GenAI on the rise

You don’t have to look far to see the rapid evolution of generative AI accelerating automation and changing demand for various occupations. Businesses of all sizes, across sectors, have started experimenting with, or fully embracing, AI.

Ventana Research, now part of leading global technology research and advisory firm ISG, found “one-quarter of organizations currently use AI. Over a third (34%) plan to adopt AI within the next 12 months and 9 in 10 (87%) say they will adopt gen AI at some point.” Of the organizations already using AI, nearly all planned to increase or maintain their levels of investment.

The Ventana research, commissioned by MicroStrategy, shows that Gen AI in business intelligence can:

• Provide a competitive advantage by empowering employees with data-driven insights and data visualizations at every level.
• Enhance customer experiences by offering them the right product at the right time.
• Lower costs through large-scale optimization.
• Improve the bottom line by reducing inefficiencies and driving sales.

Generative AI at work

Generative AI, or GenAI, is so called because it can process massive data sets to identify trends and patterns and create enhanced insights into your data. It is still in early stages, but already coupling generative AI with natural language processing (NLP) tools to understand human meaning and context is opening up a new world of possibilities.

For example, a retailer using AI at work might:

• Predict demand patterns to optimize pricing and profitability
• Avoid overstocking or stockout by analyzing customer preferences to keep the right products on the shelves at the right time
• Enhance customer satisfaction by anticipating demand and providing personalized experiences[LF1] tailored to their preferences

This is more accessible with natural language queries or search capabilities allowing users to individually access data and analytics. They don’t need to understand the “semantic layer” or “knowledge graph” or “data modeling.” With little or no training, the end user can ask questions of the AI tool using natural language and get responses back in a form they understand.

By removing the dependency on IT or data professionals, organizations can share information more easily throughout the organization. This in turn reduces backlog and frees these business resources up for more valuable tasks, such as business intelligence or data monetization.

Make AI work

Traditional AI has proven difficult for most organization to tackle without help. Ventana Research found, “Two-thirds of organizations (65%) don’t have the skills they need to successfully apply AI.”

Addressing skills shortage

A key challenge businesses face is that there is a shortage of highly skilled data scientists who can develop and apply AI models. Current data professionals may have the skills to develop traditional AI-based analyses but lack the resources to make the outputs of their models available as data points for use in business intelligence analytics.

Despite concerns that GenAI may replace human expertise in many creative as well as problem-solving jobs, the labor market for several data-related occupations is expected to grow faster than average through 2031 (per the Bureau of Labor Statistics (BLS). In fact, data scientists have the “fastest employment growth” at 36 percent). It is because of insufficient resources, many business are left scrambling to figure out how to bring GenAI into their organizations now.

Safety in governance

Another challenge? Governing AI takes discipline; it’s essential to creating trust in data modeling. Yet, Ventana Research found only one-quarter of organizations (23%) have governance policies in place for AI.

AI results are shaped by the accuracy and validity of the data inputs. Still, organizations that have to document how data-driven decisions are made face difficulties preserving the data models used even as the AI models require regular updating to ensure quality.

In light of these challenges, many businesses can benefit from a single-product analytics platform, such as MicroStrategy ONE, which has one integrated codebase built from the ground up. This supports a more comprehensive capability for governance and compliance as well as leads to more stable code with fewer software bugs.

Putting GenAI in the hands of your users

GenAI also enables software vendors to improve productivity with, and accessibility to, various capabilities that make their products easier to use. With large language models (LLM) transforming vast amounts of data into insights accessible even to those without data science expertise, businesses can see more productivity and empower more innovation.

MicroStrategy has paired LLM-powered AI with business intelligence to offer more business value than ever before. MicroStrategy ONE is a trusted and open platform that provides every employee data-enhanced insights.

To learn more about bringing AI into your organization and how to enhance business intelligence with it, read the full Ventana eBook “Revolutionize Your Analytics with AI.”