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Growth Expectations for Intelligent Assistant Systems

In other to predict the future based on growth expectations, it is okay to take a step backward and look at how things have been. Things in the future might not necessarily look as they were in the past. However, looking at the past helps to come up with trends that can be used to plot different future scenarios. This is what I intend to do with this content

To analyse the growth expectations, let's first take a look at the top two global market in the Artificial Intelligence (AI) Industry. These are China and the US. As of June 31, 2017, there was a total of 2,542 AI companies worldwide. The US remains the leader of the global AI industry development while China is following innovatively.

In China, startups in the AI industry are classified as follows;

1. Robots and Drones
2. Natural Language Processing
3. Computer Image/Graphics
4. Affective Computing - a combination of psychology, semantics, vision and environmental sensing.

In the US, AI-based machines are classified as follows

1. Neurocomputers
2. Expert Systems
3. Autonomous Robots
4. Smart Embedded Systems
5. Intelligent Assistance Systems

In 2014, Siemens in conjunction with BCC Research (a market research company that specializes in technology markets) provided facts and forecasts about the growth of AI-based machines. For AI-based machines, the US market generated 5.3 billion US dollars in 2013 which is also predicted to generate a sale of 15.3 billion US dollars in 2019. This is based on the compound annual growth rate (CAGR) of 19.9% by the year 2024. In the research study, one of the conclusions was that the intelligent assistant systems are predicted to have the highest aggregate 5-year growth rate.

However, at this stage of growth for the intelligent assistant systems, it is difficult to specify a concrete or actual and predicted growth rate in terms of sales for the intelligent assistance systems. So, it is safe research-wise to rely on the number of publications and patent applications and come up with growth expectations for intelligent assistant systems.

Publications on Intelligent Assistant Systems for Growth Expectations

The number of published publications were searched on the Web of Science Core Collections. In the search results for “Artificial Intelligence” under the “Computer Science Artificial Intelligence” category, 9,340 publications were presented. However, doing the same search method for “Virtual Assistant”, 83 publications were presented. With a focus on the past 5 years (i.e. 2013 to 2017), 46 publications on “virtual assistant” were discovered. The 46 publications are approximately 55% of all the publications published between 1998 and 2017. This shows people are much more interested in the topic in the past 5 years.

 
Publications on Intelligent Assistant Systems

 

Patent Applications on Intelligent Assistant Systems for Growth Expectations

The number of patent applications were searched on the Espacenet. In the search results for “Artificial Intelligence”, 1,758 patent applications were presented. However, doing the same search method for “Virtual Assistant”, 77 patent applications were presented. With a focus on the past 5 years (i.e. 2013 to 2017), 51 patent applications on “virtual assistant” were discovered. The 51 publications are approximately 66% of all the publications published between 1996 and 2017. This shows people are much more interested in the topic in the past 5 years.

 
Patent Applications on Intelligent Assistant Systems

 
By looking at the past, we see an approximately linear growth for the intelligent assistance systems. This can be used to predict the growth expectations. Four different scenarios can be predicted - exponential growth, continued linear growth, linear decrease or exponential decrease. However, I think the market for intelligent assistant systems will grow exponentially. This conclusion can be verified using different diffusion or growth models such as Product Life Cycle, Diffusion of Innovation, Bass Model, S-curve, Verhulst Model, or SCOT model. However, these models require sufficient data about the intelligent assistant systems.

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