In one way or another, digital transformation companies already know the power of business intelligence platforms and methods. But there is little discussion in the corporate world on the alliance between data analysis and Artificial Intelligence (AI).

This scenario is changing, as these two pillars of technological innovation have increasingly merged to elevate the analytical power of business to an even greater level — that’s what experts say around the world.

In this article, we propose to demystify this theme. Keep reading to understand why joining these two technological concepts can help reinvent your business management.

What is and how does Business Intelligence work?

According to Gartner’s IT glossary, the term Businbusiss Intelligence (BI) refers to technologies, applications, and practices for collecting, integrating, analyzing, and presenting business information. BI’s goal is to support business decision-making.

Essentially, Business Intelligence systems support decision-making in data-driven management, used interchangeably with reporting and query tools and executive information systems.

In other words, Business Intelligence platforms provide historical, current, and predictive views on business operations, most often using information that has been gathered at a data warehouse or at external sources. Software elements support reporting, interactive pivot table analysis, and statistical data mining.

Thus, it is correct to say that companies that have a good Business Intelligence strategy (technology + methods of management aimed at competitive intelligence) obtain the following advantages:

  • more strategic and less “intuitive” management, since projects and action plans are driven by the data collected, processed, and analyzed in real time;
  • competitive efficiency, with quick responses to executive inquiries in the most varied areas (commercial, marketing, operations, etc.);
  • more in-depth knowledge of customers, business partners, and competitors;
  • quick and accurate identification of risks, threats, business opportunities, etc.

What is Artificial Intelligence?

The concept of Artificial Intelligence is a bit broad and sometimes difficult to explain. It involves the learning of machines and other programmable resources that make equipment, operating systems, and other IT infrastructure work by simulating and enhancing human capabilities.

In general, it is important to know that Artificial Intelligence enables machines to learn from experience, adjust to new entries, and perform tasks as if they were people — even though they can work more accurately, faster, and more effectively.

Most of the AI ​​examples we hear about today — from computers that play chess to stand-alone cars — depend heavily on deep learning and the processing of natural language. Using these technologies, machines can be trained to perform specific tasks, processing large amounts of data, and recognizing patterns.

Let’s take a practical example: the Deloitte consultancy recently did a very interesting experiment in the Netherlands. It has promoted a kind of “battle” between three tax management technicians and a “bot” — a computer programmed to simulate human actions and operate systems in an automated way.

What Deloitte wanted to know is if the professionals would be more agile than the machine to generate the largest possible number of invoices. To do this, they had to perform about forty manual processing tasks, reconciling data from different sources to create and send invoices.

The result? In one hour, the robot produced 192 invoices and the three specialists only performed 129, which demonstrated the productive power of Artificial Intelligence in a very practical case.

In general, we can say that, applied to business, Artificial Intelligence can provide the following benefits:

  • automate repetitive tasks to boost productivity and reduce errors;
  • add intelligence to existing products and services and pave the way for the creation of new offers;
  • analyze deeper data using neural networks that have many hidden layers, for example, in financial transactions;
  • exploiting data in a more profitable way by making them intellectual property through self-learning algorithms, for example in an industrial plant.

How are Business Intelligence and Artificial Intelligence related?

To think about the alignment of Business Intelligence and Artificial Intelligence solutions and methods, let’s use a fictitious example. Imagine that your business strategy is to increase sales through online trading, but that competition in the area is already tight.

Through machine learning, a categorization algorithm allows software applications to become more accurate in predicting results without being explicitly programmed, enhancing the consumer experience.

Using Artificial Intelligence applications, you can, for example, make accurate recommendations when a potential customer starts typing in the virtual shop search field.

At the same time, data analysis integrated with that application can provide insights to the digital marketing team, which will produce more assertive actions to reach the target audience in the virtual environment and facilitate the measurement of results.

By pursuing this same goal, it is also perfectly feasible to automate merchandising based on a predictive understanding of consumers. Combining data analysis and IA, the e-commerce platform can determine which items can appeal to a specific customer profile from online surveys and provide options for selling complementary products, for example.

In addition to the practical actions described so far, the combination of insight generation and Artificial Intelligence can also empower predictive tasks, such as determining what customers want based on the information they provide. All this in an automated way, with the minimum of human intervention.

As you have seen, there are many possibilities for combining BI and IA solutions in the corporate world. The biggest challenge for organizations is to structure strategies and decide which equipment and tools will be applied to business objectives, and this can be done with the right help. Therefore, the most important is to have the assistance of specialized consultants to assist you in the design of your solution.

What do you think of the idea of ​​aligning Artificial Intelligence and Business Intelligence? Can you envision a project like this in your company? To receive more articles like this directly in your email, subscribe to our newsletter right now!