Enabling analysts to compile and retrieve data in a way that facilitates deep analysis with greater speed is perhaps the key deliverable of AI. Machine learning has promised to take decision making to a new level, allowing exponential completion of mundane and complex tasks to facilitate greater outcomes. Even in its current state, is AI really delivering on that promise?
While AI strives to provide faster decision making, BI’s promise is augmenting decision making through improved analytics. It’s understood that BI is designed to deliver fast and accurate reporting, competitive analysis, and identification of market trends, among other things. Ultimately, organizations desire to turn such insight into action. The question remains as to whether BI will ultimately achieve this potential. Can AI provide BI the augmented analytics capabilities required by organizations?
Blending AI and BI with 360-degree decision making
No matter the size or industry, organizations strive for better decision-making capability and improved outcomes. The application of AI to BI continues to develop, but that marriage has yet to mature. Organizations that used these two previously separate capabilities are now finding its combination potentially transformative.
In short, AI is poised to transform how analysts and their organizations work with information. Rather than BI providing fancy dashboards with little intelligence, AI-enabled BI can scan through a variety of information sources and help determine the good and the bad. The result is the notification of the right stakeholder with the right information in order to make the right decision at the right time.
Companies leveraging AI-enabled BI today
The idea of implementing AI-enabled BI is not far off. In fact, it’s already here, as many organizations have begun this revolution, transforming their operations with noticeable results.
ING, a Dutch multinational banking and financial services organization, has used AI-enabled BI. ING has tied payments, client credit data, and other information into a powerful tool for various departments. The sales department, for example, can use the insights gleaned from the new tool to help clients see various options in order to make better decisions. In addition, the risk department can improve the quality and efficiency of risk assessment to more efficiently determine loans and lines of credit for worthy clients.
Walmart, the operator of more than 11,000 retails stores worldwide, has also joined the AI-enabled BI revolution by incorporating SAP’s HANA. This cloud platform replicates and takes in structured data, including sales transactions and customer information, from apps, relational databases, and other sources. Due to Walmart’s complexity, the solution they’ve implemented allows the organization to process high volumes of transaction records in a matter of seconds. This allows Walmart to make faster decisions in purchasing, sourcing and transportation. This ability to more effectively analyze data through AI-enabled BI is leading to greater efficiency. It’s also resulting in better decision making and greater control of costs.
Walmart’s application of AI-enabled BI is not just for internal use. The company’s website can now make recommendations to individual consumers, based on location, availability, and other criteria. This enables Walmart to compete more effectively with the likes of Amazon and other online-only retailers.
In the heavy industry sector, General Electric is utilizing AI-enabled BI to more accurately predict the need for repairs, ensuring machinery runs at peak efficiency. The company’s process involves incorporating sensors in machinery and vehicles while connecting them to production plans. This means equipment can be digitized and effectively monitored via AI. GE’s operation takes full advantage of the IoT, where sensors communicate seamlessly with networks. The Business Intelligence solution allows for rapid monitoring and resolution of potential issues before they become full-blown problems.