Top 7 Augmented Intelligence Examples And How to Utilize Them

In this day and age, you’d be hard-pressed to find someone who isn’t in some way familiar with artificial intelligence (AI). It’s everywhere, from our phones to the core structure of multi-billion dollar businesses, providing direction and insight into the world we live in. 

However, there are many branches of AI, and one which you might not be as familiar with is augmented intelligence (AU). 

Perhaps you’ve heard of augmented reality (AR). That’s definitely along the same vein. But augmented intelligence can offer so much more than just AR. So, let’s take a brief dive into some of the best examples available at the moment, and discover how you might be able to use them for yourself.  

What is augmented intelligence?

The general consensus is that, whilst AI is designed to replace certain aspects of human intervention through mechanical automation, AU seeks to enhance human intelligence and what we already know and do. It’s the ideal combination of both worlds, which is why it’s also known as intelligence amplification (IA) or cognitive augmentation. 

Think of it as a partner rather than a director. Augmented reality suggests rather than instructs when it comes to decision making, and can provide new avenues for thought without taking complete control. Both artificial and augmented intelligence already play a big role in our lives.

Artificial intelligence:- Machines replacing human processes- Makes decisions- Complete imitation of human brain- Automated robots performing tasks- Fully automated dronesAugmented intelligence:- Machines aiding human processes- Suggests decisions- Selective imitation of human brain- Collaborative robots working alongside humans- Intelligent drones operated by humans


How does it work?

Augmented intelligence uses machine learning, as any AI system would, to develop a database of information which it can then draw from. This includes big data, which are vast data sets that can be fed into an AI algorithm to be sorted through and learned from. 

A combination of deep learning and natural language processing (NLP) ensures that the augmented systems can respond in a human-like manner. The end result is an improvement to the human decision-making process, since artificial intelligence can examine a wider array of data in a shorter amount of time, and report back with informed, data-driven decision suggestions. 

6 Use case examples of augmented intelligence

Over time, we have developed more ways to make better decisions with artificial assistance. Due to the widespread nature of AI technology, it’s possible to find hundreds of examples of companies and industries that have integrated AI and AU machine intelligence. 

Here are 6 examples of where AU is already being used across the world. 

1. Healthcare

The medical industry is an incredibly stressful place to work, but it’s an essential part of a country’s economy and infrastructure. Unfortunately, the World Health Organization (WHO) has predicted that there will be a shortfall of 10 million healthcare workers by 2030.

AU can assist with this potential issue by helping the current doctors to perform better with greater decision support. For example, AI algorithms that have been trained to detect cancer are already in operation. In some instances, the AI outperformed human doctors in its ability to detect cervical cancer, with an accuracy of 91%.

Two identical black and white pictures of murky shapes sit side-by-side on a computer screen. On the left side, Ismail Baris Turkbey, M.D., a radiologist with 15 years of experience, has outlined an area where the fuzzy shapes represent what he believes is a creeping, growing prostate cancer. On the other side of the screen, an artificial intelligence (AI) computer program has done the same—and the results are nearly identical.The black and white image is an MRI scan from someone with prostate cancer


Moreover, AU can help when it comes to the logistical side of organizing hospitals and healthcare professionals through administrative tasks. This includes:

  • Data analysis of patient records to provide actionable insights (i.e. previous issues, potential susceptibility to infection or complications, or ongoing/genetic health problems like type 1 diabetes which would impact treatment)
  • Hospital information, including average length of patient stay, staffing rotations, or information on facilities which are outdated
  • Information on priority cases, or people who need additional check-ups, help, or support

This will help advise on the decisions that doctors and nurses have to make, which will save time and money for the hospital, and give practitioners more opportunity to save lives rather than rifle through hours of paperwork. Ultimately, it will enhance cognitive performance of those working in the healthcare industry.

2. Social media

If you run ads on social media, it would be useful if they were directed towards your target audience. Well, AU can help with that. By studying user patterns, searches for similar products, or basic information like demographics, your algorithms can send your content to the correct people. This is one of the more mainstream, day-to-day examples of augmented intelligence.

Additionally, augmented intelligence systems can trawl social media looking for mentions of your product. This is fantastic for building up sentiment analysis, and dealing with any emerging issues. Of course, you could just get an intern to stay constantly on your Twitter page, responding to every brief mention. But it’s so much easier to get an AI to do it and send you notifications of when someone tags or mentions you. 

A diagram showing the process from detection of user profiles (implicit, explicit and hybrid) which are then converted into data and run through AI algorithms to create hyper individualized experiences


When it comes to users, AU and AR can combine to make a more interactive, fun experience. Camera filters on Snapchat, Instagram, or Tik Tok are prime examples. You can also play interactive games, or share AR content in real time to friends. 

3. Virtual assistants

Devices such as Alexa and Siri make use of AU, but any business can include augmented digital assistants through the use of chatbots. 

Websites can program a small pop-up bot to appear when a user enters their site. This will give customers the option to ask questions, troubleshoot, or get in contact with a human. Having a human at the end of the line is very important, as a TELUS study found that, whilst 93% of people enjoy self-service, 88% said it was also important to be able to speak with a live agent at any point. 

The development of NLP makes these devices far easier to talk to, making them almost indistinguishable from a real person on the other end of a chat-box. It also means services are available 24/7, and you aren’t relying on customer support to get back to you in the morning. 

