From Data to Decisions: How AI is Revolutionizing Business Intelligence

From Data to Decisions: How AI is Revolutionizing Business Intelligence

According to a report by Statista, approximately 402.74 million terabytes of data are created each day, and 90% of global data was created in just the last two years. Currently, there are 517 data centres in the United Kingdom, which makes it the third largest country in terms of the number of data centres, followed by the United States and Germany. But what is happening with this data? Businesses have been using data to make informed decisions since decades but recently the use of data in the day-to-day business decisions has become inevitable. The precision and speed to convert this raw data into informed business decisions has become crucial for businesses to stay competitive. This is where Artificial Intelligence comes into play. In the UK, where industries are navigating economic uncertainties and evolving regulations, AI is revolutionizing how businesses utilize data to make informed, timely decisions.

What is Business Intelligence?

Business intelligence has been around for decades and in simple terms refers to collecting, processing, and analysing data to make informed decisions. The question arises about what has changed in recent years to create such a big buzz about BI. Traditionally, BI relied on static dashboards and manual reporting, offering limited insights, however, due to the massive amount of data being generated, there was a need for faster and more accurate insights in taking day to day business decisions and this was where AI entered and changed the entire landscape. AI provides real time insights and predictive analytics to go beyond “what happened” to uncover “what will happen” and “what to do next.”

Real-World Use Cases of AI in BI

• 1. Financial Services

  AI enables financial institutions to predict loan defaults, identify fraudulent transactions, and enhance customer experience. As mentioned in a recent report by the Bank of England , 75% of financial institutions are already using AI with a further 10% planning to use it in the next year. The report also mentions that AI driven data insights has been the biggest use case for these firms.

• 2. Retail and E-Commerce

  Retailers use AI to analyze purchasing patterns, improve personalization, and manage supply chains. A McKinsey report found that retailers adopting AI in their BI processes saw up to a 20% increase in sales productivity

• 3. Public Sector

  Local councils in the UK have been using AI-powered BI tools to allocate resources efficiently. AI is also used in traffic management systems to reduce congestion and optimize urban planning. The UK government is considering using AI to build smart cities by leveraging environmental data to reduce pollution and environmental impact.

Addressing Challenges in AI-Driven BI

While AI brings immense benefits, challenges like data quality, integration, and privacy remain. To address these, businesses should:

• 1. Invest In clean data

  AI driven insights are only as good as the data that have been used to train the model. As seen in a lot of cases, poor quality data leads to inaccuracies and poor decision making. Businesses should invest in collecting accurate data and at the same time being compliant with laws like GDPR to ensure accuracy in their AI models.

• 2. Human Intervention

  On June 3 , 2017, there was a terror attack in Central London and the algorithm of Uber at the time raised prices by 200%, which caused a backlash for the company and stained its brand image. Businesses need to keep a person accountable for their algorithms as these AI driven BI tools are still in their nascent stages.

• 3. Transparency about Data Collection and Privacy

  Due to strict regulations like GDPR and recent FCA regulations, businesses must keep the process of collecting and using the data to train AI models completely transparent. According to a report by the Bank Of England, Data Privacy and protection remains the largest potential threat to the use of AI based BI models and expected to remain the highest perceived risk in the next three years.

Conclusion

As we continue to generate petabytes of data on a daily basis, the process and speed of converting this raw data into informed business decisions will help companies remain competitive in the future. AI empowers companies to streamline this process and in the future we will see more and more companies leverage AI to make business decisions. However, these AI driven BI tools are still in their nascent stages and can work counter productively if not developed and used properly.

Author: Shradul Kumar Arora , Marketing Analyst at Digilytics AI

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