Conversational AI Building Platforms

The KuppingerCole Market Compass reviews the market for conversational AI building platforms focused on chatbot solutions that use machine learning to continuously improve conversations and integrate into existing customer touchpoints such as websites, portals, e-commerce, and CRM. Purely voice-only and rule-based systems are excluded. After a hype peak in 2016 and subsequent disillusionment driven by “gadget” implementations, the market is maturing as chatbots become embedded in broader digitalization initiatives across marketing, sales, and service management, with growing adoption also in HR and internal communication. Significant market growth is expected in the coming years.

Selecting a platform should start with a clearly defined business case and requirements. Conversation quality matters, but platform fit also depends on channel/device coverage, multi-language needs for international rollouts, integration with third-party and back-end systems, deployment preferences (cloud vs. on-premises), scalability, available internal resources, and change management. Solutions vary from narrowly focused chatbot platforms that rely on connectors to broader suites that combine data management, marketing automation, and CRM; neither approach is universally superior.

Core capabilities include hybrid conversational methods (ML plus rules), personalization using conversational and third-party data, multi-platform and multi-language support, rich content delivery, strong integration capabilities (messengers, social, CRM, e-commerce, service desks, HR), analytics to improve flows and business outcomes, and robust security/privacy controls for personally identifiable information, including GDPR compliance. Advanced capabilities may include human handover, cross-device conversation persistence, usable administration tooling, industry-specific training content, and optional voice interaction.

The report evaluates vendors including Aivo, AWS, Clustaar, HubSpot, IBM, Microsoft, MobileMonkey, and SAP, highlighting Microsoft for capabilities, IBM for machine learning, and Aivo for usability.

• Conversational interfaces experienced hype in 2016 followed by disillusionment in subsequent years.
• The Market Compass covers chatbot-focused conversational AI building platforms with machine learning for continuous improvement.
• Voice-only solutions are not considered in this report.
• Rule-based solutions without machine learning capabilities are excluded from the Market Compass.
• ELIZA is described as a 1966 MIT-developed chatbot that successfully passed the Turing test.
• Personally identifiable information is commonly present in conversational data.
• GDPR is cited as an example of relevant legislation for compliance when processing personally identifiable information.
• IBM Watson Assistant is stated to have been launched in 2013 and was formerly called Watson Conversation.
• IBM Watson Assistant (public cloud SaaS version) is stated to converse with 82 million users per month as of October 2019.
• Amazon Lex is stated to currently support only English language, with Amazon Translate usable to build text chatbots in other languages.

• “Conversational interfaces experienced hype in 2016, followed by some disillusionment in the next years, as many solutions were technical gadgets rather than delivering real value.”
• “Ideally, the choice of a conversational AI building platform is based on a proper business or use case, considering individual requirements, as there are many solutions on the market, each with specific strengths.”
• “The quality of the conversational flow is only one criterion among many.”
• “A ‘standalone’ conversational platform is just a technical gadget.”
• “Connecting with data pools will be crucial in order to enable communications that customers expect in future—personalized, individual information in real time is crucial in this case to meet user experience expectations.”
• “Constant improvement, embedded learning ability, and agility are keys to establishing a successful chatbot that goes beyond a marketing gimmick.”
• “Some vendors offer solutions with a narrow focus on conversational interfaces and offer connectors to integrate with other systems.”
• “Others offer comprehensive suites covering other aspects, such as data management, marketing automation, and customer relationship management.”
• “In every case, it is crucial to consider a clear business case, including change management procedures.”
• “In a heterogenous market there exist various ‘flavors’ of conversational AI building platforms.”