Jan

MAKING AI MAINSTREAM



We are experiencing a strong demand for conversational AI solutions. It is coming from every corner of the B2C market. It is growing by the day.

Conversational AI is becoming increasingly popular among the consumer facing business community. It is easy to see why - AI offers sales and customer service scalability and therefore is critical for the long-term success of a business.

Conversational AI solutions such as chatbots, voice bots, and virtual assistants provide much needed speed and efficiency, in an age where the rapid advancement of technology makes them virtually the only sustainable customer service solution.

Bu there is a catch - AI is complicated. Mainstream businesses do not have in house AI expertise. And it is not part of their business model to develop such expertise.

Today’s market offer several good conversational AI solutions, such as IBM Watson or Google DialogFlow. However, getting a business value out of them requires the very AI expertise that mainstream companies do not possess.

So what can be done?

Any AI solution should follow these three steps in order for the mainstream business community to fully benefit from it:

  1. Conversational AI should come as a service,
  2. The service should be available in natural language,
  3. The service should be fully personalized.  
 In the next several posts we will explore how the AI industry, including nmodes, is moving towards achieving these goals.
Interested in reading more? Check out our other blogs:

Pros and cons of automation

Automation drives forward the economy. It allows businesses to scale and service large groups of customers. Automation first appeared in traditional industries, such as cotton production in England in 18th century or car conveyors in the US in early 20th century. The automation replaced physical labor.

With the invention of computers automated systems began to replace intellectual labour such as math calculations. Most of the software applications we use today can be described as automation. Online payments processing, online tickets purchasing, tax returns software, computer games, search engines, and endless other programs are all examples of software automation system.

As a next step we are now aiming at automating human decision making processing and high-level intellectual activities, historically considered to be sole domain of humans.

 

One interesting aspect of automation is lesser quality of service compared to manual service.

This is to be expected. If we gain in quantity we lose in quality.The gain in quantity is what automation is about - it allows to reach out to a large number of customers. Manual product or service can reach out to individuals only. The price we pay for the ability to deliver product or provide service en masse is the drop in quality.

 

Sometimes automation is an obvious choice. This is when the gain, the scalability, hugely outweighs the costs, lower quality. Search engine is a popular successful example. In other cases, the advantage in not so obvious. Online travel booking offers fast service without leaving the comforts of the home, but it does not often deliver the best option, such as finding the cheapest flight, and therefore many people still use ‘manual’ travel agents.

 

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AI unmasked: How a chatbot is different from a voice bot




The main difference is in the linguistic complexity. 

People express themselves differently when they speak compared to when they type. When we speak we use more sentences and we make our sentences longer. 

As a result a voice bot needs to have better AI compared to a chatbot, in order to handle a conversation and deliver the same customer experience. 


If your business model allows it, is better to start with a chatbot and add a voice bot on top of it.

This way you can gradually increase the complexity of your AI without compromising on your customer experience. 

 
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