Discover how the combination of AI and BI guides BI managers to make quick business decisions and steer large-scale data.
We are living in an era of change, where industries are changing their traditional way of managing and streamlining organizational goals. SMEs and SMBs are gradually gaining market share and developing well-known brands, eliminating the term monopoly, as any business with an appropriate data strategy can create its own space in this competitive landscape.
To stay competitive, businesses are attracted to two potential technologies: artificial intelligence (AI) and business intelligence (BI). Combined, they offer a powerful tool that transforms raw data into implementable insight by making data accessible to BI managers. This collaboration between AI and BI enables companies to steer large-scale data efficiently and make quick business decisions.
This article provides an overview of the current landscape of AI and BI, highlighting the evolution of BI systems after integrating artificial intelligence.
1. The Synergy Between BI and AI
The partnership between artificial intelligence and business intelligence has become the backbone of the modern business world.
In this competitive market, businesses across all industries strive to drive innovation and automation as an integrated strategy that reshapes organizations from a mindset of data and data-driven decision-making.
When BI managers integrate AI into BI systems in businesses, it harnesses big data’s power, providing previously inaccessible insights.
Traditionally, BI systems were focused on historical data analysis, which was collected and analyzed manually with the help of a data team, which tends to be a tedious job, and businesses often face data bias.
However, AI-powered BI systems have become a dynamic tool that uses predictive analysis and real-time decision-making skills to identify market patterns and predict future trends, providing a more holistic view of business operations and allowing your organization to make informed decisions.
The current landscape of AI-driven BI is a combination of big data analytics, machine learning (ML) algorithms, and AI in traditional BI systems, leading to a more sophisticated tool that provides spontaneous and automated analytical results.
As the AI field diversifies, the BI system will mature continuously, posing an integral role in shaping the future of business strategies across various industries.
2. AI Business Intelligence vs. Traditional Business Intelligence
Companies across industries have been using business intelligence tools and software for decades to evaluate business performance. But in this digital world, traditional BI services are becoming obsolete as companies opt for AI-driven BI solutions that are nuanced and BI managers can get faster results.
If you are searching for BI tools that fit your modern business, here are four differences between AI-driven BI services and traditional services:
3. Evolution of Business Intelligence Tools and Techniques
The advancement of business intelligence (BI) tools, software, and techniques after the integration of AI has witnessed significant developments in the fields of business decision-making and data analytics. With novel ML tools designed for data fusion in the analysis of sentiments about specific events, it aims to support business decisions with human-centric explanations. This is a classic advancement in BI as the combination of ML and sentiment analysis provides a comprehensive insight into customers’ sentiments and updated market trends.
The role of Robotic Process Automation (RPA) is to generate an automated business process that improves accuracy, productivity, and efficiency among BI managers and their teams and also provide customer satisfaction.
Let’s take a glance at a few examples of BI tools and software with use cases:
3.1. Using AI to Turn Databases Into Useful Information
The major utilization of AI in business intelligence can be witnessed in HANA, a cloud platform by SAP that enables BI managers and their teams to manage databases of accumulated information.
HANA replicates and ingests structured data from relational databases, applications, and other sources. For instance, Walmart has been using HANA to process its large volumes of data within a few minutes, enabling it to operate faster and control the cost of its business office as the process of data collection is automated.
3.2. BI’s Deep Analytics Platform
Avanade, a joint venture of Microsoft and Accenture, leverages the Cortana Intelligence Suite and many other solutions used for predictive analyses and data-based insight. This platform helps companies gain a better perspective and insight into the current market and learn about customer behavior through analytics.
For instance, Pacific Specialty, an insurance company, tapped Avanade to develop an analytical platform with the intention that this application would be more staff-oriented and give them business insights. The goal behind making this platform was to understand customer and policy data for better business growth. By understanding policyholder behavior and trends, Pacific Specialties can develop better products and services.
Artificial intelligence is transforming business intelligence in numerous ways by making it a powerful tool for BI managers and their teams to work efficiently and effectively and have access to a wider range of customers. Even small businesses and enterprises are trying their hands at AI-powered BI software, intending to automate the maximum work of data analytics to make quick decisions.
In the coming years, we can expect more potential use cases of AI-powered business intelligence software and tools, helping businesses solve the greatest challenges and reach new heights.
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