Artificial Intelligence (AI) is the talk of the town, so it’s no surprise the newest wave of business intelligence (BI) solutions are harnessing this technology. In fact, our recent survey with MIT SMR Connections shows that 67% of leaders are using GenAI for data and analytics. Even better, they are seeing results: differentiation, revenue growth, and increased customer engagement just to name a few.
But what exactly can AI in BI can achieve and, more importantly, how can it drive outcomes for your business? Below, we’ve listed some of the top ways leaders are sparking their data renaissance with AI and how you can do the same for your business.
Table of contents:
We know BI is the use of technology to analyze and transform data into actionable insights. It usually includes leveraging BI tools to handle tasks like data collection, analysis, visualization, and interpretation. However, as the volume and complexity of data increases, businesses often struggle to uncover patterns, trends, or insights within their data. That’s where AI comes into play.
With AI-powered BI solutions, you take your analytical capabilities one step further. These solutions can sift through large datasets in real-time and identify patterns, correlations, and anomalies. Powerful capabilities like natural language processing (NLP), machine learning (ML), and deep learning can help you create powerful data models to predict outcomes or uncover hidden insights. Let’s look at some of the ways where AI-powered solutions are enabling end users to understand their business better and not just query their data:
1. Empowering self-service analytics
Earlier, non-technical users often faced lengthy delays in decision-making—sometimes waiting weeks or months—because they relied on reports from their data teams. When time is money, it’s beneficial to empower business users to quickly get the data insights they need so they can make timely, informed decisions. And this is why self-service analytics is crucial.
Here’s what David Stodder, former Senior Director of Research for BI at TDWI, says on the matter: “Self-service is a priority because it breaks [users] off from being completely dependent on IT and IT developers.”
He adds that data democratization entails adopting AI analytics tools that are more personalized to users’ needs in terms of search, analysis, and visualization.
Now with AI-Powered Analytics solutions like ThoughtSpot, business users can query data the same way they’d search for information on their favorite search engine. Here’s one real-life example of self-service analytics in action: Using ThoughtSpot’s natural language search, Wellthy’s care team could visualize real-time patient data, filter and drill into specific searches, and segment members based on their specific needs—without relying on their data teams. Thanks to ThoughtSpot, even Wellthy’s data teams felt liberated to work on high-value initiatives, saving the company over $200k by increasing analyst efficiency.
💡Pro tip: If you haven’t already launched a data fluency and AI training program, do so now. Create customized learning programs that help users understand how to work with their new BI tools and drive their own strategic decisions.
2. Crafting better data narratives
When you’re making strategic business decisions, you’ll need to be able to zoom in and out of your data to get a complete picture. With modern AI-powered dashboard solutions like ThoughtSpot, organizations are no longer stuck analyzing past data. They can monitor KPI changes in real-time, predict future trends, and uncover unusual patterns—all with just a few clicks. Armed with this information, you can craft compelling data stories, ensuring you can communicate important insights to all stakeholders.
For instance, instead of presenting just a static chart showcasing your sales performance, you can create interactive dashboards that allow you to drill down into specific data points, compare past and present performance, and highlight important trends. Such narratives can significantly enhance decision-making, offering stakeholders a clearer view of potential improvements and challenges.
💡Pro tip: Ask yourself, does your current BI tool allow you to tailor your visualizations? Does it support drill-anywhere visualizations that help you explore specific data points, categories, and time periods? If the answer is no, it’s time to invest in other tools.
3. Augmented intelligence: Less plumbing, faster insights
Finding the "aha!" moments in your data requires a lot of manual plumbing and processing. It is vital to consistently ensure the data you feed into your analytics systems is readily accessible, clean, and reliable. However, such activities can take up half the time of your data team, shifting their focus away from value-added activities.
Luckily, with the emergence of cloud computing and GenAI, analysts can create a single source of truth and democratize analytics for all. The entire process of data transformation and even data modeling can be made easier and faster with AI. However, human oversight remains crucial.
That’s why adopting the right augmented intelligence solution matters. For instance, ThoughtSpot was the first to ride the AI wave back in the year 2023 and is now recognized as a leader in the 2024 Gartner MQ for Analytics and BI. What sets ThoughtSpot apart is its promise to offer enterprise-grade accuracy and governance. As a matter of fact, customers report up to 95% accuracy when using ThoughtSpot Spotter compared to GPT alone. This level of accuracy and precision is possible because of advanced human-in-the-loop feedback controls that allow you to improve LLM outputs.
💡Pro tip: Prioritize BI solutions that allow for a human-in-the-loop feedback feature so your AI model can provide accurate, business-specific answers.
4. Paving the way for advanced analytics
Of all the emergent benefits of AI in BI, predicting outcomes is perhaps the most intriguing. By leveraging ML algorithms and advanced data modeling techniques, AI can help you build complex predictive models that create forecasts or provide recommendations based on historical data.
For instance, AI in business analytics can help retailors predict inventory needs based on past purchasing behaviors and seasonal trends. Similarly, healthcare providers can forecast patient admission rates by analyzing historical patient data. This ability allows organizations to meet future demands and innovate new offerings, giving them a competitive edge.
💡Pro tip: While predictive analytics is certainly exciting, implement a risk mitigation plan to reduce the chances of data hallucinations and biases.
AI in BI is being applied across a wide range of industries and business functions. Here are a few examples of how organizations are using AI to drive significant outcomes for their businesses:
Customer-focused: AI algorithms can help your marketing, sales, and customer service teams analyze historical customer data, sales trends, and other relevant factors for segmentation, churn prediction, and personalization.
Person-focused: AI-powered analytics can help your operations and customer-support teams manage client and patient-centric challenges such as predicting clinical-support needs, managing patient risk, and enhancing customer retention strategies.
Operations focused: By analyzing sensor data and identifying patterns that indicate potential equipment failures, AI algorithms can detect machinery malfunctions ahead of time, helping teams optimize performance, reduce downtime, and save costs.
Risk and fraud focused: Finance and risk management teams can use AI-powered analytics to analyze transactions, identify suspicious patterns, and flag potentially fraudulent activities in real-time.
Supply chain focused: AI-enabled BI solutions can quickly detect anomalies or outliers in supply-chain data, helping procurement leaders detect bottlenecks and anticipate delivery issues before they disrupt production timelines.
While the race to the “AI gold rush” rages on, it is important not to get distracted by flashy BI solutions. Researching and gaining hands-on experience with different GenAI products is crucial to understanding trust, accuracy, and cost trade-offs.
Even though ThoughtSpot stands out as a true leader among legacy BI solutions, we still encourage you to take an interactive product tour. This firsthand experience will demonstrate how ThoughtSpot can turn data into insights and drive meaningful outcomes across your business.
