10 Real World AI Applications to Transform Global Businesses

AI applications are disrupting major global business models to create better opportunities and improve human capabilities. Global leaders from all diverse industries including Google, Uber, CitiBank, Amazon, and others are proactively investing in artificial intelligence services to optimize operations and enhance customer services.

Let’s explore some of the most significant real-world AI applications that are constantly evolving and improving business processes.

10 Top-notch AI Applications Empowering Global Businesses

  • AI for Optimizing Internal Business Operations

Gone are the days when email service providers would manually sift through email content to filter out spam or fraudulent emails. Now, the task of filtering spam emails from your inbox is efficiently handled by AI. From Gmail to Outlook, email service providers have successfully optimized business mailboxes with automated email management, including –

  1. Spam filters
  2. Smart Email Categorization
  3. Intelligent email routing
  4. Automatic tagging of important emails, and more.

With machine learning algorithms, businesses can deploy smart email assistants to improve employee productivity and efficiency.

  • Recommendation Engines for Boosting Product Marketing

Recommendation Engines for Boosting Product Marketing

Humans lack the ability to understand dynamic customer behavior, needs, and preferences. To serve customers better and enhance their online experience, AI is assisting global businesses such as Netflix, Amazon, and YouTube to match customer interests with the right product or service recommendations.

Recommendation engines enable businesses to deploy machine learning models to gauge patterns in customer queries and searches for-

  1. Recommending digital content including movies, videos, or pins
  2. Suggesting suitable product combinations, and
  3. Customizing offers according to customer demographics.
  • Predictive Analytics for Improving Customer Experience

Predictive analytics is emerging as an effective AI-powered technology that is propelling valuable insights and predictions into business models to improve services and operations. For instance, Google uses location data along with predictive analytics to analyze traffic patterns and movements in a specific area.

Moreover, the healthcare industry is beginning to deploy predictive analytics for identifying diabetes, cancer, and heart diseases in patients. At large manufacturing units, predictive analytics can trigger preemptive actions to maintain and repair complex machinery and equipment.

  • Facial Recognition for Better Socializing

Facial Recognition for Better Socializing

Uploading photos with family and friends is one of the many social activities people enjoy doing across social media platforms. However, little do we realize how easily the system identifies and tags the faces of our friends with a mere mouse hover. This is possible with AI’s facial recognition technology.

 

Facebook and most other social media channels use facial recognition technology powered by machine learning algorithms to enhance user experience. FB’s most recent acquisition of a facial recognition start-up like Face.com and Masquerade determines the social media giant’s future prospects for harnessing more of AI. 

  • Machine Learning for Accelerating Transportation

While cab service applications have made short distance travel an effortless ride, it is important to highlight the main engine behind it- Machine Learning. The data processing, analyzing, and extracting insights abilities of machine learning models enable major cab services such as Uber to-

  1. Determine the price of every ride
  2. Minimize the wait time for a cab
  3. Match riders optimally to minimize detours,
  4. Analyze demand to guide drivers and improve cab availability, and
  5. Compute optimal pickup locations.

All this much more can be done to improve the transportation industry with machine learning techniques.

  • Conversational Agents for Augmenting Sales

Chatbots and conversational interfaces have already become an integral part of business strategies across the globe. In fact, Gartner suggests,

By the year 2020, more than 25% of customer service operations will be using AI-powered chatbot technology or virtual agents.

From healthcare and banking to social media and eCommerce, chatbots are witnessing an exponential demand across industries for-

  1. Enhancing customer experience
  2. Engaging potential customers
  3. Augmenting up-selling and cross-selling efforts
  4. Lead generation
  5. Personalizing services
  6. Delivering services 24*7
  7. Standardizing customer interactions across channels, and
  8. Improving customer satisfaction and loyalty

The integration of chatbots across social media platforms has also gained steam in recent years. For instance, the messaging platform, Slack has proactively encouraged third-party chatbot developers to integrate their virtual assistants into the platform.

  • OCR for Automating Data Extraction and Search

Optical Character Recognition (OCR) is a traditional practice of extracting data from scanned images of documents, written text, and other reading materials. However, the systems were painstakingly inefficient at extracting data from unstructured documents and thus required human intervention.

With algorithmic advancements, machine learning coupled with OCR systems can not only capture and extract valuable information form structured and unstructured documents but also support a plethora of doc formats and sizes. The technology is already relacing human efforts to manually sift through millions of physical documents and extract information. Use cases of AI-powered OCR system include but are not limited to-

  1. Automated data extraction from financial statements, invoices, identity cards, academic material, HR documents, and more.
  2. Creation of editable and searchable digital files of physical docs
  3. Maintenance of digital archives
  4. Translation of docs in several different languages, and
  5. Extraction of valuable data from complex documents

AI-OCR systems are gaining huge momentum across businesses including Cambridge University and Google.

  • AI for Strengthening Financial Services

Financial services constitute an indispensable part of any economic system. Fro banks to lending institutions to insurance agencies, financial services are always at the forefront of adapting technology-led innovations to streamline operations and optimize services.

The advent of artificial intelligence has led banks to take their technological initiative a step ahead in the form of-

  1. Personalized banking chatbots
  2. Credit risk management
  3. Dynamic data analytics
  4. Robust fraud detection with predictive analytics
  5. Appropriate compliance management, and
  6. Offering customized services and solutions to customers.

Among banks, Citibank has proactively encouraged the development of AI-led solutions for its customers. The most recent products include contactless cards, virtual account numbers, and RPA for automating routine banking operations.

  • Computer Vision for Designing Autonomous Vehicles

AI’s computer vision technology is yet another increasingly evolving technology that empowers businesses to teach machines to visualize like humans. The technology is being deeply embedded in the development of autonomous vehicles or driverless cars.

The automobile industry is readily encouraging and investing in computer vision technology that automates-

  1. Object detection
  2. Image recognition
  3. Traffic analysis, and more

Automobile company, BMW is making remarkable strides in testing and building autonomous cars using big data analytics and AI.

  • Deep Video Analytics for Upgrading Agricultural Output

Although agriculture has always been a human-dominated field, AI is showcasing a significant potential to automate critical farming tasks efficiently. Data analytics and insight generation capabilities of AI can assist farmers in-

  1. Yeilding healthier crops
  2. Controlling pests
  3. Monitoring soil and weather conditions
  4. Choosing the right crop according to soil and growing conditions
  5. Automating crucial supply-chain tasks, and others.

Artificial intelligence is propelling the development and deployment of futuristic solutions that are effective for every industrial process.

Author Bio

Sanam Malhotra is a technical writer at Oodles AI that provides enterprise-grade artificial intelligence solutions to global businesses. Fascinated by AI’s transformative potential, Sanam explores how businesses can combine machine learning and deep learning with industrial systems to automate operations and achieve economies of scale.

Tanmay Mondal

I am well motivated Digital Marketer. From last 5 years, I am working on this domain & I always Try to use latest techniques that could help my clients to get maximum leads. Apart from all, I like to share updated news on my blog DigiTechkorner.

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