Voice Assistants

A digital assistant that uses voice recognition, speech synthesis, and natural language processing (NLP) to provide a service through a particular application.
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Low Risk
High Disruption Potential
Game Changer

An intelligent virtual assistant (IVA) or intelligent personal assistant (IPA) is a software agent that can perform tasks or services for an individual based on commands or questions. Sometimes the term "chatbot" is used to refer to virtual assistants generally or specifically accessed by online chat. In some cases, online chat programs are exclusively for entertainment purposes. Some virtual assistants are able to interpret human speech and respond via synthesised voices. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal (spoken?) commands. A similar concept, however with differences, lays under the dialogue systems.

As of 2017, the capabilities and usage of virtual assistants are expanding rapidly, with new products entering the market and a strong emphasis on both email and voice user interfaces. Apple and Google have large installed bases of users on smartphones. Microsoft has a large installed base of Windows-based personal computers, smartphones and smart speakers. Amazon has a large install base for smart speakers. Conversica has over 100 million engagements via its email and sms interface Intelligent Virtual Assistants for business.

Voice assistants are featured in mobile devices, laptops, and smart speakers. They're trigged by 'wake words' like "Alexa" or "Ok Google". The device records your question or request and then responds according to either pre-programmed "skills" such as activating a smart light or turning on the television, or by finding and defining information that is available online. The advancement of the voice assistants supported by Artificial Intelligence and Machine learning is rapid.

Trend Metrics

Trend Timeline (Last 4 weeks)

Based on web searches worldwide.

Disruption Breakdown

Success Factors

Cost Efficiency

Based on the cost of production and speciality needed in machinery and job roles.

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Ability to Mass Produce

Based on ease of access to all components and level of personalisation required.

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Speed to Produce

Time taken from manufacturing start point to consumer ready.

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Concept Realisation

Based on proven case studies of the technologies and concepts used.

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Consumer Needs Met

Based on consumer interest, needs and demand.

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Disruption Factors

Ecosystem Potential

Potential to integrate into existing consumer ecosystems (digital or lifestyle) and potential to create new ecosystems.

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Potential to Change Consumer Behavior

Potential to change behavior of the consumer if delivered successfully. Based on creating new interactivity, delivery systems, a unique service or through new knowledge delivered.

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Potential to Change Industry Behavior

Potential to change industry behavior if delivered successfully. Based on creating new technology, leveragable delivery systems or through new knowledge gained.

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Uniqueness of IP

Based on amount of existing consumer products and services leveraging this idea and examples of successful case studies.

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New Knowledge Gained

New technical, development, manufacturing or consumer knowledge gained if delivered successfully.

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Success Potential

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Disruption Potential

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Total Disruption Score

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If delivered successfully

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