Though there is a lot of excitement around smart, data-driven decision-making. Business intelligence and artificial intelligence are often considered synonymous. 

There is a long-standing debate between business intelligence artificial intelligence. While both assist businesses in making critical decisions, their differences are crucial. In AI, intelligence refers to the intelligence of a computer, while in BI, it refers to the ability to make intelligent decisions. 

By integrating dotnetreport builder with your business intelligence artificial intelligence platform, you will be able to design dashboards that meet the needs of your analytics team.

Take a closer look at how business intelligence artificial intelligence differ and how they can be used together to drive modern business enablement.

Distinguishing the Two

  1. Artificial Intelligence

In the field of computer science, artificial intelligence refers to the creation of machines that are programmed to think and solve problems in a way similar to human thinking. 

Artificial intelligence involves advanced algorithms and theories of computer science. It is extensively used in robotics and games. It can perform tasks that are similar to human beings and learn from past experiences. 

  1. Business Intelligence 

Data is collected and presented in a coherent, clear, and comprehensible way through business intelligence, Transforming murky data into a clear picture for businesses. 

Business intelligence converts bulk data into readable reports. BI does not interpret data; rather, it is presented in an understandable way.

It is necessary to combine data mining, warehousing, and various tools to extract more information based on data.

As an example, BI can generate a neat overview of sales leads, but it cannot predict which leads should be contacted first in order to maximize sales.

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AI and BI  Have Distinct Goals

business intelligence
  1. The Main Goals of BI

By using BI, businesses can improve the quality of their data and the consistency with which they collect it by simplifying the process of collecting, reporting, and analyzing it.

The purpose of Business Intelligence is not to tell you what to do; it is to tell you what was done and what is happening.

As a result, BI tools can turn reams of noisy data into a coherent picture but not prescribe how to use that data.

Companies such as Microsoft, Oracle, and Tableau have developed business intelligence tools for HR, sales, and marketing, among other functions. Businesses can organize data and make traditionally difficult decisions much easier when they monitor everything they do daily – and use that data to create spreadsheets, performance metrics, dashboards, charts, and graphs. Over the past three years, BI solutions have grown by nearly 50 percent.

If your strategic business goal is to achieve growth in monthly active users of your service, you might use business intelligence to understand how many monthly active users your service has, and whether the number is trending upwards or downwards. By doing so, you can determine if your current growth-oriented campaigns are working or not. For example, a KBQ might be, “For the past six months, how many monthly active users have I had?”. 

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  1. The Main Goals of AI

One of the primary goals of artificial intelligence is to simulate human intelligence. AI programs learn and make rational decisions by modeling human behaviors and thought processes.

When it comes to AI, technology professionals usually want to know two things: Can machines learn and adapt? Can they form reliable intuitions?

If businesses are willing to invest in and experiment with these questions, they will be able to reap significant benefits. 

Toptal Insights has explored how AI-driven applications like chatbots can lead to greater profitability and efficiency.

AI can provide human operators with prescriptions that they can act upon autonomously, rather than simply clarifying a messy picture.

Computers can make business decisions themselves with AI, unlike Business Intelligence, which makes it much easier to analyze data but leaves the decision-making up to humans. 

Chatbots can, for instance, answer customer questions without human interference. AI can be used to clarify a messy picture, give human operators prescriptions, and act on those prescriptions without human intervention.

Artificial Intelligence in Business Analytics and Business Intelligence

According to Statista, IoT-enabled connected devices are expected to increase from 26 billion in 2019 to 75 billion by 2025. The global business world is witnessing an increasing volume of connected devices and data. IoT devices produce a growing amount of data daily, generating over 5 quintillion bytes of data.

Business data is growing rapidly, and corporations can no longer rely solely on traditional business analytics or business intelligence tools to analyze and interpret this data and derive valuable business insights. 

Walmart processes its daily transactions in a matter of seconds using the ML-enabled HANA platform, which operates over 11,000 retail stores. Business intelligence tools based on machine learning, such as HANA, are expected to reduce customer infrastructure costs and enhance operations.

