Conversational AI Trends 2020: Roadmap and Strategy

Conversational AI Trends 2020: Roadmap and Strategy

Artificial intelligence (AI) is becoming more human with cognitive conversational abilities. What commenced as online chatbots, turned into essential AI-powered assistants for businesses, households, and users worldwide. Conversational AI and...

Artificial intelligence (AI) is becoming more human with cognitive conversational abilities. What commenced as online chatbots, turned into essential AI-powered assistants for businesses, households, and users worldwide. Conversational AI and chatbot development services are all set to become more agile with expected market size of USD 15.7 billion by 2024. From domain-specific solutions to intelligent retail chatbots, check out the most exciting Conversational AI trends for the new year 2020.

  1. Extensively Narrow or Domain-specific Results
    For a long time, providers of AI development services used a rule-based or decision tree approach to run online chatbots. Although rule-based chatbots provide accurate customer responses, their intelligence is limited to pre-defined FAQs and common user queries.

The advent of data-driven machine learning intelligence is empowering chatbots and conversational AI applications to facilitate domain-specific user interactions. The new year will witness notable progress in the development of domain-specific conversational AI applications with the following business benefits-

a) Self-learning Conversational AI
Unlike decision-tree bots, conversational AI is trained using rich consumer data to augment a system’s self-learning capabilities. Self-learning chatbots will enable businesses to train models with consumer data, product details, social media interactions, and other valuable troves of data.

b) Domain-specific solutions
Conversational AI is predicted to upskill its algorithms in 2020 for a deeper understanding of customers’ intent and context. It leads users to fulfill highly specific requests such as booking a restaurant table, a haircut appointment, a car service, and whatnot.

  1. Rise in Conversational AI Marketing
    Building an emotional and long-lasting connection with the target audience is the core essence of any marketing strategy. However, the ever-increasing shift in the structure, location, and size of end-users is challenging businesses to evolve their marketing strategies.

AI development services hold the potential to transform the global marketing landscape with cognitive and conversational applications. The year 2020 is projected to experience a paradigm shift in chatbot applications from customer support to sales and marketing efforts.

Here’s how AI-powered conversational AI trends will boost marketing strategies in 2020-

a) Capturing potential leads and automating follow-ups and lead scoring efforts. Chatbots may even completely alternate the need for lengthy lead generation forms with engaging dialogue-based lead conversations.

b) Responding to client queries in real-time and schedule sales meetings automatically

c) Making personalized recommendations across social media channels.

The AI team at Oodles build conversational chatbots integrated with Fb Messenger to augment social media marketing efforts of multiple industry businesses.

  1. Conversational AI Trends for everyday Retail Customers
    While chatbots are showing significant results for eCommerce businesses, conversational AI is yet to become a mainstream adoption for the retail sector. IoT technology has already entered brick and mortar stores through touch-screen devices, automated checkouts, RFID-enabled shelves, and more. AI applications are the next step forward to use IoT data for enhanced customer services and experience.

In 2020, the retail customers are set to experience interactive shopping experience with the following innovative conversation AI trends-

a) Finding the right product
Navigation in retail stores is an omnipresent challenge for customers. AI-powered chatbots can assist customers in locating their products and guide through the floor plan.

b) Resolving customer queries
Multiple surveys have confirmed that the millennial generation is more likely to interact with a chatbot for customer support. Customer services through chatbots deliver a less administrative and more engaging experience.

Exploring the potential of Conversational AI with Oodles
Global industries are evolving their conversational practices with artificial intelligence technologies. At Oodles, we harness IoT and AI capabilities to build highly intelligent and intuitive experiences for businesses and their customers. With hands-on experience in Natural Language Processing algorithms, we empower eCommerce, healthcare, banking, and other businesses to augment their customer outreach efforts.

Our NLP services extend to the extraction of customer behavior and preferences with the application of sentiment analytics technology across portals and social media channels. We deploy various tools and bot frameworks such as IBM Watson, Dialogflow, Azure, and other platforms to match the ever-expanding customer requirements.

Talk to our AI development team to know more about our artificial intelligence services

Top 10 Technologies to Learn in 2020 | Trending Technologies 2020

Top 10 Technologies to Learn in 2020 | Trending Technologies 2020

Intellipaat Online Training: https://intellipaat.com/ In this Intellipaat's top 10 technologies to learn in 2020 video, you will learn all the trending techn...

