Constellation ShortList™ Conversational AI

About This Constellation ShortList™

Conversational AI platforms simulate human conversation, enabling self-service and intelligent digital interactions between humans and machines. In early applications, rudimentary chatbots were the earliest use cases and limited to basic information delivery (e.g.: self-service FAQ responses) utilizing natural language processing (NLP) to understand and process human language. As Generative AI advances, these conversational copilots and assistants not only interact to solve problems but can engage with personality —and even empathy—to create dynamic bi-directional experiences between humans and machines.

Conversational AI uses a combination of AI technologies and techniques from machine learning (ML), natural language understanding (NLU), and NLP to establish robust sentiment and tone analysis, intent understanding, and cognitive analysis. Generative AI models continued to push the adoption and popularity of chatbots to better understand and respond to natural language, generate personalized responses and create content that is more resonant to a user’s specific questions, situation or needs. The year ahead will see a similar explosion in conversational AI platforms as agentic AI brings new opportunity to advance virtual assistants beyond early use cases in contact centers and marketing applications.

Enterprise Conversational AI systems are used in many applications including chatbots, virtual personal assistants, Intelligent Virtual Agents (IVA), Interactive Voice Response (IVR) systems, voice assistants, virtual concierge, and intelligent copilots. Constellation Research continues to see more efficient and effective conversational AI systems being prototyped, beta tested and rolled out across the enterprise as “co-pilots” focused on both functional and industry specific tasks, especially in retail, healthcare, education, transportation, e-commerce, entertainment, hospitality, insurance, banking, and financial services.

Expect to see added pressure put on this space as enterprise technology leaders continue to voice concerns around training, access to proper data/systems, oversight, compliance, maintenance, accuracy of personalization and localization have been addressed. Also expect to see more vendors within functional segments (i.e. service, contact center, sales, IT service management, etc.) include conversational AI into their offerings, pushing customers to expect even more innovation from stand-alone platforms to push the needle and justify costs outside of existing stack environments.

Threshold Criteria

Constellation considers the following criteria for these solutions:

• Context awareness 
• Support for multiple most common human languages 
• Automated reinforcement learning to improve outcomes 
• Capacity to understand user intents and needs, personalizing conversations based on real time customer context 
• Automated workflows including case escalation to smoothly transition service to an available human agent 
• Customizable workflow management 
• Natural Language Processing (NLP) capabilities 
• Natural Language Understanding (NLU) capabilities 
• Access to generative AI capabilities including integration with closed or open source LLMS 
• Integrated with backend systems (ERP, HR, etc) 
• Integrated with front end CX systems (CRM, Service, Knowledge and content management systems) 
• Localization capabilities 
• Security, Privacy, Authentication and Compliance 
• Options to understand accents, pronunciation, emotions, sentiment, sarcasm, idioms, and colloquialism 
• Robust conversational analytics and reporting 
• Scalability 
• Omnichannel capability 
• Industry specific enhancements