Business Intelligence and artificial intelligence are increasingly crucial yet often misunderstood tools in an enterprise context. This article clarifies the differences between each field and explains how they will work together in the future.
Business Intelligence and artificial intelligence are increasingly crucial yet often misunderstood tools in an enterprise context.
Business intelligence (BI) refers to the use of various technologies and tools to collect and analyze business data. The main purpose of BI is to provide companies with useful information and analysis to aid decision-making. Using BI allows businesses to make decisions nearly five times faster than they otherwise could. Both AI and BI have key, and in some cases overlapping, enterprise applications. There are, however, important differences between these technologies that businesses should grasp. Understanding these differences can clarify how AI and BI complement one another and may help businesses to sustain and run operation with efficiently and effectively.
BI and AI are distinct but complementary. The “intelligence” in AI refers to computer intelligence, while in BI it refers to the more intelligent business decision-making that data analysis and visualization can yield. BI can help companies bring order to the massive amounts of data they collect. But neat visualizations and dashboards may not always be sufficient.
Artificial intelligence (AI) use of computer systems to mimic various attributes of human intelligence, such as problem solving, learning, and judgment. Though in its technological infancy, businesses see huge potential in AI for speech recognition, decision-making, and everything in between. A 2017 survey conducted by PwC shows that over 72 percent of business leaders believe that the using AI can “enable humans to concentrate on meaningful work.”
Both AI and BI have key, and in some cases overlapping, enterprise applications.
The difference between AI and Machine learning
Artificial intelligence and machine learning are very closely related and connected. Because of this relationship, when you look into AI vs. machine learning, you’re really looking into their interconnection.
What is artificial intelligence (AI)?
Artificial intelligence is the capability of a computer system to mimic human cognitive functions such as learning and problem-solving. Through AI, a computer system uses math and logic to simulate the reasoning that people use to learn from new information and make decisions. In business, AI is used for various applications such as natural language processing (NLP), image recognition, recommendation systems, predictive analytics, and process automation. AI can be used to improve customer experience, boost revenue, increase productivity, and drive business growth. Some examples of how AI is used in business include:
- Personalization: Personalized customer services, experiences, and support
- Fraud detection: Real-time identification of credit fraud
- Supply chain optimization: Prediction of material prices and shipping, and estimation of how fast products will move through the supply chain
- Forecasting: Analysis of financial data to make predictions about future trends or outcomes
- Compliance: Automation of compliance checks and maintenance of real-time records of all financial transactions and activities
What is machine learning?
Machine learning is an application of AI. It’s the process of using mathematical models of data to help a computer learn without direct instruction. This enables a computer system to continue learning and improving on its own, based on experience
In summary, BI leverages data analytics to provide insights into past and current performance, while AI uses advanced technologies like machine learning to develop intelligent systems capable of learning, reasoning, and decision-making. Machine learning is a common thread that enhances both BI and AI applications, driving data-driven decision-making and automation in businesses.
