AI has taken the business world by storm, with organizations testing applications in a wide variety of areas to increase productivity and lower costs. Of the many potential applications for artificial intelligence, however, one of the most noteworthy is its potential for being used in conjunction with business intelligence (BI) tools to enhance an organization’s data usage and decision-making capabilities.
With the convergence of generative AI and business intelligence, leaders have a more powerful set of tools to aid them in making informed decisions that will chart the future course of their brand.
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The value of combining AI and BI
The value of applying artificial intelligence to business intelligence tools should be immediately apparent in light of just how much data businesses create and rely on every day. According to an analysis by Veritas, the average enterprise-level business stores roughly 10PB of data — the equivalent of 23.1 billion files — with 15% of that data being business-critical, 33% being redundant or obsolete and 52% being unclassified.
From sales pipelines and logistics tracking to the data that is collected from web visitors or through customer resource management software, the sheer number of data points a business can (and likely should) be using to improve its output can quickly become overwhelming.
As Konstantinos Mitsopoulos, a research scientist at the Institute for Human and Machine Cognition (IHMC) in Florida explains in an interview with the Harvard Business Review, “In principle, generative AI systems can help overcome some of the problems affecting human decision making, such as limited working memory, short attention spans, and decision fatigue, especially when it comes to making decisions under pressure. Generative AI tools can potentially help decision makers save time, conserve energy, and free up time to focus on the issues or questions that matter most.”
How generative business intelligence works
While business intelligence tools contain a wide array of useful data, accessing that data is often a challenge for organizations. When team members don’t understand how to turn available data into meaningful insights — or even how to find that data in the first place — it doesn’t deliver its intended value.
On the other hand, combining AI and BI (often referred to as generative business intelligence or GenBI) makes it much simpler to extract data-related insights. GenBI tools allow users to type in a request or question using natural language, which the combined AI and BI solution transforms into an analytical query to produce a relevant analysis or even a complete dashboard.
In an interview with Unite.ai, Omri Kohl, CEO and co-founder of Pyramid Analytics, explains, “Quite simply, GenBI allows anyone to tap into the insights they need, regardless of their level of expertise. Traditional BI tools require the user to know which is the best data manipulation technique to receive the necessary results. But most people don’t think in pie charts, scatter charts or tables. They don’t want to have to work out which visualization is the most effective for their situation — they just want answers to their questions. GenBI delivers these answers to anyone, regardless of their expertise.”
Notably, this combination of AI and BI allows query results to be produced in either a plain language version or a visualization that best communicates the data. GenBI removes the tech barriers that often keep individuals from accessing and utilizing the data they need. These tools provide the basis for informed decision-making by not only providing data but making it easy to understand.
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Practical applications
Business intelligence has long been considered a valuable tool for identifying trends in consumer and market behavior, benchmarking performance and understanding what is or isn’t working for a company. Quality data analysis is essential for leaders to make informed decisions to guide marketing, product development and other crucial aspects of the business.
By using AI to enhance what traditional business intelligence is capable of, however, leaders open up a new world of possibilities for how they can use their data to strengthen the business.
For example, AI can build upon standard business intelligence data by using that historic data for predictive analytics — namely, in forecasting outcomes related to potential future trends or business decisions. This enables organizations to take a more proactive approach to understanding the risks and opportunities associated with different events and actions.
AI’s ability to automatically identify trends and anomalies can prove crucial in empowering the human decision-making process. With so much data available, combining AI and BI can help leaders pinpoint specific issues or concerns and respond quickly. Alternatively, GenBI can make it easier for leaders to identify opportunities to personalize the customer experience or streamline their internal processes to create more engaging experiences.
Ultimately, by enhancing operational efficiency, the combination of AI and BI enables leaders to make decisions with confidence, knowing that they have access to all relevant data related to that decision.
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The future of decision-making
By combining straightforward interfacing with the ability to maximize an organization’s capability to use and understand its data, the combination of AI and BI is poised to dramatically improve business decision-making in the years to come.
Leaders who strategically implement these resources to augment their own knowledge and skills will find themselves well-positioned to achieve outcomes in line with their company’s most important goals.