This article explores how artificial intelligence and business analytics are perfectly complementary.

According to one recent study conducted by Sigma Computing, the total amount of data worldwide will balloon to a massive 175 zettabytes by as soon as 2025. By 2023, the “Big Data” industry will grow to an estimated $77 billion in value – outlining just how valuable this “information revolution” that we’re currently living through really is.

But at the same time, data is so much more than just a series of files on a hard drive somewhere in an office. Contained within that data is the actionable insight that people need to make better and more informed decisions all the time. It can help business leaders uncover trends and patterns that otherwise would have gone undiscovered. It’s the key to doing higher quality work for clients, while enabling employees to work “smarter, not harder” at the same time.

It’s also very, very difficult to process… at least without some additional solution at your side.

It’s been estimated that most companies are only able to analyze about 12% of the data they’re generating on a daily basis. This means that the vast majority of it goes unanalyzed – meaning that it’s actually costing organizations money. When you consider the potential lost revenue because businesses have no means to process that data, coupled with the fact that they’re also paying to store that data indefinitely, it’s a major opportunity that few are equipped to fully take advantage of.

Artificial Intelligence and Business Analytics:

In recent years, AI has become more and more prominent in even the smallest enterprises out there – and with good reason. It isn’t just beneficial to combine the analytical toolset you’re already using with artificial intelligence moving forward.

It’s an absolute game-changer – something that is true in a host of unique ways, all of which are worth exploring.

The Power of AI: Bringing Cognitive Insight to Your Business

As stated, one of the key benefits that “big data” has brought to most businesses has to do with the massive volumes of insight that organizations can now tap into. Traditional analytical tools have historically been used to make sense of this data, extracting as much value from it as possible. But as data volumes have exploded, these “standard” tools are having a difficult time keeping up – which is where artificial intelligence enters the equation.

AI-powered cognitive insight uses advanced algorithms to not only detect patterns in business data, but to also help interpret their meaning. Yes, traditional analytics also provides insights – but these AI-powered tools take things one step further.

The end result is that you get a much-needed context surrounding those uncovered trends and patterns – one that is much more data-intensive and detailed than ever before. Because AI models are also trained on some portion of the data set during their initial deployment, they can also get “better” at their job of interpretation over time. This means that their ability to use historical data to make predictions about what the future might hold actually gets more accurate the longer they’re in use.

Regardless of the type of business you’re running, it’s easy to see the value this brings with it. This type of AI-driven cognitive insight could be used to:

• Use past behaviors and even purchase histories to “predict” which products a customer is most likely to buy in the future.
• Quickly uncover suspicious activity with an account to identify issues like credit card fraud in real-time.
• Help insurance adjusters spot insurance claims fraud by detecting when conditions of claims fall outside a predetermined “normal” pattern.
• Process warranty data to proactively identify issues that may lead to poor quality (or even dangerous) products.

But the best part of all is that because these tools are typically used to perform tasks that human beings can’t – such as making sense of seemingly limitless volumes of data – they’re not a threat to employees at all. Instead, they’re a way to support and empower them – freeing up as much of their valuable time as possible so that they can spend less time wading through data and more time acting on it.

Supporting Customer Service by Increasing Engagement

Of course, not all of the insights generated by AI-powered analytics need to be forward-thinking in nature. Yes, artificial intelligence can absolutely use the trends of the past to help decision-makers and leaders accurately predict where things may be headed. But they’re also a great way to focus on the “now” by supporting the most important aspect of an organization of all:

Its customers.

Over the last few years in particular, chatbots in customer service have become increasingly popular in just about every industry. According to one recent study, chatbots can cut operational costs by as much as 30% in some cases. It’s also a support channel that customers have shown that they’re enthusiastic about – to the point where the same source indicated that AI would handle about 85% of all customer interactions via chatbots or through other non-human means by the end of 2021.

Chatbots have always been effective, in part, because they’ve used analytics to better “understand” a customer and what their concern is during an interaction. An enterprise can leverage basic analytics to route a customer to the appropriate human employee to answer a question, for example, or to perform straightforward tasks pertaining to their account (like paying a bill or looking up a balance) without involving a human all.

Now, artificial intelligence can help take this one step further by leveraging concepts like machine learning, natural language processing and more to allow these chatbots to actually get better at their jobs over time. They won’t just “understand” what a customer is trying to do. They will learn WHY they want to do it, thus offering support for a wider range of issues that actually grow over time.

With AI-powered analytics, a chatbot can be used to address even complicated technical support questions in the customer’s natural language, for example. They can make natural recommendations for products and services in a way that increases personalization, engagement, and more.

They can even be helpful internally, forming the basis of a “Knowledge Base” or other types of self-service hub that informs employees about human resources policies, benefits, IT information, and more.

But the key thing that separates these from more “traditional” chatbots is that they’re more than just a “self-help” portal. They allow customers to get more out of every interaction with a brand, and they do it in a way that is available 24 hours a day, seven days a week, 365 days a year.

All told, the amount of data available to businesses is growing at a staggering rate – and that is one trend that shows no signs of slowing anytime in the near future. The businesses that are able to capitalize on this opportunity will be the ones that understand that mere analytics alone are no longer enough to get the job done. It will be analytics combined with artificial intelligence that will pave the way for the next decade of your company’s success and beyond – and that is a very exciting position to be in, no question about it.

Consider how artificial intelligence and business analytics are complementary; it is time for your enterprise to consider your options on upgrading your decision analytics.