The narrative around AI analytics is that it’s a seismic shift—a groundbreaking force that can catapult anyone from data uncertainty to actionable confidence. Think about it: Natural language search putting the power of data exploration in everyone's hands, and an even bigger leap—agentic AI, delivering context-rich guidance right when it’s needed the most. It’s a vision that promises endless possibilities.
However, as a data leader, you know the reality isn’t quite as picture-perfect. While these capabilities are undeniably impressive, they come with a caveat. Without the right tools and clear use cases, you’re not adding value—you’re simply creating another pile of technical debt. In fact, Accenture research reveals that 41% of executives identify AI as the highest contributor to tech debt.
So, here’s the big question: How do you find the right AI analytics tools for your business? One that aligns expectations with outcomes? Let this article be your guide.
Table of contents:
When the GenAI wave began in early 2023, ThoughtSpot was the first to announce and launch an AI-Powered Analytics experience. As leaders in BI, ThoughtSpot empowers users with a trusted, enterprise-grade AI that makes it easy for everyone to explore data from any angle, all in real-time.
With ThoughtSpot’s AI-powered BI, you’re not just viewing data—you’re interacting with it. Ask questions, get automated insights, perform complex analyses, and drill endlessly into real-time visualizations. You also have granular security controls with an advanced human-in-loop system that allows you to limit biases for accurate results and improved performance.
Core features
AI Agents: With Spotter as your AI Analyst, insights are accessible to everyone—not just experts. No matter how complex your dataset is, you can ask complex questions in natural language and immediately get AI insights to identify the places where you can make the most impact. From comparisons to cohort analysis, you can truly understand how your data changes, but more importantly, why it changes.
AI Augmented Dashboards: While traditional dashboards are static and limiting, ThoughtSpot’s AI-augmented dashboards provide automated, real-time insights that respond instantly to the needs of anyone across your business. You can drill down from high-level analytics to the most granular insights without the need for pre-defining drill paths.
Actionable Analytics: ThoughtSpot offers real-time, actionable intelligence that goes beyond surface-level analysis. With powerful capabilities like AI Highlights, proactive KPI monitoring, predictive insights, and workflow automation, you can gain quick clarity on key trends and performance indicators, driving smarter, faster decision-making.
Analyst Studio: And don’t worry, we haven’t forgotten about your data teams. With Analyst Studio, they have all the power tools needed to prepare data for AI and move effortlessly between quick ad hoc analysis and advanced analytics. They can easily connect data from multiple cloud data warehouses, prep it, or leverage Python & R notebooks to create sophisticated data models. This powerful suite of analyst capabilities creates a collaborative creator space for faster time-to-insight.
ThoughtSpot pros
The self-service analytics experience makes data exploration and analysis intuitive for everyone, even those without a technical background.
Leverage a suite of AI capabilities to perform a wide range of data analyses.
Offers the flexibility to work with multiple LLMs and data sources.
ThoughtSpot cons
For exploring advanced analytics features, business users may require additional training.
Pricing
ThoughtSpot offers flexible pricing models designed to meet the unique needs of different businesses and enterprises. Here’s a quick breakdown of each plan:
The Essential plan—starts at $1250 /month: Designed for small data teams and businesses who want to share AI-powered insights and drive smarter decisions.
The Pro plan—custom pricing: Helps growing businesses bring the power of AI analytics to their business users.
The Enterprise plan—custom pricing: Ideal for enterprises who want to scale their analytics capabilities across the organization.
IBM's Cognos Analytics is an AI tool for data analysis that supports AI-assisted data preparation, statistical modeling, and predictive analytics. Analysts can connect and clean their data from multiple sources, create reports, and use machine learning to build time series models. To make exploration easier, the platform also has ‘Ask the Cognos Analytics’, an AI assistant that helps you create a real-time dashboard and share insights.
That said, it’s not without its challenges. While Cognos scores well in reporting and visualization, industry reports highlight performance bottlenecks during data prep. These slowdowns can keep data leaders from building new pipelines and capitalizing on opportunities quickly.
Core features
Data visualization and reporting: Create interactive visualizations and leverage reporting capabilities for further analysis.
