MicroStrategy targets trusted AI with latest platform update

New capabilities

While the key potential of generative AI for business analytics is that it can make data experts more efficient and enable non-experts to work with data using natural language, one of its drawbacks is a lack of accuracy.

For decades, the percentage of employees within organizations using analytics in their job has stagnated around 25%. Historically, analytics platforms have been complex, requiring users to write code to carry out most tasks.

Large language models (LLMs) such as the GPT line from OpenAI and Google Gemini change that.

LLMs have extensive vocabularies that when integrated with analytics platforms enable users to interact with data using true natural language rather than code. That suddenly makes analytics tools potentially accessible to more users. In addition, it reduces the time it takes for existing analytics users to carry out tasks.

However, though language models make interacting with data easier, they suffer from AI hallucinations. If trained on proper data related to a user’s query, the likelihood of a hallucination is low. However, it is not completely eliminated.

As a result, trust is a big issue with generative AI.

To address the lack of trust, vendors such as MicroStrategy are taking steps to help users know whether the responses they receive from generative AI tools such as MicroStrategy’s Auto Answers, which lets customers essentially converse with their data, are accurate.

AI Explainability is a feature in MicroStrategy AI that enables users to request that Auto provide text and visual explanations showing what the bot interpreted the user’s question to be asking and what it used to respond. The intent is to add context to generative AI responses, provide what amounts to data lineage and enable users to check the work of the tool.

Other vendors providing similar generative AI explainability include Domo and Tableau.

Beyond AI Explainability, a new feature in MicroStrategy AI that lets customers to update MicroStrategy’s semantic network is significant, according to Leone.

By describing terms using natural language rather than code, the feature enables Auto to better understand an individual organization and interpret queries related to that organization’s data.

“I particularly like the way in which MicroStrategy is enabling customers to enrich AI with their own knowledge assets,” Leone said. “It serves as a powerful way to not only improve accuracy and reduce hallucinations, but also deliver somewhat personalized responses in the context of their particular business unit.”

In addition, the latest MicroStrategy One update includes the following:

• Automated workflows triggered from any MicroStrategy One dashboard or application featuring MicroStrategy Auto so that customers can improve the time it takes to carry out repeatable tasks. Using Python, customers can connect to systems such as Salesforce, Marketo and Workforce and automate actions such as updating customer data, triggering email campaigns and approving expenses.
• Auto Express, a self-service environment where potential customers can explore MicroStrategy AI for 30 days without any commitment.
• Data Summary, an environment within Auto where users can view and use data sets.
• Auto on Mobile so that customers can run Auto as a standalone mobile application.
• Auto API, a feature that enables users to connect MicroStrategy AI to any application using an API.

The impetus for the features included in the latest MicroStrategy One release came largely from customer and partner feedback, according to PeggySue Werthessen, the vendor’s vice president of product marketing.

In particular, MicroStrategy’s community helped the vendor identify ways to make its platform easier to use for non-technical experts, she noted.

“Our enhancements come from working hand-in-hand with our innovation partners, such as Pfizer, which helped us work through many real world use cases for AI and evaluate different ways to improve the experience for everyday users — people who are not necessarily data experts,” Werthessen said.

Leone, meanwhile, noted that the new features taken as one demonstrate MicroStrategy’s progress toward delivering trusted AI to enterprise customers.

“That means improving Auto’s ability to interpret business-specific questions via the MicroStrategy Semantic Graph,” he said. “That means offering greater AI explainability in Auto with both text and visual explanations. And with Auto Express, organizations get a 30-day trial to test out these capabilities in a self-service environment.”

Next steps

MicroStrategy first introduced the concept of “intelligence everywhere” with the launch of HyperIntelligence in 2019.

While HyperIntelligence is no longer a focal point of the vendor’s product development strategy, delivering data to users in their normal workflows rather than forcing them to visit a BI environment to engage with data still is, according to Werthessen.

As a result, MicroStrategy plans to continue finding new ways to provide customers with data in real time.

“The more that we can bring the right data at the right time directly to the people that drive the business, the more our customers can realize their objective of being data driven organizations,” she said.

Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.