Given the growing importance of a data-driven approach to business, information-driven decisions and effective tools for data visualization are essential in today's world12. The AI-built data visualization tools of 2024 have further improved the rapidity, accuracy, and availability of needed insights for various business sectors34. Apply these tools, whether you are a data scientist, business analyst, or a marketing person, and you will be able to make your data vivid and accessible5. Here are some of the best AI visualization tools of 2024 that have different features to help you understand and communicate your data in creative ways67.

Tableau is a leading name in data visualization as it constantly innovates to stay competitive. Its AI engine uses predictive analytics and natural language processing to give users the power to create sophisticated visualizations with very little coding knowledge12. Its "Ask Data" feature allows its users to ask questions in plain language, with Tableau generating visualizations based on the responses3. Also, its Smart Data Discovery function helps users uncover patterns, outliers, and trends. This provides insights that might go unnoticed through manual analysis4. Tableau's predictive abilities give organizations the tools to forecast trends, helping them stay ahead of the decision-making curve5. These combined AI-driven features make Tableau ideal for companies that need customizable data visualizations plus extensive data-driven forecasts6.

We see that in integrations with Microsoft Power BI, which is a user-friendly, all-encompassing platform for data visualization. It comes with integrated AI features, including a package called AI Insights, which helps with analyzing data; it also provides pre-built models for use by clients without extensive programming backgrounds.12 The tool then automatically summarizes data insights to produce something called 'Power BI Smart Narratives', which is designed to free up more time for users, thus reducing report preparation time as well.3 One of the tools it offers is Cognitive Services for NLP, image recognition, and text analytics, providing users with easy visualizations of unstructured data.4 Its tools also provide AI Visualizations, including the Key Influencers tool, which is designed to help users recognize patterns and factors affecting key metrics.5 It offers a good option for users who also use Microsoft products in their workflow and want an ecosystem-integrated platform with a relatively easy learning curve for data interpretation.67

Google Looker features integrated tools that help to make the process of visualizing and creating business intelligence a simple and actionable task, particularly for the users of Google Cloud ecosystem. For the users of BigQuery ML, there's a Looker Block that helps with designing, training, and visualizing the machine-learning models within Google Looker itself, aiding in the analysis without leaving the platform12. For the users striving to check whether their datasets can be quickly analyzed using BigQuery ML automatically, there's the AutoML Tables feature that helps create custom metrics using large datasets. Also, you don't have to code everything manually – instead, you can copy the custom metric and send it back to BigQuery, which in the future will return the dataset using the given metric and without BigQuery ML3.

For the users of Google Looker who want to incorporate machine learning algorithms directly within their visualization workflow, or intend to define the table schema and the model with a data dictionary and structured dataset, Google Looker uses the modeling language called LookML4. Features such as aggregate functions and specialized table types like hierarchy and geography-specific tables help to simplify creating reports that incorporate nested data and help to present your industry-scaled data more simply via district, division, or branch5.

What makes Qlik Sense unique among other business intelligence (BI) platforms is its augmented intelligence. This allows individuals to search, associate, and visualize their data interactively. Its associative model means that users can find things that they might not expect to. It promotes intuitive searching and association that might not be possible when analyzing the same data in an SQL (Structured Query Language) database.12

Insight Advisor leverages AI to help users find the best insights and visualizations based on what the company says are your 'data inputs'. Qlik Sense also has natural language interaction that lets users type or speak questions that it responds to with insights. The platform has a machine learning component. Developers can add ML models directly into dashboards. The Qlik platform is currently used in about 44 percent of the Global 2000 listed on the Forbes website.34

DataRobot is an automated machine learning (AutoML) system with new features, released in early 2022, that enhance its data visualization capabilities. It is a tool for data scientists and business analysts who need to produce predictive models quickly. DataRobot automates the selection of machine learning models and displays the results with clear, interactive graphics. Model Interpretability provides tabular and graphic breakdowns of model effectiveness and shows prediction reliability. For users who want to produce predictive models but lack substantial experience in the field of machine learning, DataRobot is exceptional. Its core offering makes model creation faster than it would otherwise be. And by making it quick and easy to produce predictive models, it's also easier to communicate model output to non-technical stakeholders.123

Domo is a full-suite business intelligence including applications. Its AI helps the users automate insights for quick insights from data without convoluted analytics. Data Storytelling uses Domo's AI to display visualizations in narrative forms as a blend of visualization and storytelling. This helps in communicating insights easily for non-technical audiences.12 The Auto Insights feature of Domo helps identify patterns, anomalies, and trends in data analysis. Domo also provides alerts and notifications for data monitoring in real time. If any anomaly is found, Domo alerts the user about it. Its application is advantageous for businesses willing to democratize data so that its usage is not limited to business analysts. Domo helps businesses empower all users to make instant data-driven decisions.34

Powered by Zia, Zoho Analytics offers a comprehensive AI-driven experience, so you don't have to be a coding expert to identify valuable insights, forecast trends, and plausible anomalies simply by using a few clicks. AI assistant, Zia, ensures you have it all at your fingertips. With conversational AI, you can type questions such as 'What are the total receipts for New Zealand compared to last year?' and get visualizations on the fly12. Its anomaly detection capability scans for unusual patterns, while its forecasting capability helps to provide projections using historical data to help businesses take a more proactive approach34. Zoho Analytics is ideal for small to medium businesses or any organization and is great for teams that require quick answers to their business queries without being overwhelmed by complexities and the need for dedicated data experts25.

ThoughtSpot offers a search-driven analytics platform coupled with AI features for accelerating insight. With its search-driven analytical interface, you can type queries into the search bar to see associated visualizations being returned immediately. The tool is highly compatible with all major cloud data sources such as Snowflake, Google BigQuery, and Amazon Redshift, allowing you to scale without runtime issues for large datasets. ThoughtSpot is designed for the fast-paced retail, finance, and healthcare sectors where quick insights that don't require advanced technical skills can be crucial for generating the next actions.123

ThoughtSpot's AI-powered analytics platform, ThoughtSpot Sage, combines large language models (LLMs) with patented search technology to deliver trustworthy insights in natural language1. Users can ask business questions using plain language, and the system generates accurate SQL statements to execute on complex relational schemas1. The platform also offers AI-suggested searches to help users explore new data sources and learn how to use natural language search effectively4.

Deciding which AI data visualization tool one should go for in 2024 hugely depends on the type of data your organization works with, your tech proficiency as a team, and your budget. Enterprises already using Google Cloud or Microsoft Azure or Amazon Redshift can benefit from building things like Looker, Power BI, or Sisense into their existing environments12. Similarly, larger organizations with large datasets can benefit from Tableau, Looker, or Qlik Sense34. Smaller teams or organizations with a tighter budget might find Zoho Analytics or Power BI more accessible56. For predictive analytics, Tableau, DataRobot, or Sisense currently lead78. With better tools, data today gives teams the means to quickly uncover insights, build robust actions that bring benefits at scale, and even contribute to the implementation processes. With the right AI tool, data can become a business's secret sauce – the gateway to smarter decisions built around speed and scale.