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AI and BI explained: A roadmap to business efficiency

Written by
Carla Hetherington
Published on
August 31, 2023

Business Intelligence and Artificial Intelligence have been at the forefront of business innovation for quite some time and have revolutionized how we do business, turning raw data into actionable insights. However, while both technologies supply data-driven insights, they differ in several aspects, from how they collect data to their capabilities, limitations, and the benefits they have for businesses. This blog will provide an overview of both AI and BI, how they differ, and how they can be combined to maximize operational efficiency. Let’s get right into it!

What is Artificial Intelligence?

Artificial Intelligence is a branch of computer science that creates technology able to simulate the way humans think and solve problems. These technologies can execute tasks in a human-like manner and even learn from past experiences, modifying their “behavior” accordingly.

Although AI is mainly used to automate manual tasks, it is increasingly being used to make decisions of a more complex nature and with minimal human involvement, fostering its independent learning capabilities. Nevertheless, at least for now, for the most part, businesses are using AI to streamline operational processes and enhance efficiency. Examples include customer segmentation, predictive analytics and reporting, inventory and warehouse management, and AI-generated content for marketing purposes.

Above all, most organizations are focused on AI’s analytical and generative capabilities. The former refers to the ability to process and interpret large amounts of data and translate it to actionable results with tangible business implications. The latter refers to content-creation tools such as natural language processing models like the somewhat infamous Chat-GPT and (visual content creation tool).

What is Business Intelligence?

Business Intelligence refers to the collection and analysis of business data through diverse methods and technologies. The main purpose behind BI is to provide organizations with relevant information based on data so they can make decisions accordingly.

However, it is important to note that while BI transforms bulk data into clear, readable reports, it does not in itself interpret data but is instead concerned with providing a comprehensive representation of otherwise obscure data. In the case of BI, the task of finding significant insights and adjudicating the necessary follow-up actions belongs to the person analyzing the data reports.

So, how are AI and BI different?

Different purpose and scope

  • AI focuses on creating systems that can simulate human intelligence and cognitive functions, enabling them to perform tasks that typically require human intelligence, such as learning from experience, recognizing patterns, making decisions, and solving problems.
  • BI, on the other hand, is primarily concerned with collecting and presenting historical data to help organizations make informed decisions regarding their performance and operations.

Different capabilities and limitations

  • AI systems can make autonomous decisions based on patterns they learn from data, optimizing processes and predicting future outcomes.
  • BI tools, however, provide information for humans to make informed decisions. Their main function is to mine and present historical and current data in a format that is easy to understand, allowing human users to draw conclusions and make decisions. Thus, BI tools do not possess the decision-making abilities that AI tools have.

Different areas and applications

  • AI can be applied to various fields, from autonomous vehicles and medical diagnosis to language translation and gaming. As mentioned earlier, AI tools have the capabilities to not only automate tasks but to provide personalized recommendations and even solve complex problems.
  • The applications of BI, on the other hand, are much more limited. BI is mainly used in business contexts to monitor KPIs, track performance metrics, and support decision-making across departments like marketing, finance, and operations, but it is not really relevant in other fields.

Different analytical capabilities:

  • AI often focuses on predictive and prescriptive analytics, aiming to forecast future outcomes and recommend actions to achieve certain goals.
  • Alternatively, BI focuses on historical and descriptive analytics, providing insights into past and current data, explaining what has happened and why, but not suggesting what actions to take.

That said, despite some overlap and similarities regarding their capabilities, AI and BI should not be seen as competing technologies but rather as complementing ones. Instead of choosing one or the other, businesses should be focused on how to merge the two to maximize their potential and enhance their operational efficiency.

How can you combine AI and BI to maximize their potential?

When AI is combined with BI, both tools can jointly provide highly effective analytical solutions suitable for various business scenarios. By merging the analytical and mining capacities of BI with the predictive abilities of AI, businesses can benefit from more in-depth research and accurate market predictions than they would using the technologies separately.

Furthermore, AI-powered BI tools can help organizations reduce their data analysis time and undertake quicker, more successful data analytics projects, as, albeit effective, individual data analyses done by BI tools are often time-consuming. This frees up analysts to work on more effective tasks and allows the organization’s decision-makers to both react and anticipate market trends and changes based on the collected data.

Based on their individual merits, both AI and BI have great added business value. So, the question remains: Why choose when you can have the best of both worlds?

How can you integrate AI and BI in your business?

Before selecting which AI and BI solutions to integrate into your business, it is imperative to define which objectives or targets you want to reach with the help of these technologies. Instead of simply jumping on the AI/BI wagon, make sure these tools will add value to your operations and will be compatible with your existing systems.

Once you have set specific goals and determined which AI and BI capabilities you want to harness, you can employ the help of an integration platform like Alumio to help you connect your selected AI and BI tools to your existing systems.

The role of integration platforms

Having a reliable integration platform is vital to connect multiple systems and ensure compatibility and optimal data flow between points, which is increasingly important as a business grows. The more data points, the bigger the risk of common integration problems such as data silos, inconsistency, duplications, etc. Alumio ensures business continuity and prevents system crashes by enabling real-time data exchange, processing huge data loads, and more.

An integration platform like Alumio will also ensure your business can always be up to date and embrace the newest tools and updates in the market, thanks to the platform’s flexible and scalable nature. With Alumio, systems can be replaced and modified according to specific business needs, maintaining an uninterrupted data flow and avoiding data loss.

Additionally, Alumio will take care of the security, privacy, and compliance regulations of the tools you use, which is of vital importance when it comes to protecting the information accessible by AI and BI solutions.

Do you want to integrate AI and BI solutions to streamline your operations and boost efficiency? Discover how Alumio can help you connect with any systems you choose. Get in touch with one of our experts and start harnessing the power of AI and BI to innovate your business.

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