African Artificial Intelligence (AI) Market, 2016

This study provides an analysis of the African Artificial Intelligence (AI) market. The stakeholder scope includes international technology corporations and African start-ups; technology scope includes computer vision, deep learning, machine learning, natural language processing, neural networks, predictive analytics, and robotics; and the end-user scope includes a number of industries such as banking and financial services and insurance (BFSI), healthcare, manufacturing, mining, hospitality and media, amongst others. This study details the key components of an AI ecosystem and explains how AI converges with technologies such as analytics, Internet of Things (IoT), Augmented Reality (AR) and Virtual Reality (VR). It provides a snapshot of global AI trends in terms of key investments, strategy and competition, and also lists the acquisition-led strategies adopted by leading technology corporations including Google, Apple, Microsoft, Intel, Facebook, Salesforce and IBM. This study provides an analysis of the African AI market, including the competitive landscape and the extent of AI market development across key African countries, along with the impact potential and extent of market penetration of various AI technologies and the degree of AI adoption across key industry verticals. It also gives an overview of the future trajectory of AI technologies adoption in Africa. It also offers a snapshot of the AI-powered business applications in Africa; and the key consumers of AI solutions across leading industry verticals. Further, it identifies the key market drivers and restraints that are urging businesses to adopt AI and analyses the key market trends that are prompting businesses in Africa to adopt AI. Moreover, this study discusses the product portfolio and acquisition-driven strategy of emerging international AI leaders like Cisco and IBM in the AI context. It throws light on the start-up landscape in some key African countries, along with the solutions offered, technologies adopted and industries impacted. The study also explains some of the key AI solutions that are addressing regionally relevant issues in the content. It explores key growth opportunities that businesses will look to invest in and the strategic initiatives they will adopt to accelerate their AI journey. It also throws light on the key predictions for the South African AI market, in terms of consumption and technological advancements.
Published: 29 Nov 2017

African Artificial Intelligence (AI) Market, 2016

Chatbots Central to Developing an Intelligently Automated Service Delivery Model

This study provides an analysis of the African Artificial Intelligence (AI) market. The stakeholder scope includes international technology corporations and African start-ups; technology scope includes computer vision, deep learning, machine learning, natural language processing, neural networks, predictive analytics, and robotics; and the end-user scope includes a number of industries such as banking and financial services and insurance (BFSI), healthcare, manufacturing, mining, hospitality and media, amongst others. This study details the key components of an AI ecosystem and explains how AI converges with technologies such as analytics, Internet of Things (IoT), Augmented Reality (AR) and Virtual Reality (VR). It provides a snapshot of global AI trends in terms of key investments, strategy and competition, and also lists the acquisition-led strategies adopted by leading technology corporations including Google, Apple, Microsoft, Intel, Facebook, Salesforce and IBM.

This study provides an analysis of the African AI market, including the competitive landscape and the extent of AI market development across key African countries, along with the impact potential and extent of market penetration of various AI technologies and the degree of AI adoption across key industry verticals. It also gives an overview of the future trajectory of AI technologies adoption in Africa. It also offers a snapshot of the AI-powered business applications in Africa; and the key consumers of AI solutions across leading industry verticals. Further, it identifies the key market drivers and restraints that are urging businesses to adopt AI and analyses the key market trends that are prompting businesses in Africa to adopt AI. Moreover, this study discusses the product portfolio and acquisition-driven strategy of emerging international AI leaders like Cisco and IBM in the AI context. It throws light on the start-up landscape in some key African countries, along with the solutions offered, technologies adopted and industries impacted. The study also explains some of the key AI solutions that are addressing regionally relevant issues in the content. It explores key growth opportunities that businesses will look to invest in and the strategic initiatives they will adopt to accelerate their AI journey. It also throws light on the key predictions for the South African AI market, in terms of consumption and technological advancements.

Key Questions this Study will Answer

  • What are the main components in an AI ecosystem? How does it converge with analytics, Internet of Things (IoT), AR, and VR?
  • What are the key global trends in terms of competition, strategy and investments?
  • What are the key market drivers and restraints for the development of AI market in Africa?
  • How are emerging international leaders like IBM and Cisco advancing in the AI market?
  • Who are the innovative African start-ups disrupting the AI market and what do they do?
  • What are the potential growth opportunities in Africa that businesses can capitalise on to improve performance and stay competitive?
  • How is AI addressing regional issues in Africa and which are the companies developing these solutions?
  • What are the ethical dilemmas concerning AI in Africa?
  • What are the key trends shaping the African AI market?
  • How is the African AI market growing in terms of market development, competition, impact potential and extent of adoption across industries?

Features of this Research

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