Artificial Intelligence in the Enterprise Point of View - Competitive Review
Artificial Intelligence in the Enterprise
A competitive review of Enterprise AI and Machine Learning platforms and technologies.
  • Project Year
  • Creator Name
    Kevin Grant
  • Organization
    TD Bank
  • City
  • Country
  • Creation Date
    03 February 2018
  • Modification Date
    13 March 2021
  • Version

Successful Enterprise Intelligent Assistant implementations:

  • 1) Reduce operating costs while improving customer experience and satisfaction
  • 2) Automate the handling of routine or repetitive activities
  • 3) Optimize the interaction for both Customer and Agent, when they require a human touch

Enterprise Intelligent Assistants
Overall Market

  • There is an explosive growth in Enterprise spending on licenses, services and platforms.
  • Enterprise spending on Intelligent Assistants is exceeds $500 million by 2017 – on its way to being a billion dollar opportunity in 2020.
  • Enterprise spending on Enterprise Intelligent Assistant solutions is growing at roughly 28% annually.

Enterprise Intelligent Assistants
The Landscape

General Purpose

This category includes IBM Watson, powerful general tools for general purpose problems. These solutions focus on conversational intent but typically require a lot of specialty services to set up and maintain the experience.

Chat Vendors

Typically focused on “front-end” chat by providing knowledge and deflection capabilities. These vendors don’t typically address live assistance or integration across channels.

Orchestrated / Blended AI

Built for customer experience using technology that is tailored to understanding customers, their journeys and behaviors, and the needs of human agents. This is AI that's specifically focused on CX that enables seamless transition from self-service to assisted= service.

These solutions differentiate on their ability to blend AI with the human touch.

Artificial Intelligence in the Enterprise Point of View - Competitive Review


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