How Businesses Use AI & Big Data To Increase Revenue

Big data and AI are being used – or at least have the potential to be used – to revolutionize many businesses. Effective use of AI to navigate big data can lead to cost reduction, time savings, error reduction, novel new products/services, and more.

Big data simply refers to the large amount of data that companies can now access every day from a variety of transactions. Artificial intelligence, or AI, can then be used to navigate this data via machine learning algorithms.

In this article, we’ll provide definitions of big data and AI and explore some examples to show how AI and big data can be used to increase revenue and reduce costs.

How Businesses Use AI and Big Data To Increase Revenue

What Is AI?

Answers to “What is AI?” have changed over time. In the 1950s, a generally-accepted definition was that if a task could be performed by a machine that previously required human intelligence, you were observing artificial intelligence. Today, that definition is considered too broad. AI researcher Francois Chollet, from Google, believes AI is defined by a system’s ability to adapt and generalize its knowledge. When a program or machine can apply what it knows to a new situation to solve a problem, that’s AI at work.

Big data and AI are two different yet complementary concepts. Big data is data that is so large, fast, or complex that it’s extremely difficult to make sense of using traditional methods. And one of the non-traditional methods that is best equipped to make sense of big data is artificial intelligence.

Examples of AI

Examples of AI are numerous. Imagine your company sells some sort of web-based app, with hundreds of thousands of users. You have internal and external data about their usage behavior, how they interact with social media sites, their locations, and other factors. As the owner of the app, you seek to understand what other services they might buy and insight into how to get more users to engage with your app.

Human beings can be incredibly adept at data analysis. We are good at generating hypotheses, running tests, looking for patterns, etc. But with massive amounts of data and thousands of factors, artificial intelligence produces insights that humans simply can’t. With AI, a machine learning algorithm could be set up to scour the app-related data, and over time, it will learn how and where to identify patterns and run its own tests on the data – without human intervention. AI can make recommendations to help roll out new features that make people want to use the app more. In addition, it can help identify the types of people who are the best customers and worth marketing to.

AI applications can be split into two camps: narrow and general. Today, what we see all around us is narrow AI. These are systems that have been taught or can learn how to do specific things. Narrow AI applications include Apple’s Siri’s ability to recognize speech, visual recognition systems in industrial robots and self-driving cars, or recommendation engines that suggest what your next Netflix show or product purchase should be.

The uses of big data align closely with AI applications. Elevators across the world are now often equipped with various types of sensors. Large amounts of “big data” is emitted from these sensors. AI algorithms can be used to predict and schedule maintenance, which avoids expensive and frustrating elevator downtime and service interruption. Even AI applications that don’t appear to be related to the “big data” concept usually are, because big data and AI are linked through learning that often occurs behind the scenes.

When you interact with a virtual customer service agent, its ability to interpret and understand your issue is aided by the millions of other interactions that assistant has analyzed and learned from. Companies that can effectively use AI to manage customer interactions are positioned to save millions of dollars.

Future Of AI & Big Data

General AI is different from narrow AI in that it refers to a highly adaptable intellect that can apply insights from one area immediately to vastly different domains. General AI is best understood as a much more human-like artificial intelligence that is flexible. Almost no expert believes this type of intelligence exists today or will in the next several decades. But from there, estimates vary widely. Many AI experts believe general AI will be a part of society in the 2040s or 2050s. Other AI experts see general AI as still centuries away.

Putting aside general AI, the future of narrow AI is almost certainly going to involve impressive and, at times, shocking advances in available AI applications. Narrow AI has been shown to be capable of producing superhuman performance, and in some cases, shockingly superior levels of creativity within a domain. For example, in 2020, one AI system developed the ability to write while another created a unique language to increase the level of cooperation between AI agents in the system.

AI & Big Data Trends

AI and big data trends are likely to include increasingly human-like abilities, from writing to speaking to seeing to design and discovery. In 2020, an entire new type of software was designed by AI, and a Nobel prize-level discovery about how to unpack the protein structure of amino acids was made by AI. In the former case, the idea of a business developing a value-added software application via AI has the potential to deliver revenue increases through new product design at dramatically lower cost. In the latter case, we may be able to cure diseases via AI, saving thousands of lives.

Big data and AI are inextricably linked primarily through machine learning. Practically all recent achievements in AI have stemmed from machine learning. When speaking about AI today, most people are talking about machine learning. Machine learning is where a computer system learns how to perform a task without having been programmed. Key to machine learning capabilities are neural networks. These are mathematical models capable of adjusting internal parameters to change what they output

But to learn, these machine learning models need data – enormous amounts of it. The quality and amount of data is critical for building a system able to accomplish an intended objective. This is the sense in which AI and big data are inextricably linked.

The future of AI and big data will involve what is called deep learning. During deep learning, neural networks are stretched into sprawling systems with numerous layers that are trained using gigantic amounts of data. Deep neural networks have powered the recent step change in computers’ abilities to recognize speech and achieve human-like ability to see. Future advances in AI will be fueled by a combination of deep learning, increasing amounts of data, and constantly expanding computing power.

Conclusion

Big data and AI are inextricably linked. Together, they may have the power to cure disease, prevent catastrophes, increase revenue for businesses, and predict your preferences. It’s an exciting – if uncertain – time to be in business!

 

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Filed Under: business consulting, Consulting skills, Corporate Training