Integration impasse: Why organizations can’t wait for data integration before deploying AI
The key to making organizations truly data-driven is making data easily accessible, reliable, and actionable to any employee, from the C-suite to frontline workers. Traditionally, BI handled the reliability part well, but it wasn’t built for widespread access or actions. The integration of GenAI and browser-based or application-embedded contextual intelligence changes that.
With a modern AI+BI approach, organizations can provide relevant data to employees no matter where employees work, whether in web, mobile, or even legacy apps. Users would simply hover over any keywords on the screen—such as customer names, product SKUs, accounting codes—and instantly see relevant analytics data about those objects pop up in a window. That alone is a powerful capability, but with the addition of GenAI, employees can ask questions using natural language to gain deeper insights and even initiate actions within different applications.
To illustrate, consider a sales representative preparing for a call with a customer. The rep wants to make sure they have a firm grasp on their contact’s role, historical orders, contract terms, and support tickets. Usually, this would require 30 minutes or more of switching between applications and manually copying data from one system to another or to a notepad. With modern, contextual BI, it’s as easy as hovering over the customer’s name to view CRM profile data, moving the cursor to a product name to see quarterly purchase orders from the ERP system, then hovering over an incident number to see the last support ticket logged in the help desk system. If these insights aren’t enough, whatever additional information the sales rep needs can be retrieved instantly by typing their questions into a chat box using GenAI.
In effect, the new world of contextual, AI-powered BI follows the 80/20 rule, delivering 80% of the value of an enterprise-wide data integration project at 20% of the cost and effort. The need for comprehensive data management will always be important, and there are many other benefits of digital transformation, but CIOs don’t need to delay GenAI projects until the completion of a giant data centralization effort. By adopting a more flexible approach that incorporates GenAI and next-generation BI tools, businesses can navigate the complexities of modern data ecosystems while driving innovation and maintaining a competitive edge in an AI-driven world.