Published: 13 March 2023
Summary
Capabilities of enterprise conversational AI platforms are evolving to offer more domain-specific modules, broader multilingual support and wider-ranging integration options. This research helps application leaders choose the offerings that fit their requirements from a range of 19 vendors.
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Overview
Key Findings
Organizations demand more domain- and industry-specific conversational AI solutions incorporating a broader set of prebuilt modules that improve implementation timelines and business outcomes.
Emerging markets represent a largely unexplored frontier for conversational AI, where common challenges include the complexity of multilingual environments and the understanding of local needs in terms of, for example, channels and customer experience (CX).
Customer-facing use cases for chatbots are evolving toward the incorporation of more omnichannel user journeys and dependencies on a diverse range of natural language processing (NLP) and automation technologies, such as voice biometric authentication, robotic processing automation (RPA) or intelligent document processing
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- [24]7.ai
- Aisera
- Amazon Web Services
- Amelia
- Avaamo
- Boost.ai
- Cognigy
- eGain
- Google
- IBM
- Inbenta
- Kore.ai
- Laiye
- Omilia
- OneReach.ai
- Openstream.ai
- Sinch
- Sprinklr
- Yellow.ai
- Channels
- Voice
- Natural Language Understanding
- Dialogue Management
- Back-End Integrations
- Agent Escalations
- Analytics, Continuous Improvements
- Bot Orchestration
- Life Cycle Management
- Enterprise Administration
- Deployment Options
- Self-Service Chatbots
- Multilingual Chatbot Initiatives
- ITSM/HR Virtual Assistants
- Contact Center Automation
- Orchestration of Multiple Employee-Facing Bots
Gartner Recommended Reading
Critical Capabilities Methodology