AI-powered insights: IBM’s AI assistant provides automated insights that highlight key trends and patterns in the data.
Data modeling: Leverage machine learning to build models that structure data for deeper analysis.
Integration with cloud data sources: Combine data from multiple sources, including cloud databases and spreadsheets.
IBM Cognos Analytics pros
The drag-and-drop interface helps users visualize, analyze, and explore their data.
Users can customize their reports and dashboards with different types of charts, graphs, and tables.
IBM Cognos Analytics cons
Subscription costs for add-ons and advanced features can quickly add up, especially with advanced reporting features.
The platform struggles with larger datasets or complex queries, making it less suitable for high-demand environments.
Pricing
Cognos Analytics offers two main pricing tiers, but ultimately pricing depends on number of users, feature access, and deployment options.
The Standard plan—$10.60 per authorized user: This individual plan provides users access to the platform’s basic features. Users can create dashboards, leverage AI features, and share information.
The Premium plan—$42.40 per authorized user: This plan is designed for smaller teams, offering access to the Cognos Analytics basic plan plus Cognos enterprise reporting features.
30-day free trial available
MicroStrategy’s flagship AI data analytics tool, Strategy One allows you to connect to data warehouses, streamline workflows, build AI-powered dashboards, and share reports. It also has an AI assistant ‘Auto’ which delivers automated insights to help you stay on top of your KPIs.
Although the platform has introduced Generative AI capabilities, reports indicate its augmented analytics features fall short. This makes the platform less ideal for organizations seeking faster, more powerful AI-driven insights.
Core features
Interactive dashboards and reporting: Create customizable, real-time dashboards and reports to monitor business performance.
AI features: Gain automated insights into important trends and anomalies with a natural language interface.
Embedded analytics: Embed analytics into existing applications.
Mobile app availability: Access dashboards and reports from anywhere.
Microstrategy pros
MicroStrategy remains highly competitive in terms of its governance and reporting capabilities.
With features like Auto SQL and Semantic Graph, data teams can prepare and clean their data for advanced analysis.
Microstrategy cons
The platform can be complex to navigate, especially for users without technical backgrounds.
The tool may require significant computing resources, which can lead to performance issues if not properly managed.
Pricing
MicroStrategy offers a subscription-based licensing model, with costs varying significantly based on factors like deployment type (cloud or on-premises), data storage needs, enabled features, user roles, and the number of users. For the most accurate pricing tailored to your needs, it’s best to consult with their team directly.
30-day free trial available
Microsoft’s Power BI is an AI-powered data visualization tool that helps you visualize trends in data and perform complex analyses. The platform is designed to help organizations connect, visualize, and analyze data through a drag-and-drop interface. Plus, it has Copilot that allows users to ask questions in natural language and receive visualizations.
However, there’s a catch: Although Power BI is popular among technical data teams, it can be quite challenging for beginners to understand. The steep learning curve around its user interface makes it less accessible to business users and front-line decision-makers.
Core features
Custom-built visuals: Create visualizations and dashboards with pre-built templates.
Data modeling: Shape, clean, and define data relationships, and create measures with Power Query, Power Pivot, and DAX.
Connectivity with Microsoft ecosystem: Integrates with other Microsoft tools such as Azure, Excel, and SharePoint.
Real-time data analysis: Monitor metrics and performance indicators in real time.
Power BI pros
Power BI has a large community of active users, offering users a wealth of resources and tutorials.
Copilot for Power BI can help users accelerate the report creation process.
Power BI cons
Power BI service runs only in Azure. This limitation makes it difficult to connect with external databases or applications.
Reports show Power BI customers are facing challenges when it comes to enforcing data governance practices.
Pricing
Power BI offers various pricing models, so you can choose the plan that best fits your business—whether you're looking for basic analytics features or advanced AI tools:
Power BI free plan: Perfect for individual users, this plan gives you access to Power BI on your desktop, where you can create dashboards and reports.
Power BI Pro—$10.00 user/month: Best for small organizations with dedicated data teams, this plan allows users to create dashboards, generate KPI reports, and share insights across the organization.
Power BI Premium—$20.00 user/month: Tailored for mid-sized companies and enterprises, this plan lets you access larger model sizes and more frequent data refreshes.
