MicroStrategy update aims to improve generative AI accuracy

New capabilities

Generative AI has been the dominant trend in data management and analytics in the two years since OpenAI's launch of ChatGPT brought significant improvement in large language model capabilities.

Two of the main potential benefits of generative AI are true natural language processing that lets workers of any skill level query and analyze data to inform decisions and process automation that enables data experts to be more efficient.

As a result, vendors such as MicroStrategy, Domo and Qlik -- among others -- have created suites that make it simple for customers to combine generative AI capabilities with their own proprietary data to develop tools that understand their business.

Accuracy, however, has been a problem for generative AI tools. Even when trained with quality data, generative AI models and applications sometimes deliver incorrect and even bizarre responses called AI hallucinations.

Data quality helps reduce the likelihood of hallucinations. So does data volume -- the more quality data a model or applications is trained on, the less likely it is to make up a response. But they aren't foolproof, which is one reason MicroStrategy provided explanations showing how Auto arrived at a response.

Now, by upgrading the large language model underpinning Auto AI to OpenAI's GPT-4o, MicroStrategy is hoping to further improve the accuracy of generative AI responses to make them more trustworthy. With GPT-4o working in concert with an enterprise's proprietary data, Auto is now better at understanding the context of a user's query, which results in a more relevant and accurate response.

Beyond attempting to improve the accuracy of Auto's responses, new MicroStrategy AI features include Auto for Teams, an integration that lets users query Auto directly in Microsoft Teams so they don't have to leave their collaboration environment to work with data.

The suite also includes Auto Narratives, a tool that provides automatically generated summaries of text and visualizations to provide users with context related to the data they're using. It also has a feature that enables developers to train bots using multiple datasets without requiring them to first consolidate their data into a single, unified set.

Each are significant and stand to benefit MicroStrategy customers, according to Leone.

"Auto for Teams is a feature that I think anyone with Teams would appreciate: Simply message an expert on a certain topic and get a relevant response," he said. "And … Auto Narratives really feeds into the idea that explainability matters. Enabling more folks to understand data remains a critical area for businesses, and this serves as a reliable shortcut."

As MicroStrategy adds new features to MicroStrategy AI and tries to improve existing ones, customer feedback provides the primary motivation for deciding what to feature in a given platform update, according to PeggySue Werthessen, the vendor's vice president of go-to-market strategy.

"The impetus for these enhanced features of Auto and actionable analytics was working directly with our customers to understand how GenAI can deliver real business value," she said.

Complementing customer feedback is MicroStrategy's ongoing effort to ensure that its platform is "accessible, flexible, and performs with reliability and scalability to support demanding use cases," Werthessen added.

Beyond the new MicroStrategy AI features, new MicroStrategy One capabilities include the following:

• New integrations with Microsoft Office 365 that enable users to import entire dashboards and other data assets into Excel and PowerPoint presentations and then keep those data assets current with automatic refreshes.
• A connector to Tableau so joint customers can access MicroStrategy datasets in their Tableau environments.
• Python action buttons, a feature that allows users to automate Python workflows in third-party applications such as Salesforce and Workday from their MicroStrategy dashboards

Of note are the Python action buttons, according to Werthessen.

"This means that a front-line knowledge worker can initiate workflows for individual items in a list with a click of a button," she said.

Next steps

With the latest MicroStrategy One update now available, including new generative AI capabilities, one of the vendor's priorities will be developing a generative AI-powered data modeling tool, according to Werthessen.

It's a solid incremental release that further enhances the capabilities of MicroStrategy AI. They have really prioritized convenience and trust in this release.

Auto Data Modeling is now in private preview and will be one of the next significant additions to MicroStrategy AI.

"We will be working with a limited set of customers over the coming couple of quarters to refine this capability," Werthessen said.

Beyond generative AI, MicroStrategy is providing customers with the flexibility to use its platform on the cloud of their choice, she continued. Toward that end, the vendor continues to adjust its cloud native architecture to make sure it is fully deployed on AWS, Google Cloud and Microsoft Azure.

Leone, meanwhile, suggested that MicroStrategy further advance its AI suite by adding more integrations.

Just as Auto for Teams allows joint MicroStrategy and Teams users to benefit from AI in their collaboration workflow, integrations between Auto and other tools would further extend its reach.

"Expanding those integrations will be critical in exposing more users to the power of MicroStrategy AI and Auto. Additionally, moving … more to integrations that enable actions will be incredibly valuable going forward," Leone 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.