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I spoke with MicroStrategy CEO Phong Le about how the new combination of generative AI and business intelligence is creating powerful new solutions.
Indeed, some industry observers see these two technologies as an unusual pairing. Business intelligence has a long history as a stable platform that relies on critical data analysis. Important financial decisions are made based on insights gained from BI applications.
In comparison, generative AI is a brand new, emerging technology with great potential – creative output based on simple text prompts – but also sometimes hallucinatory. Does this new player fit into the staid world of business intelligence?
In fact, Phong Le says that the combination of generative AI and BI is still in its infancy. In contrast, “MicroStrategy has been working on business intelligence for over 30 years. As you know, we invented this space, but there hasn’t been much innovation in this space in the last 10 years.
“In my opinion, generative AI has breathed new life into the BI space and redefined what's important,” he said, noting that generative AI's ability to provide natural language answers is useful in both consumer and business contexts. “When you get to the heart of what businesses want, you need answers to numerical data.”
“When I ask a question of an analyst, or ultimately a Gen AI bot, I want answers, not predictive answers. The combination of Gen AI and BI does just that — solving problems that aren't being solved today.”
View the full interview Select highlights from the interview below.
Interview highlight: Phong Le talks about generative AI and business intelligence
These interview highlights have been edited for length and clarity.
Generative AI and the Future of Business Intelligence
The addition of generative AI “is the biggest change we've seen in decades, the biggest change added to business intelligence. Generative AI has made it possible in all areas of software, but especially in BI. So I'm really excited to see what the future holds.”
Over the past decade or so, companies have been working to distribute access to BI insights to their internal “edge” workers, retail store managers, and salespeople on the go.
“That came in the form of dashboards and applications,” Le says, “and what people realized is that the further away you are from the core of the enterprise, the less likely you are to feel comfortable consuming that information in a traditional dashboard or grid report.”
In other words, corporate finance personnel are familiar with BI programs, but retail managers often are not.
“Store managers are going to rely on intuition, not data from grid reports. So what we've been trying to do over the last three years is [figure out]: How can we get edge workers to make better use of BI?
“They don't read a lot of email. So let's give them self-service email on the web. They don't look at the web a lot, so let's give it to them on their mobile devices. Now we're getting somewhere.
“First-generation AI will enable retail associates to simply ask questions, rather than the currently unused consumption paradigm, in natural language: 'How much do we have in stock at the moment?'
“So now our frontline workers are empowered with BI and data to make decisions. And we think Gen AI is going to solve that last-mile problem.”
To see a list of the top generative AI apps, read our guide “Top 20 Generative AI Tools & Apps”.