Power BI Embedded—variable pricing: Ideal for organizations looking to embed Power BI’s capabilities into their applications.
💡Quick note: Power BI’s Copilot is only available to Premium license holders or specific Fabric licenses.
Free trial available
Qlik's data analytics platform uses AI to drive associative modeling and data discovery. It offers augmented analytics capabilities like automated insight generation, natural language interaction, AI-assisted data prep, and predictive analytics. Qlik also supports dashboard capabilities and advanced data exploration, but potential adopters should consider some key limitations. As the vendor loses market share year after year, customers are voicing their concerns about its limited Plus, it’s still unclear if the company can ramp up its AI capabilities fast enough to keep up with the market’s growing demands.
Core features
Multiple data integration connectors: Combines data from multiple sources like cloud databases and spreadsheets.
Real-time monitoring: Tracks data as it changes for the latest updates on business KPIs.
Predictive analytics: Use Qlik’s AutoML feature to create models, explore data, run experiments, and forecast trends.
Automated insights: Qlik’s AI-powered assistant offers instant insights into data.
Qlik pros
Qlik integrates with multiple cloud warehouses and databases.
Users have praised Qlik for its data monitoring and alerting features that deliver real-time notifications about KPI changes.
Qlik cons
For complex datasets, Qlik may require manual reloading or refreshing of data..
The pricing model for Qlik is confusing and can become prohibitively expensive as usage scales.
Pricing
Qlik has a subscription-based pricing model where the costs vary widely depending on which features you need and how you plan to use them. Even though there's a standard plan, getting all of Qlik’s features can be expensive, especially if your data consumption is high. It’s best to connect with their team for the best pricing estimate.
Free trial available
Joe Reis, renowned author and data expert said in an episode of ‘The Data Chief’: “When it comes to adopting AI in the organization there’s a lot of pressure from the top down. Ultimately, understanding what that means to your organization should be table stakes.”
Without a clear, orchestrated roadmap about how, where, and when you are going to invest and implement your AI analytics tech stack, you’re not just wasting valuable resources, you’re creating more user frustrations and backlogs. But don’t worry! Here are a few actionable steps to make your selection and implementation process easier:
1. Know what AI analytics means for your business and users
AI analytics can mean different things for different users. For instance, business users could use it for instant visualizations, and power users like analysts can leverage it to identify hidden trends and shape raw data into meaningful data stories. When you assess users’ needs, you have better clarity about functionalities important to them and set realistic expectations.
2. Prioritize vendors with demonstrated use cases
Most AI analytics tools in the market are still in the production stage and don’t have much documentation about real-life use cases. This can be misleading, as many tools promise a lot but fail to deliver the capabilities needed to support that vision.
Choose a data analytics tool with in-depth documentation, resources, and training materials. It’s important to not just read about the tool but also get hands-on experience with different Gen AI products to understand trust, accuracy, and cost trade-offs. You may also find it useful to check user reviews from reputable sources and read industry reports for up-to-date information about the platform's performance.
3. Give precedence to the human-in-the-loop element
Everyone wants instant insights from their AI tool, but it doesn’t always get it right. From well-documented cases of hallucinations to biased results, trusting AI blindly with your business data can lead to misinformed decisions—or worse, loss of trust. That’s why having a human-in-the-loop feedback system is important. It helps in curbing biases and building transparency, making sure your data is accurately represented when queried.
Going from legacy BI to AI-powered analytics is a journey; your success won’t happen overnight. But with the right tools and an established AI partner, you'll hit your goals faster. Just look at our MIT survey, which shows that 56% of early adopters have already exceeded their business goals by building the right partnerships at the right time. So, are you ready to go from 0 to 100 with GenAI?
With ThoughtSpot, you can deliver a GenAI analytics experience that’s purpose-built for everyone. Whether your team needs real-time insights or wants to predict trends for the next quarter, our AI-Powered Analytics puts users in the driver’s seat—delivering trusted insights, anywhere, at the speed of business.
Want to see this for yourself? Sign up for a ThoughtSpot demo and see how AI-Powered Analytics can bring your data to life.
