June 19th, 2025
Ask AI: Conversations That Turn Data into Insight
By Simon Avila · 5 min read
Consider what AI can do for your data analysis. As your business grows, you'll need to rely on advanced analytics to give you actionable insights and drive informed decision-making. The global conversational AI market size was estimated at USD 11.58 billion in 2024 and is projected to reach USD 41.39 billion by 2030, growing at a CAGR of 23.7% from 2025 to 2030 [1].
Combining data analytics tools with AI can open up a world of possibilities that will allow you to enhance your data exploration and empower your end-users to find the most value in the data. AI tools combined with data analysis can help your teams explore data more naturally, having a conversation and asking questions to help find answers.
Many AI tools will empower your data analysis. Knowing which to choose can mean a lot of research, time, and testing to see what will work for your business. We're giving you a head start by reviewing some of the top tools and features, from predictive analytics to natural language processing, so you can choose what will work best for you and your data.
Whether you're a small startup or a multinational corporation, these tools are essential for your data and to give you a competitive edge. Let's dive into what you should look for from the top nine AI tools for data analysis in 2025.
How to Use AI for Data Analysis
Want to know how you can use AI tools to help analyze data? The good news is that there are a lot of possibilities. While your data is full of rich insights and information your company can take immediate action on, it can sometimes be a time-consuming and tool-intensive process to get everything possible out of the data.
Utilizing AI tools to analyze data allows organizations to sift through massive amounts of data faster and discover insights more naturally and intuitively. Even the most advanced data intelligence platforms use AI tools to enhance user experiences, surface more insights, and ensure users find answers to their business questions.
Here are some ways AI can help you harness even more data analysis power:
• Predictive analytics: You can use AI algorithms to analyze historical data and forecast future trends, enabling your business to anticipate market shifts, customer behavior, and operational needs.
• Prescriptive analytics: By combining AI with optimization algorithms, your team can determine the best course of action to achieve your business goals through optimizing resources and maximizing efficiency.
• Anomaly detection: Use AI algorithms to identify outliers within your datasets. This will flag potential errors, fraud, or emerging patterns that require attention.
• Natural Language Processing (NLP): NLP is the leading technology segment in the market, enabling AI systems to interpret, understand, and respond to human language effectively. NLP's ability to process both text and speech enhances conversational AI applications across industries, ensuring seamless and context-aware interactions [2].
• Image and video analysis: Use AI algorithms to analyze images and videos and extract valuable insights, like object recognition, sentiment analysis, and demographic profiling, then categorize your media files for further analysis.
• Time series forecasting: AI models can analyze sequential data points over time to forecast future trends and patterns, aiding in inventory management, resource planning, and financial forecasting.
• Automated data preparation: AI streamlines data cleaning, transformation, and integration processes, accelerating data preparation tasks and ensuring quality data for analysis.
Best 9 AI Tools to Analyze Data
Now that you're thinking about how you can use AI tools to analyze data, let's look at the top tools on the market in 2025 and how they can help your business grow. Here is an overview of the tools and pros and cons to consider when deciding what will work best for you.
1. Julius AI
Julius is a conversational AI data analysis platform that enables users to analyze, visualize, and manipulate data through natural language interactions. Julius is a powerful AI data analyst that helps you analyze and visualize your data. Chat with your data, create graphs, build forecasting models, and more. The platform allows users to upload files and receive expert-level insights without requiring programming knowledge.
• Julius AI is designed to be intuitive and user-friendly, reducing the learning curve significantly. Even individuals without a background in data science or statistics can start analyzing their data with ease. Additionally, the platform offers a question-driven analysis feature, where users can simply ask questions to get the insights they need [3].
• One of Julius AI's most valuable features is its ability to perform complex statistical tests without requiring users to write code or understand statistical programming. Julius knows which statistical tests are appropriate for your data and research questions, then performs these tests automatically.
• Julius AI supports various data formats and sources, making it easy to bring your information into the platform for analysis.
• Built for knowledge workers who need immediate access to sophisticated analysis
• Requires subscription for advanced features beyond the basic plan
• Newer platform with a smaller user community compared to established tools
2. Domo
Domo is an end-to-end data platform that supports cleaning, modifying, and loading data to build customizable data apps. This comprehensive suite has an AI service layer that helps users deliver data in a more streamlined way and guides users to insights through AI-enhanced data exploration.
• AI-enhanced tools across every aspect of the data journey
• Intuitive interface for data exploration and AI model management
• Built-in analytics and governance to ensure responsible AI deployment
• Utilizes AI to support comprehensive data governance and security
• Large, active user community
• As an end-to-end data platform, it can be more feature-heavy than some businesses need
• The cost may be high for businesses looking only for data analysis
3. Microsoft Power BI
For users already well-integrated with the Microsoft Office suite, Power BI integrates well with current applications and ensures seamless AI integration across tools. Native integrations like Azure Machine Learning with Excel allow users to work within their current applications seamlessly.
