Mapping Up and Coming Artificial Intelligence Trends in 2020

Sanam Malhotra | 3rd December 2019

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.

Also Read- Powering Chatbots with IBM Watson to Impact Global Businesses

 

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

Also Read- Strengthening Artificial Intelligence with Raspberry Pi for Global Businesses

 

Substantial Machine Learning Applications with TensorFlow

For many organizations, machine learning (ML) is still limited to high-end research and in-depth analysis. However, the launch of open-source libraries such as OpenCV and TensorFlow has accelerated the development of effective ML applications for businesses worldwide.

The trajectory of TensorFlow-based applications is witnessing an upward graph since last year. Its agile architecture enables developers to practice ML models using their most preferred programming languages like Python, Javascript, and Swift. In addition, businesses are proactively exploring TensorFlow’s rich database to augment their automation efforts.

Here are a few interactive ML applications and business use cases built on TensorFlow-

a) Image recognition models that can store and analyze millions of images to identify objects, human faces, and detect anomalies. Convolutional neural networks constitute the underlying algorithms of image recognition models that extract valuable insights from complex images.

b) Speech-to-text translation models that enable businesses to interact with distance customers seamlessly. Speech recognition is also a powerful building block for business chatbots that enhance customer engagement efficiently.

speech recognition tensorflow

Source- Github

Also read- Deploying TensorFlow and Keras for Deep Learning Models

 

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. 

About Author

Sanam Malhotra

Sanam is a technical writer at Oodles who is currently covering Artificial Intelligence and its underlying disruptive technologies. Fascinated by the transformative potential of AI, Sanam explores how global businesses can harness AI-powered growth. Her writings aim at contributing the multidimensional values of AI, IoT, and machine learning to the digital landscape.

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