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AI and BI are almost similar yet distinct, you can consider AI as BI’s upgraded version sometimes. AI (Artificial Intelligence) is newer in the industry as compared with BI (Business Intelligence). Business Intelligence uses different technologies and tools to gather and analyse business data whereas, Artificial Intelligence uses computer systems to imitate human capabilities such as problem-solving, learning, and judgement. This article dives into the differences between Artificial Intelligence and Business Intelligence and their priorities in relatable situations.
1. Goals of AI vs BI: BI aims to analyse data through collecting and reporting. BI enhances the quality and consistency of the data while leading them towards a clearer path, however they don’t guide on how the data can be used during decision-making. Companies such as Microsoft, Oracle & Tableau use BI tools to create spreadsheets, operation metrics, dashboards, graphs, charts and other displays. Besides, they also use these tools for a range of diverse functions involving business, which includes HR and Marketing.
On the other side, AI targets to model human intelligence. Through modelling human needs, it makes coherent decisions. Besides, it enables systems to learn from their data and improve their performance within a certain period of time.
2. Use cases of BI & AI: BI has become so common and fundamental towards the way where businesses operate that persons in an organization don’t even realize they rely on it. Individuals who have used Microsoft Excel or any another spreadsheet application from a business perspective, might have come across BI. Organizations also use BI to understand a client’s demands. They interact with their customers through chatbots, emails, including social media.
BI can collect data from various sources and represent it in a cohesive and a unified format, which enable businesses to gain a deeper understanding on how they can serve their customers best. Companies also use BI to boost efficiency in operations.
Nowadays, AI is used in various segments beginning from medical diagnoses to establishing sustainable energy grids and enabling individuals to have a better understanding of customers’ wants. There are numerous AI powered enterprise applications including process automation. Applications such as Automation Process update information such as customers’ needs and records, manage customer standard communications, and offer basic guidance on standardized contracts and documentation.
3. Technologies: BI uses technologies such as data warehousing, data mining, ETL (Extract Transform & Load), reporting tools such as OLAP (Online Analytical Processing), and dashboarding.
AI utilizes technologies like machine learning, neural networks, natural language processing (NLP), robotics and much more.
4. Implementation Mechanisms: BI often requires user-friendly interfaces and tools. The implementation encompasses setting up of data sources, developing data models, and devising reports and dashboards.
AI can be implemented through dedicated knowledge and expertise in data science, machine learning, and algorithm development. In comparison with BI, AI implementation is a bit more complex and intense to resources, including data preparation, model training, and frequent monitoring.
1. Data Analysis: AI can support BI by integrating updated data analysis mechanisms. Machine Learning within AI can analyse critical data through algorithms, which traditional BI tools might lack.
2. Automation: AI can enable BI tools to deliver outputs quickly through data process and analysis by automation and with less human involvement.
3. Immediate response to changing market scenarios: The speed at which AI systems respond and react to market changes, allows organizations in quick decision making. AI powered BI tools monitor real-time data from diverse sources, making organizations aware of significant events that can bring an impact on their businesses, while initiating swift strategic adjustments.
4. Convenient Decision Making: AI ensures smooth decision making. Unlike humans who may be influenced by biases or fluctuating levels of performance, AI mechanisms offer straight and compact analysis and suggestions based on the data they receive.
AI & BI are complementary to each other, as AI can be considered to BI’s upgraded version if only both are integrated. However, AI implementation needs a lot expertise knowledge including machine learning, NLP (Natural Language Processing), data science and algorithm development. On a concluded note, both are important in real life scenario, however AI is newer in the industry compared to BI and is quicker than that.
1. What is the primary difference between AI and BI?
A: AI focuses on creating systems besides adapting and learning from data resources, autonomously, whereas BI gathers, analyses, and reports data for businesses and organizations.
2. In what ways AI and BI help businesses?
A: AI enhance businesses by analysing data and modelling human behaviour through algorithms. BI collects data from various sources, analyses them to reveal insight while generating reports and dashboards.
3. Can AI & BI be used together?
A: AI and BI can be integrated together. AI can enhance BI by providing updated analytical mechanisms, automation leading to a more efficient and insightful business aura.
