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AI has taken the business world by storm, with organizations testing applications in a number of areas to extend productivity and reduce costs. However, among the many potential uses for AI, one of the most notable is its potential for use in conjunction with business intelligence (BI) tools to extend an organization’s data utilization and decision-making capabilities.
By combining generative AI and business intelligence, leaders have a simpler set of tools to assist them make informed decisions that can impact the future course of their brand.
The Value of Combining AI and BI
The value of applying AI to business intelligence tools needs to be immediately apparent in light of how much data corporations create and rely on every day. According to a Veritas study, the average enterprise-class company stores about 10PB of knowledge — comparable to 23.1 billion files — of which 15% is business-critical, 33% is redundant or outdated, and 52% is not confidential.
From sales processes and logistics tracking to data collected from website visitors or through customer asset management software, the amount of knowledge a business can (and probably should) leverage to enhance results can quickly develop into overwhelming.
As Konstantinos Mitsopoulos, a research scientist at the Institute for Human and Machine Cognition (IHMC) in Florida, explains, interview from Harvard Business Review, “In principle, generative AI systems can help overcome some of the problems that affect 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 have the potential to help decision-makers save time, 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 selection of useful data, accessing it is often a challenge for organizations. When team members do not understand the way to transform available data into meaningful insights—or even the way to find that data—it does not deliver the intended value.
On the other hand, combining AI and BI (sometimes called generative business intelligence or GenBI) makes it much easier to extract insights from data. GenBI tools allow users to type a request or query using natural language, which the combined AI and BI solution then transforms into an analytical query to generate relevant evaluation or even a complete dashboard.
In an interview with Unite.ai, Omri Kohl, CEO and co-founder of Pyramid Analytics, explain“Simply put, GenBI empowers anyone with the insights they need, regardless of their level of expertise. Traditional BI tools require users to know how to best manipulate data to get the results they need. But most people don’t think in terms of pie charts, scatter plots, or tables. They don’t want to think about which visualization works best for their situation—they just want answers to their questions. GenBI delivers those answers to anyone, regardless of their level of expertise.”
Interestingly, this mixture of AI and BI allows for query results to be produced in plain language or visualized versions that best convey the data. GenBI removes the technological barriers that usually prevent people from accessing and using the data they need. These tools provide a foundation for informed decision-making by not only providing data but also making it easier to grasp.
Practical applications
Business intelligence has long been considered a useful tool for identifying trends in consumer and market behavior, benchmarking performance, and understanding what is and isn’t working in a business. Qualitative data evaluation is essential for leaders to make informed decisions to drive marketing, product development, and other key features of the business.
By using AI to increase the capabilities of traditional business intelligence tools, leaders are opening up latest opportunities to leverage data to power their business.
For example, AI can build on standard business intelligence data by using this historical data for predictive analytics—namely, forecasting outcomes related to potential future trends or business decisions. This allows organizations to take a more proactive approach to understanding the risks and opportunities associated with various events and activities.
AI’s ability to mechanically discover trends and anomalies could prove crucial in improving human decision-making. With so much data available, combining AI and BI may also help leaders pinpoint specific issues or concerns and respond quickly. Alternatively, GenBI may also help leaders discover opportunities to personalize customer experiences or streamline internal processes to create more engaging experiences.
Ultimately, by increasing operational efficiency, the combination of artificial intelligence (AI) and business analytics (BI) allows leaders to make decisions with confidence, knowing they have access to all the relevant data related to a given decision.
The way forward for decision making
By combining a easy interface with the ability to maximise an organization’s potential to leverage and understand its data, the combination of artificial intelligence (AI) and business analytics (BI) has the potential to radically improve business decision-making in the years to return.
Leaders who strategically deploy these resources to expand their very own knowledge and skills will probably be well-positioned to attain results that align with their company’s most significant goals.