In this Intellipaat's top 10 technologies to learn in 2020 video, you will learn all the trending technologies in the market in 2020. The end goal of this video is to educate you about the latest technologies to learn and all the top 10 trending technologies you can watch for in order to make a fantastic career in IT technologies in 2020.

Artificial Intelligence Trends in 2020

Artificial Intelligence Trends in 2020

As we progress towards the new year, artificial intelligence continues to propel enterprise goals and objectives. With high computational powers and machine learning advancements, business applications of AI are opening new and better...

As we progress towards the new year, artificial intelligence continues to propel enterprise goals and objectives. With high computational powers and machine learning advancements, business applications of AI are opening new and better opportunities across vectors. For this new year, providers of AI development services are aiming to improve business services and strategies with disruptive AI technologies. Read on to find out what all artificial intelligence trends in 2020 will impact your organization’s digital transformation journey.

Chatbots Will Master Human Interactions

2019 witnessed a ubiquitous influence of chatbots across business portals, social media platforms, and dedicated mobile applications. However, AI is still struggling to abate the lackluster performance of chatbots topped with their malfunctioning in response to complex queries.

With constant algorithmic advancements and models wired with self-learning algorithms, the year 2020 would initiate natural conversations with chatbots. Businesses will be able to capitalize on the bot’s human-like interactions by gaining maximum customer loyalty across borders and timezones.

Following are the key transformations awaiting AI-powered chatbot development services in 2020-

a) Voice-based customer interactions will be the most prevalent AI-powered support function throughout the next year. With better natural language processing (NLP) capabilities, virtual assistants will benefit multiple industries with a consistent brand voice and smarter customer engagement.

b) Sentiment analysis will be yet another milestone for chatbots to achieve in 2020. Chatbots’ underlying NLP techniques will enable businesses to trace their target audience’s needs and interests to provide user-centric products and services.

c) Also, social media platforms will give a major boost to businesses with direct purchasing windows available in the form of chatbots. Social media bots not only augment upselling efforts by making personalized offers but also addresses customer grievances efficiently.

shopping bot artificial intelligence

A functional Fb Messenger Shopping bot built by Oodles AI. With experiential knowledge in conversational AI, Oodles’ AI team develops text and voice-based chatbots to handle contextual interactions across channels.

AI’s black box decoded with Explainable AI
To our dismay, artificial intelligence has caused businesses irrecoverable losses in the past due to wrong predictions and impersonal interactions. Critical industries such as healthcare, insurance, and banking are particularly at risk of making uninformed decisions based on AI’s unreasonable outputs.

To make AI’s black box transparent, ‘Explainable AI’ or ‘XAI’ is an emerging technology that justifies AI’s specific decisions with understandable methodology. XAI is a significant development towards the ethical use of AI in businesses along with the following advantages-

a) Improved decision-making based on AI’ deep neural networks.

b) Simplicity and ease of implementation even with complex datasets

c) Better identification of business errors and removal of data biases

d) Strengthened cybersecurity with full control over AI performance

Capitalizing on Artificial Intelligence Trends in 2020 with Oodles AI
We, at Oodles AI, are a team of AI enthusiasts and experts who are exploring innovative business applications of artificial intelligence and its underlying technologies. With hands-on experience in developing industry-specific machine learning models, we deploy complex neural networks and frameworks to fulfill your automation requirements. Our AI capabilities involve NLP services, computer vision technologies, recommendation engines, predictive analytics, and custom chatbot development services.

Talk to our AI team to know more about our artificial intelligence services.

AI-powered Conversational Chatbot Development Using Wit.ai

AI-powered Conversational Chatbot Development Using Wit.ai

Artificial intelligence (AI) is the driving force behind emerging conversational technologies. Businesses are beginning to strengthen their customer relations with conversational AI technologies by deploying various chatbot development frameworks....

Artificial intelligence (AI) is the driving force behind emerging conversational technologies. Businesses are beginning to strengthen their customer relations with conversational AI technologies by deploying various chatbot development frameworks. One such bot framework, Wit.ai is gaining momentum with its machine learning algorithms to empower chatbots and virtual assistants across applications and IoT devices. As an emerging chatbot development company, we at Oodles AI are exploring new business opportunities for conversational chatbot development using Wit.ai.

