The Top 5 Traits Of Applied Conversational AI

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applied conversational ai

Conversational artificial intelligence technology is still in its fledgling stage, but its business applications are mind-blowing. More than any other form of robotics, chatbots, a form of conversational AI have crossed the Uncanny Valley becoming more human-like than ever.

The Uncanny Valley is a mysterious region that nestles between the synthetic and natural in robotics design. Here, machines, which seem poised to supplant humans, become unappealing and unacceptable as per their level of humanness.

The phenomena coined by Masahiro Mori in 1970, hypothesizes that people develop an emotional sense of discomfort and unease when they encounter robots with an extreme mechanical composition. People prefer human likeness in robots. Watch out though; get too close to perfectly human, and the emotional uncanny valley phenomena steps in. Humans perceive such robots as eerie and discomfiting.


Applied Conversational AIs are comfortably human

The debate about Masahiro Mori’s hypothesis is still raging on, and pundits believe that the bridge across this sentimental rift is made of bots with features that are indistinguishable from humans. Conversational AIs from hobbyists and legacy businesses are building this bridge perfectly.

As an illustration, a few years ago, employees had to put down their names on a schedule on a conference room wall when reserving their places for a meeting. The internet era came by and made scheduling much easier with the digital calendar, allowing meeting members to automatically reserve their seats from the comfort of their desks. Collaboration also became easier across all meeting participants.

Today, with conversational AIs like Aira, you do not need to open any application to pre-engage yourself in a meeting. Virtual meeting assistants like Aira will give you a quick wake up and inquire about your availability for a meeting on a particular Thursday afternoon. The AI will search your company’s database for meeting procedures and processes and share them with employees that require the data.

This technology saves meeting preparation time and energy increasing productivity, collaboration, and smoothens the workflow. The meeting companion Aira for instance can intelligently join your online conferencing meetings, write meeting notes, and transcribe the meeting dialogue for future use.

She will highlight all your key points and share these notes with your meeting members. She integrates with customer relationship management platforms via Zapier and can supply the analytics of your meetings for optimization. The best applied conversational AI have traits such as;


1. Truly conversational

Truly Conversational

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Intelligent dialogue is a vital component for any AI and machine-learning platform purposing to stay clear of the Uncanny Valley. Research in dialogue and its patterns is central to the new generation of AI agents. The day’s conversational AI can carry conversations with its users across a wide range of topics.

They can chat with users just as well as people talk to each other and are therefore easy to use an enjoyable as well. Consequently, you can use them for more than song requests or scheduling appointments. They have engaging and coherent responses, can reason, and understand some nuances in conversations.

For this reason, conversational AIs have become crucial to customer experience improvement. Data shows that over 64% of businesses use them to offer personalized customer experience. Close to 70% of chatbot users report positive experiences and half of all millennials that have not encountered conversational AIs, are yearning to use them.

Genuinely conversational AIs are a big hit with this generation of customers because unlike emails, SMS texts, or calls, chatbots can provide instant gratification, a feature that most millennials crave for in customer service. They would rather ask Google or Alexa to read them a manual than asking service personnel for guidance over the phone.

Millennials love chatbots also because they can engage with them in the casual chat tones that they prefer. Consequently, over 83% of consumers say that chatbots are ‘very helpful’ and would make them their primary channels of contacting support.

It is therefore clear that in the future, the customer will seek the services of conversational AIs more than any other customer service process. Some of the notable weaknesses of open domain conversational AIs are their low aptitudes of consistency, empathy, specificity, understanding, and knowledgeability.

Consequently, there is a wide chasm between an intelligent conversation with a bot and a chatbot question answering service. The best AIs are humanlike in conversation understanding user intent and answering questions without ambiguity.

They can use machine-learning technology to learn more about the user and store the information learned for future personalization or context purposes. The best conversational AIs for multinationals are not only deeply conversational but also multi-lingual.