• User-friendly interface, especially for those already familiar with Microsoft products
• Integration with the Microsoft Office suite of applications
• Scales to handle large data sets
• Can become costly with premium features
• Learning curve for advanced functionalities, including AI tools
• Integration with non-Microsoft data may require additional tools and steps
4. Tableau
Tableau is one of the leading business intelligence platforms in the market. Tableau uses AI to give users more intuitive and natural paths for finding answers and insights within their data. Tableau's AI capabilities, including Tableau GPT and Tableau Pulse, enhance data analysis and preparation by leveraging advanced AI models.
• Advanced visualizations with an intuitive drag-and-drop interface
• Feature-rich with AI tools across the product
• Seamlessly integrates with Salesforce data
• High cost for enterprise versions
• Can still require a steep learning curve for new users
• AI tools only offer limited customization
5. Qlik
The 2025 Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms names Qlik a Leader for the 15th year in a row [4]. Qlik offers robust analytics through its associative data model and provides AI-enhanced capabilities for data exploration.
• Associative data model for flexible data exploration
• Allows data users to embed data in external applications• Empower people at all skill levels with AI-powered insights and predictions that inform intelligent action when it matters most [4]
• Offers a comparatively lower AI feature set than some competitors
• Higher cost relative to AI capabilities offered
• Steeper learning curve
6. IBM Cognos Analytics
The AI Assistant available in IBM Cognos Analytics answers users' questions about their data in natural language, generating visualizations and dashboards on demand [5]. With IBM Watson Analytics, it offers automated pattern detection and advanced analytics capabilities.
• The vendor has incorporated NLQ, automated insights, and intent-driven modeling and has invested in automation and ML capabilities across data modeling, dashboards, data exploration, and an analytics chat assistant. The Cognos Analytics assistant allows users to explore data by asking natural language questions [6]
• Integrates with IBM tools and IBM Watson ecosystem
• Built-in AI-infused insights, predictive forecasting, and data exploration capabilities [7]
• Complex interface with a steep learning curve
• Can be prohibitively expensive for small to mid-sized companies
• Limited AI customization compared to specialized platforms
7. AnswerRocket
Founded in 2013, AnswerRocket is an augmented analytics platform for data exploration, analysis, and insights discovery. It allows users to monitor key metrics, identify performance drivers, and detect critical issues within seconds [8]. It focuses on allowing business users to ask questions in natural language and leveraging AI to provide rapid insights.
• Easy data exploration: Effortlessly ask natural language questions and receive instant insights tailored to your data, such as metric drivers, trends, and outliers [9]
• Quick insights and report generation
• Good AI-driven analytics capabilities
• Suitable for business users without technical expertise
• Lacks advanced features compared to more established tools
• Integration options can be restrictive
• Smaller user community and support resources
8. Bardeen.ai
Bardeen is an automation and workflow platform designed to help GTM teams eliminate manual tasks and streamline processes. It connects and integrates with your favorite tools, enabling you to automate repetitive workflows, manage data across systems, and enhance collaboration [10]. It focuses on automating repetitive tasks and data workflows using AI.
• Automate data processing tasks: Bardeen can help you automate data processing tasks such as extracting data from websites and documents, cleaning and organizing data, and creating reports [11]
• Easy to integrate with popular apps and tools
• Focused on automating repetitive tasks
• No coding required
• Limited to workflow automation rather than deep analytics
• Fewer data visualization and analysis features
• Templates lack customization features
9. Talend
Talend Data Fabric offers a scalable, cloud-independent data fabric that supports the full data lifecycle, from integration and quality to observability and governance [12]. With ready-to-use machine learning components, it's a data platform that can help users integrate AI algorithms with their data efficiently.
• Excellent data integration and management tools
• Talend natively supports Hadoop, Spark, Hive, and other big data platforms. Whether you're batch-processing TBs of data or doing real-time ingestion into Kafka streams, Talend has built-in connectors and frameworks that reduce friction [13]
• Limited AI feature set compared to specialized analysis tools
• Can be complex to set up and configure
• Limited direct visualization and analytics capabilities
• Requires technical expertise to fully utilize AI features
Conclusion
The potential of AI in data analysis continues to revolutionize how organizations derive insights from their data. From predictive and prescriptive analytics to natural language processing, these tools equip businesses—from startups to multinational corporations—with the capabilities needed to make informed decisions and drive growth.
The integration of conversational AI into data analysis represents a fundamental shift toward more accessible, intuitive analytics. Generative AI chatbots help users manage and analyze information to extract valuable insights. They can be leveraged for tasks such as database querying, content summarization, and report generation [14].
By understanding the unique features and benefits of each tool, you can select the best fit for your organization, ensuring that your data analysis processes are efficient, insightful, and aligned with your strategic goals. The democratization of advanced analytics through conversational interfaces means that sophisticated data analysis is no longer limited to technical specialists.
Ready to experience the future of conversational data analysis?
Julius makes advanced analytics accessible to everyone in your organization through natural language interaction. Transform your approach to data insights and discover how intuitive analysis can accelerate your business success.
Start your journey toward more accessible, powerful data analytics today by using Julius AI.
