Business intelligence visualizes data. With AI, it can interpret and forecast. Source: Shutterstock

Business intelligence visualizes data. With AI, it can interpret and forecast. Source: Shutterstock

Is artificial intelligence the differentiator that BI tools need?

ORGANIZATIONS are increasingly investing in sensors and other connected devices to collect more data — but are they getting the most out of it? If they’re using simple business intelligence (BI) tools, chances are that they’re missing out.

In today’s competitive environment, organizations tend to collect plenty of data about customers, employees, workers, and its overall operations. Much of this data is saved in the company’s servers almost instantaneously, in real-time.

However, businesses that use simple BI tools find that they’re unable to get the most of out of their data. In most cases, data from the myriad sources tend to sit in repositories until they’re queried by users of the BI tool.

In most cases, managers use BI tools to access the same datasets they’ve always accessed, to generate the same reports they’ve always relied on. The only difference now is that they’re able to pull out reports in real-time.

Some slightly advanced BI tools provide data visualization capabilities, allow managers to create dashboards, and make it possible to drill-down into datasets.

Managers, despite having access to more advanced tools, don’t always make use of them because they lack training and more importantly, don’t understand how new datasets can help them better understand customers, the competition, or the market.

The solution? Well, till managers can be trained to understand the nuances of datasets they have access to and see how data from different kinds of sources paint a holistic picture, it might be a good idea to call on artificial intelligence (AI) to analyze the data and spot trends and insights for managers to act on.

AI can augment the capability of managers and help them make sense of data in ways they don’t fully understand themselves.

For example, when an out of the box AI model crunches “typical” meteorological and economic data and factors in historical and real-time data from the company’s own sources, it is able to help supply chain managers better predict the availability of raw materials and demand for goods in different geographies across the world.

Further, when organizations try to customize AI models to suit managers’ needs, they’ll need managers to work with data scientists — which is not only likely to help business managers better understand data but also open their minds up to how different sources of data can be merged to generate interesting insights.

Overall, BI tools are great for most organizations looking to do more with data, however, in order to be able to truly leverage “big data” to create smart insights, organizations need to prepare to work with AI in some shape or form.

In the coming months, as 5G enables the internet of things (IoT), more data is likely to be collected. Organizations that build a culture around data and invest in understanding it intelligently now are likely to win big in the future.