Examples Of Augmented Intelligence In Today’s Workplaces Shaping the Business as Usual
Last updated: January 11, 2024 Read in fullscreen view
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And while some AI technology is intended to operate autonomously, one of the most useful types of AI — augmented intelligence (also known as Intelligence Augmention or Intelligence Amplification, or IA) — uses machine learning and predictive analytics of data sets not to replace human intelligence, but to enhance it.
Augmented intelligence takes many different forms, but here are some common examples for workplaces that use documents and data (which is just about every business that’s thriving today!).
Augmented intelligence examples include virtual assistants, such as Siri, Alexa, and Google Home. Augmented intelligence can predict patterns and aid in decision-making for customers. For instance, social media often predicts user patterns to determine which ads to show certain people that are most likely to entice them. In the same way, these technologies can suggest new accounts for sales teams, perform regulation and risk analytic tasks in banks, and help to diagnose and offer treatment solutions in hospitals. Augmented intelligence can take historical data and then make a prediction, but the actual decision is up to the human user. An example is streaming services that can offer you show or movie suggestions based on your past history, but it is up to you to decide whether or not to go with the suggested option.
Making collecting and analyzing data easier
With so much data available in today’s time, it becomes difficult for organizations to collect, manage, and analyze the data effectively. If you try to do everything manually, it results in exertion and loss of valuable time.
However, now with the help of augmented intelligence, you can collect the information effectively. Not only that, but you can even go a step further and analyze the data in a better way.
One prime example is when a customer calls a call centre executive to resolve their concern, they normally have to go through a pre-recorded message to dial certain numbers. These numbers reduce the steps that the customer care representative could have spent while speaking with the customer. This is what augmented intelligence does in the best possible manner. The best part is, it tries to improvise based on the data accumulated. So, the next time a customer faces the same issue, the augmented intelligence tool provides the answer before transferring the call to the human agent. Isn’t that ingenious?
Intelligent Document Processing (IDP)
Bills of lading, letters of credit, purchase orders, service requests: Businesses run on documents. Intelligent Document Processing takes the relevant data from these documents, routes it through digital systems, and processes the content to achieve business goals. That’s only possible with AI like Computer Vision (CV), Machine Learning (ML), and Natural Language Processing (NLP). (You may remember IDP from previous blog posts; learn more about it here.)
But in many cases, the AI behind IDP is augmented intelligence, too—wherever it helps a human complete some task or process. An IDP platform might deliver documents to managers for authorization. It might condense the data into reports that bring insight to human decision-makers (more on that in number 6 on this list). Or it might give human experts the chance to train the system for continually improving performance—which brings us to our next item.
Document Maker-Checkers
Remember that both human and machine intelligence get better through augmented intelligence systems. A document maker-checker in an IDP platform allows humans to guide the ML process, improving AI for full-circle augmented intelligence.
The Nividous maker-checker presents users with a split-screen interface. On one side is the original document. On the other are the results of the AI’s data extraction. Users can annotate data points and correct any mistakes—and the AI learns from every correction, getting better over time. In other words, artificial intelligence gets augmented; that’s what we mean by augmented AI, best understood as a subset of general augmented intelligence.
AI Chatbots And Intelligent Voice Assistants (IVA)
Natural language processing AI creates opportunities to automate customer service itself. Your chatbot may use NLP to understand a wide variety of phrasings, responding with the most helpful answer in the database. It might even use Natural Language Generation (NLG) to come up with an original response. The same is true for voicebots like IVAs, which free us from the frustrating touch-tone menus of yesterday’s automated call centers.
At their best, these conversational AI systems are augmented intelligence through and through. They may send human agents transcripts of conversations thus far, preparing them to be helpful prior to escalating the call. They may pre-authorize callers, app users, and site visitors before bringing in the human agent. They may identify the right department to handle a specific request. All these things help human customer service agents work smarter, faster, and better—and they’re all examples of augmented intelligence at work.
AI influences your purchase decisions and helps make data-informed decisions
Since there is a lot of data available, as a customer, you have all the possible options to make the right purchase decisions based on testimonials and ratings reflected on the company’s website.
This way, you can make informed purchasing decisions that are data conscious. One way augmented intelligence has made a huge impact in our lives is in helping us pick up the right product at the right time.
This purchasing decision based on past data can come in handy when you make important purchases that can have a critical role in your future success.
Predictive Analytics
Machine learning models are particularly good at spotting patterns in large data sets. Predictive analytics platforms use this capability to project likely future outcomes. Increasingly, businesses are using this AI for everything from spotting credit card fraud to calculating insurance risk.
The AI predicts risk and opportunity, allowing human decision-makers to evaluate the best course of action. It’s an example of turning data into insight—and of human-AI collaboration for stronger business choices. In other words, it is augmented intelligence.
Attended Smart Robotic Process Automation (RPA) Bots
Robotic Process Automation (RPA) uses special software, usually called bots, to operate applications through user interfaces. These bots automate routine data-handling tasks, freeing human workers to focus on higher-value work. Some bots operate automatically; these are unattended RPA bots. Others only launch operations when triggered; these are attended RPA bots. And either type of RPA bot may use AI technology to handle more complex tasks.
An RPA bot that’s both attended and enhanced with AI is a form of augmented intelligence. For example, an insurance agent onboarding a new customer may trigger an attended RPA bot to collect data from customer documents, using intelligent CV technology. The bot may then verify the details, reducing errors and detecting potential fraud; together, the human agent and the smart RPA bot create a better customer experience and stronger outcomes for the business at once.
Automated Reporting
We’ve discussed NLP and NLG, two powerful language-based AI technologies. Along with the data extraction available with IDP processes, this AI can auto-generate reports to bring mission-critical information to decision-makers when they need it most. Like predictive analytics, automated reporting is a business insight solution that helps the people in charge of enterprises make smarter choices faster.
That business insight may be the key benefit of augmented intelligence—but this technology can also transform business operations by automating core processes from beginning to end, with full participation from both people and AI components.
Final Thoughts
Augmented intelligence is not there to replace humans. Rather it is there to assist them in getting better at specific tasks.
Augmented intelligence is meant to increase the intelligence of both parties: the computer and the human user. When used properly in tandem, man and machine can be smarter together. AI and augmented intelligence can open the door for more creativity and new innovations by assisting and enhancing human capabilities.
When humans and augmented intelligence platforms work in unison, it results in huge success.