating service requests, inquiries and constituent sentiment from multiple channels into a unified system; supporting proactive constituent management and outreach; and enabling a single view of constituents to support personalized services.
Gartner defines conversational AI platforms (CAIPs) as platforms primarily used for developing applications simulating human conversation across multiple channels and on a mix of modalities such as text, voice and visual content. CAIPs leverage a composition of AI techniques, including classic natural language processing (NLP), and generative AI (GenAI) and agentic AI architectures. To support the building of conversational applications, CAIPs principally provide low-code and no-code coding options. Application areas include AI assistants and conversational AI agents. Conversational AI platforms are designed to address the increasing demand for organizations to efficiently build, deploy and manage AI-driven conversational systems at scale, addressing the requirements of both employee experience and customer experience use cases. While they may offer some predefined AI assistants or AI agents that can be modified, the primary focus of a CAIP is to equip organizations with tools for building customized conversational AI applications. CAIPs typically embed specialized, dedicated and feature-rich tooling for language-specific NLP and multimodal interactions, as well as conversational flow building and analytics. By offering a unified environment that supports low-code and no-code development — and, in some cases, extends to pro-code and GenAI-assisted options — CAIPs empower technically savvy business users, including citizen developers, to create and orchestrate both customer-facing and internal AI assistants and conversational agents. Unlike AI engineering environments, which primarily serve AI engineers, software developers and data scientists, CAIPs are purpose-built for broad enterprise adoption, enabling strategic, scalable and organizationwide conversational AI initiatives.
Gartner defines a customer service knowledge management system as a collection of technologies that enable the timely provision of accurate, contextually relevant information to an organization’s customers and customer service and support employees. They provide content capture, creation, contextualization and secure storage as core capabilities, in addition to search and content aggregation. The purpose of a customer service knowledge management system (CS-KMS) is to serve as a single trustworthy source of information that ensures uniform and accurate knowledge is made available to users. Organizations use these systems to provide internal customer service agents with current, accurate, trusted knowledge and to provide timely, accurate information to customers seeking self-service support. CS-KMS platforms or tools are used to replace traditional knowledge bases; manage content; and power conversational AI, chatbots and AI agents. They address business problems such as inconsistent service levels and information across channels, difficulty for users or agents to find needed information, and the manual burden of keeping knowledge content updated and complete. CS-KMS platforms or tools help organizations achieve several positive outcomes. They can enhance service consistency and improve client interactions, as well as improve operational efficiency. By providing easily accessible and consistent information, these systems aim to improve quality and consistency of search results, support the efficient onboarding of new employees, and generally lead to a better customer experience (CX). AI-powered CS-KMS features enable automation, like generating knowledge articles from call interactions, and allow for more advanced applications such as retrieval-augmented generation (RAG) to deliver context-specific answers from proprietary data.
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.
Knowledge Management (KM) Software helps organizations centralize, organize, and share information efficiently across teams. It provides a centralized repository for storing diverse content types—such as documents, presentations, and multimedia—making knowledge easily accessible and searchable. A robust search functionality ensures quick retrieval of relevant information, while features like file version history, access control, and content editing enhance collaboration and governance. These capabilities reduce duplication of effort, preserve institutional knowledge, and streamline workflows. KM software is widely used by customer support, product and operations, HR and training, and IT and compliance teams—any function that depends on consistent, accurate, and easily retrievable information.