By this point, we all know how important data collection and analysis are within our society. Ever since big data tools became easily accessible for businesses of all sizes, we have quickly moved toward a data-driven marketplace that requires organizations to use these tools if they want to maintain a competitive edge.

Predictive analytics is often used to drive business strategy. Instead of relying on experience and instinct alone, business leaders can turn to data to help them manage risk and make good decisions. But predictive analytics can be even more helpful for modern companies when used alongside artificial intelligence (AI). Here’s how.

What is Predictive Analytics? 

Data analytics can help organizations optimize their performance and growth in many different ways. There are several types of analytics, which have different levels of complexity and help to inform business strategies in various ways. For instance, using descriptive analytics merely involves reviewing historical data to get a clear picture of how the company has performed in the past.

Predictive analytics, on the other hand, is used to help predict the organization’s future. While some metrics will change over time, depending on several different factors, past data can be used to inform future trends. The more historical data a company can gather, the more helpful and accurate predictive analytics will be.

While it’s not possible to know for certain what will happen in the future, predictive analytics can make a solid guess, based on advanced probability calculations. Using statistical models, data mining, and algorithms, predictive analytics can help businesses streamline operations, predict future demands, and refine business strategies.

How Can Artificial Intelligence Improve Predictive Analytics? 

Modern data analytics are extremely complex and involve large data sets. Data scientists are in huge demand, simply because it takes specialized and advanced training to successfully leverage the data companies routinely collect on their customers, competitors, and daily operations.

Unfortunately, not all companies have the bandwidth to hire a dedicated analytics team, nor are they large enough to justify one. Even companies that do hire analytics teams might not be able to keep up with the volume of data.

That’s where artificial intelligence can come in. AI simply describes any technology that can take on cognitive tasks that a human might perform, like reading, analyzing, and recognizing. As the name implies, artificial intelligence mimics human intelligence. There are countless applications for AI and helping with predictive analytics has proven to be an ideal use for cognitive technology.

AI allows businesses to process more data and automate some big data tasks. This can help to improve the quality of strategic insights and allow companies to leverage more from their data sets. Artificial intelligence never gets tired and it can sometimes spot patterns or trends that a human might miss.

Examples of how AI Can Improve Predictive Analytics 

Artificial intelligence systems are ideally suited to boosting predictive analytics. They can learn quickly from datasets and extract key insights with very little human intervention. Lots of companies are sitting on valuable data but simply don’t have the available talent to unlock its potential. For some organizations, AI can provide enough strategic information through predictive analytics that a human data expert isn’t required.

The other major benefit of using AI in predictive analytics is speed. Today’s market moves incredibly quickly, and organizations have to be adaptable and agile to compete. Artificial intelligence can help companies get real-time (or near real-time) insights on their customers and the market itself for use in marketing and other organizational applications.

Future of AI & Predictive Analytics 

Artificial intelligence is getting smarter all the time. Predictive analytics has become a key tool for running lean and efficient businesses, regardless of industry. Because these tools, when used together, can spot patterns driven by non-logical human traits and connections, they can be a huge asset in predicting what a company should do to grow and be more successful.

As these systems get more advanced, they will become even more skilled at predicting behavior and suggesting strategies that will drive growth. AI and predictive analytics together could make a huge difference for small businesses, allowing them to scale by sifting through data, driving innovation, and uncovering the truth about what their customers want.