Domo, a business management software firm, is another example of an industry leader. Using Domo, businesses can extract and analyze data from Salesforce, Facebook, and Shopify, gaining valuable insights into customers, sales volumes, and inventory levels by combining AI, machine learning, and predictive analytics.

How will the role of business analysts be affected by this trend? Will they become more automated like the manufacturing sector?

The role of a business analyst will be transformed as AI-driven business analytics become more common. As AI technology powers the real-time data analysis, business analysts will need to focus more on the fundamental data analysis skills without any programming skills. 

The machine-learning-enabled DataRobot tool, for example, automates predictive modeling and is accessible to anyone without any prior machine learning experience or skills.

As machine learning grows, business analysts will be able to delegate most of their repetitive tasks to computers while focusing more on providing enterprises with advanced analytical skills.

Approximately 60% of business executives believe that a well-planned AI strategy can lead to more data-driven business opportunities based on the latest 2019 business intelligence artificial intelligence statistics. AI is considered a major business advantage by 72% of business leaders.

Business intelligence artificial intelligence bots aren’t just used as customer service bots; they also read and analyze business data to enable decision-making. Furthermore, BI bots can analyze data-related queries in natural language without requiring complex querying codes. 

According to Gartner, BI bots equipped with conversational analytics and natural language processing will increase the adoption of business intelligence artificial intelligence tools.

Artificial intelligence-driven BI tools can transform business enterprises in the following ways:

  • Manage the growing volume of big data from various sources and divide it into manageable chunks.
  • Real-time insights from the rapidly changing market data can assist business managers in making key decisions on a daily basis.
  • Reduce hiring costs for data-dependent businesses by eliminating the shortage of qualified data analysts.

It is your business outcomes that determine how you will achieve your core business objectives. For that reason, our intuitive Report Builder enables your users to generate personalized reports in just a few clicks. Our advanced reporting solution can save a tremendous amount of time and effort with its ability to select relevant data and design custom filters, schedule reports and so much more.

3 Major Applications of Artificial Intelligence in Business

business intelligence

Despite its use in many aspects of modern business enterprises, Artificial Intelligence is used in 3 major areas:

  1. Work Automation

In the U.S. alone, AI-driven work automation is expected to cut over 9 million jobs. Manufacturing firms are utilizing AI technologies to make smarter decisions. By using AI-powered smart sensors installed on its manufacturing equipment, General Electric, for example, is reducing the downtime of its machines.

AI and BI along with Internet of Things (IoT) technology are enabling organizations to reduce costs, increase productivity, and create more specialized jobs.

  1. Sales and Marketing

Marketing and sales are also undergoing significant transformations as artificial intelligence plays a significant role. Through the acquisition of data, AI technologies enable marketing personnel to automate most of their routine tasks, allowing them to focus on important sales functions like increasing customer satisfaction and sales.

With machine learning algorithms, Facebook tracks customer behavior and targets the right digital ad to them. Airbnb uses artificial intelligence to target the right accommodation prices based on customer demand and location.

  1. Customer Service

Approximately 30% of all online retail transactions are made on mobile devices. Mobile apps are becoming increasingly popular, with messaging and social media apps ranking among the five most popular categories. 

For example, Royal Dutch Airlines has developed a Facebook app that allows travelers to check in and get flight notifications. Businesses are investing in AI-powered chatbots to provide customer communication and service. Over 300,000 bots are currently active on Facebook Messenger, exchanging around 20 billion messages monthly between businesses and customers.

Conclusion

Despite providing plenty of business value on their own, bi ai can be deployed side-by-side for even better results. By combining bi ai, you can deliver effective analytical solutions in any business setting. First, BI analyzes historical data. AI then predicts future actions based on the available information. This is the best of both worlds. 

There are important considerations to be made regardless of whether a company is fully mature in its data competence or is just beginning with off-the-shelf solutions. The most important part is to ensure that your ai and bi analytics strategies align with your business goals.

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