In this article, we explore how artificial intelligence services can be combined with Wit.ai to develop business-oriented applications.

How Machine Learning is Embedded in Wit.ai
The core functionality of Wit.ai is based on two major ML technologies, i.e. Natural Language Processing (NLP) and Natural Language Understanding (NLU). While NLP enabled Wit.ai to break customer queries into actionable ‘entities’, NLU extracted meaning out of these entities. However, in April 2016, Wit.ai released an entirely new mechanism called Bit Engine, for building NLP-based chatbots or virtual agents.

The new setup of Wit.ai facilitates the development of cognitive chatbots based on the concept of ‘Stories’. Stories provide the essential conversational flow to human-chatbot interactions using ‘Actions’. Though much of this new paradigm shift in Wit.ai works similar to Watson’s intent and entity mechanism. Application integration of Wit.ai is made simpler with the support of popular programming languages such as Python, Ruby, Go, and Node.js.

For now, let’s look at the four main pillars that keep a chatbot interaction going in Wit.ai today-

  1. User says
    The first step is to identify and input the exact query or command you expect your user to raise.

“I need a 30-minute appointment for a haircut tomorrow at 7 pm”

It prompts Wit.ai to extract the following “Entities” form the text-

Intent Haircut appointment
wit/duration 30 minutes
wit/datetime 01/24/2020, 7:00 PM
The Understanding tab in Wit.ai enables us to add the variants of this text or input in order to train the chatbot with human-like language.

  1. Bot Sends
    This section defines the message that a chatbot should send to the user. It may be an answer for a query or a prompt to fetch further information.

  2. Jump
    As a chatbot developer, it is important to maintain the flow of the conversation. The Jump section enables developers to jump at any point in the user-chatbot conversation and create bookmarks for important exit points.

  3. Bot executes
    It is the final control wherein Wit.ai embeds ‘Action’ into the chatbot interface. Here, developers can instruct the bot to execute certain actions wherever required. However, this action runs parallel to the code that is built in the bot’s backend to fulfill the user’s command.

If we take the above haircut example forward, the bot executes section would divide the input between ‘context’ and ‘entities’. Here, the entities mapped in the first section, ‘User says’ will support the bot to provide specific actions.

dhairsalon (context, entities)

The context object comprises of keys and values that can be used to instruct Wit when action functions add location, crowd, and budget keys. It leads Wit to demonstrate the action and complete user requests accurately and efficiently.

Different Conversational AI Applications Using Wit.ai
Virtual Assistants
The NLP engine inside Wit.ai provides for yet another virtual assistant framework to integrate with Google Home, Alexa, and other voice-controlled IoT devices. Businesses are beginning to expand their customer services using the voice recognition capabilities of Wit.ai.

For instance, real estate businesses are executing conversational chatbot development using Wit.ai to assist their potential customers in locating their ideal house or property. Wit.ai is able to analyze and respond to various customer preferences and needs with valuable information. Moreover, the location access feature in virtual assistants like Google Home can train Wit.ai to find nearby restaurants, hospitals, etc. with ease.

Voice-controlled wearable gadgets
Building voice interfaces for wearable gadgets just got easier with Wit.ai. The exhaustive set of HTTP APIs in Wit.ai simplifies the development of voice-controlled wearable gadgets. The applications of wearable gadgets are most commonly used by healthcare service providers. The NLU algorithms inside Wit.ai enables the smart IoT devices to monitor user health, extract insights, and provide suggestions to improve lifestyle. Some businesses are also deploying Wit.ai over the cloud to automate appointment bookings with health assistants.

Deploying Conversational AI using Wit.ai with Oodles
Conversational AI is one of the most potential developments expected to reach new heights in the new year 2020. At Oodles, we are constantly exploring new technologies to harness the capabilities of IoT devices and artificial intelligence to build intuitive conversational interfaces. Our AI team has experiential knowledge in deploying Natural Language Processing algorithms to empower eCommerce, insurance, and other businesses for optimum customer experience.

Our capabilities with Wit.ai extend to an in-depth analysis of specific user intents and mapping them to build domain-specific chatbots or virtual assistants. We deploy conversational chatbot development using Wit.ai both on-premise or in the cloud by using services like AWS, Google Cloud, and more.

Reach out to our AI development team to explore our diverse artificial intelligence service.