4. Retail

 There’s a surprising amount of nuance that goes into retail and marketing. You need to consider things like customer preference and satisfaction in both online and in-store situations, which can be hard to monitor. 

AU integration can help: 

  • Predict trends in the market
  • Monitor customer interactions
  • Keep track of stock and inventory
  • Provide greater information to customers on goods and products in store by scanning an item and receiving product info about it 
  • Allow users to see a product in their home with the addition of AR

This last point is particularly useful, as you’re able to integrate it into almost every level of retail. If someone wanted to buy a new piece of furniture but wasn’t sure how it would look, they could use an augmented reality feature from your online store, which makes use of augmented intelligence, to visualize the product in real-time in their home. The same goes for clothes, hairstyles, glasses, or makeup. 

Someone holds a tablet in their living room. On the screen of the tablet, there is an image of a large, grey sofa. A selection of colours run across the top.


AR scans the environment and figures out which way you’re facing. It uses gyroscopes to keep everything at the same level, then superimposes digital information over the top of the image it receives from your camera. It can evaluate distances and measurements to make sure everything is to-scale, and you won’t end up buying something that is ridiculously too small or too large for your environment. 

5. Manufacturing

Business intelligence is a powerful thing, and something every company wants to have a good supply of so that they can make the best decisions for their workers and their bottom line. 

Within a factory, augmented intelligence can massively speed up the manufacturing process and generate a greater output of products. Machines also deal with high-risk tasks, which can be safely overseen by a human without putting their life in danger. 

AU can also run predictive maintenance. This is where AI can connect to sensors within machinery that provide information about the wear and tear, temperature, or any faults that have developed. When a production line is running for maybe 14 or more hours per day, the potential for risk can be greatly increased without due care and attention. 

Data from embedded sensors (in this case, on a car) is transformed into historical data, which is put into data storage. AI and predictive analytics algorithms transform this data and send it to OEM/Dealer applications and real-time alerts/early warning systems


But information on consumption of goods and the demand for goods can also be assisted by AU. This can help you optimize your supply chain, cut out any middle men, and provide a more streamlined service for your customers. 

Additionally, you don’t want to be churning out products that no one’s buying. So the ability to predict trends in the marketplace and consumer wants can save you a lot of money in the long-run.

6. Finance

The fintech sector is a confusing place. If you’re at all familiar with digital currencies like bitcoin, or have dabbled in blockchain technology, you’ll know there’s a fair amount of room for error. So it’s important to keep up to date on finance news, stocks and bonds levels, and the general health of an economy. 

Banks and finances are really quite fragile, and susceptible to great change in a matter of moments. Just look at what happened recently to the Silicon Valley Bank. AU that utilizes data science can learn from this and help prevent it from happening again. 

When bots can self-learn and gather more data independently, it means they can develop a better understanding of what’s going on without human intervention. Then, when certain red flags begin to crop up as a pattern begins to repeat, AU can advise bankers and investors on the best course of action. It can also identify fraud, keep customers engaged, and identify new markets to break into. 

A bar chart showing 7 factors and their corresponding percentages:Fraud reduction - 77%Reduction of risk - 70%Customer retention - 68%Staying in compliance - 57%Success in existing markets - 37%Success in new markets - 31%Staff retention - 20%


What are the benefits of augmented intelligence?

So, we’ve seen how AU can be used, but what exactly are the benefits from its integration? That’s a fabulous question, so let’s dive into it. 

  • Faster, better decision making. Making decisions can be a major challenge, even when you have a full team behind you. But AU integration makes that process a dozen times faster and more effective. 
  • Less human bias. It’s easy to let bias get in the way when it comes to making important decisions. It sounds odd to say, but the cold, calculated approach that comes from an analysis of patterns and previously exhibited behaviors can be a great benefit if you want to think reasonably and objectively. 
  • Less obtrusive than general AI. There’s a deep-set fear in many people that one day we will all become obsolete within our jobs because of the AI takeover. But AU makes it clear that there are types of AI we can work alongside with, designed to help boost human intelligence rather than replace it. 
  • Provides a wide range of data. It would be borderline impossible for people to scan through every shred of data available in a workplace, especially when you’re looking at enormous institutions like banks or medicine. And yet, AI can trawl through databases, learn from it, and provide accurate, clear results in minutes. What’s better is that the more it learns, the better it gets. Constant feedback from humans can help calibrate AU systems to become smarter and smarter, and deliver top-tier results instantly. 
Human aspects: memory, perception, anticipation, problem solving, decision makingMachine aspects: natural language, computer vision, dialogue conversation, domain data, machine learning


Final thoughts

It’s clear to see how machine learning and natural language processing make artificial intelligence and augmented intelligence revolutionary for many industries and can change your business for the better. And you don’t have to worry about losing job opportunities, either, since AU is there to guide rather than replace.

There are applications for this technology across every conceivable industry. So, whatever your business model is, see how you can incorporate AU initiatives to save yourself time, money, and effort. The benefits speak for themselves.

AI systems aren’t something to be scared of, so jump on that bandwagon and start realizing your greatest potential!

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Meta-title: 7 Augmented Intelligence Examples: Industrial Superpowers

Meta-description: There are many augmented intelligence examples in the 21st century, covering all areas of industry. Let’s look at 7 key examples and how they integrate AU.