2. Hybrid models

Hybrid models

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Have you ever wondered how chatbots work? Well, here is a compressed low-down on the history of the conversational AI and why the hybrid AI is the ideal conversational AI. The history of chatbot technology is decades old, with the 1950 Turing Test laying the first block laid towards the development of conversational AIs.

More than a decade later, ELIZA by MIT’s Joseph Weizenbaum came by, utilizing natural language processing features for speech capabilities. All that ELIZA had to do was substitute people’s words into scripts, and then feed the scripts back to people to hold a conversation.

One of the most outstanding chatbots of the past is Elbot, whose cheekiness, wit, and sarcasm in 2000 came to the fore via the use of artificial intelligence and natural language processing. Since then, conversational AIs like Mitsiku and IBM Watson has been born. Nonetheless, few of these chatbots have had more popularity than the hybrid Siri, Google Now, Alexa, Cortana, and Facebook Chatbots, that all came into the market in the last decade.

Conversational AIs in the past were either machine learning models or purely linguistic. Purely linguistic bots like ELIZA need human conversations to create speech, responses, and rules. Understanding human language is a complex task for machines because conversations have nuances and subtleties that are difficult to recreate artificially.

This is the reason why hybrid AIs utilizes artificial intelligence and machine as well to mimic human abilities. AI and machine learning conversational bots harness massive amounts of training data curated for their learning. A hybrid AI and linguistic bots use natural language processing, understanding, and generation to deliver not only personalized experiences but also apt pre-scripted responses.

These hybrid chatbots can utilize your back-end systems, data repositories, and third party databases to create responses. These AIs are therefore optimizable and will deliver the perfect personality and response as per your business’s objectives.


3. Cross-platform capability

Cross-platform capabilityCross-platform capability

The best conversational AIs should prioritize your business’s opportunities, goals, strategy, and vision. The AI should demonstrate value and minimize risk by working within your ecosystem. Data shows that by 2024, the conversational AI will redefine the user experience, becoming the new customer touchpoint in the place of the website.

The technology will operate over 50% of the customer touches augmenting it with speech, computer vision, augmented and virtual reality, and computer vision. These bots will infiltrate every aspect of day-to-day and business life. Consequently, these tools have to easily integrate with your existing business framework and any other future devices and technology.

By utilizing AIs that can integrate with your business systems, you will save your business the costs of adopting new systems for AI use. The technology in use should support all its users across devices seamlessly to increase user engagement and satisfaction. Intelligent meeting assistants like Aira for instance, integrate with customer relationship management platforms via Zapier.


4. Analytics and data ownership features

Analytics and data ownership features

Do you know that by 2020, over 70% of all white collars employees will be in constant contact with a conversational AI? In two years, between 75% to 90% of all customer queries will be in the hands of customer service chatbots.  Consequently, different business sectors like banking are utilizing chatbots like Widiba for customer service improvement.

Automotive businesses like Škoda, utilize Laura the AI to enhance the customer journey. The amount of data that these service bots can collect over time is unfathomable. The information that they collect is also invaluable for business.

The data collected by these bots can be analyzed for actionable business insights. Your conversational AI of choice should, therefore, offer data protection, ownership, and analytics as part of the package.


5. Enterprise-level AIs

Enterprise-level AIs

Too often business purchase technology devoid of enterprise features. Most open-source conversational AIs rarely have the needs of business enterprises in mind. As an illustration, you will not find any user role management features or version control in non-enterprise chatbots.

There are no collaboration options or development and integration tools. Like Aira that has a robust system of service upgrades for productivity enhancement, choose AI tools that offer control and other robust business options, plus a proven success model.


Conclusion

Some other very useful traits of the best AI tools include personalization for recommendations and accuracy and control to prevent misuse or abuse of tools. Use conversational AIs also that offer brand differentiation features, to enhance visual brand personality and identity. The best AI tools utilize proven technology and have real-life applications.

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