Executive Summary

GenAI Analytics

For decades, enterprises have focused on using analytics and data software—or business intelligence—to improve operations. Software providers have made dramatic improvements in BI products by incorporating highly interactive visualizations and the ability to quickly process and display very large volumes of data. However, the quest to make analytics accessible to more of the workforce has led to generative artificial intelligence, applying it to all aspects of data analytics software to make the products easier to use. ISG Market Lens research shows that 87% of participants are AI-enabling analytics and BI applications.

ISG Research defines GenAI Analytics as the use of generative AI and other AI and machine learning techniques to enhance analytics processes. It includes providing conversational interfaces, recommending data preparation steps, suggesting visualizations of data and documenting analytics processes. It also includes using AI/ML to provide automated insights and natural language generation.

Adopting AI/ML has proven more complicated than many had expected. Ideally, BI software products would have full AI/ML capabilities. That has not happened, and AI/ML functions remain independent of BI software. AI/ML requires skills beyond the reach of many analysts, and organizations have had difficulty finding skilled resources. As a result, we expect through 2026, three-quarters of organizations will maintain multiple, separate skill sets.

Faced with this separation, BI software providers have invested in making AI/ML more accessible by augmenting the products’ capabilities. With the advent of GenAI, elements of AI/ML are more easily incorporated into analytics experiences. For example, AI/ML can drive automated insights to identify and explain relationships in the data as well as recommend actions to take. One of the most common and beneficial uses of GenAI is natural language processing to support conversational analytics with natural language queries and narrative responses. Creating ML models is made more efficient by automated machine learning, making more sophisticated analytics—such as customer segmentation using clustering techniques—accessible to more individuals. And GenAI can be applied to many tasks in analytics and data processes to make those tasks easier to design and perform.

In addition to conversational analytics, one of the greatest opportunities for GenAI is to assist with data preparation. Data preparation continues to be where organizations spend the most time in analytics processes. GenAI can be used to suggest which data tables to combine and how to combine those tables. It can automatically construct a logical data model from a physical data model. AI/ML can augment data quality processes, identifying outliers and anomalies in the data, even recommending potential corrections for those data points.

While efforts to apply AI/ML have been underway for some time, the sudden explosion of GenAI capabilities has fueled more interest in how to augment BI. GenAI is also being used to generate SQL to access data sources, and, in some cases, GenAI produces documentation of data pipelines used in analytics processes, enhancing the understanding and lineage of the data. In some ways, it is the Wild West, with providers racing to outdo each other in the application of GenAI. The technology holds much promise, and we expect it will have a significant impact on the analytics market, but it is still early days.

GenAI analytics will continue to evolve. Many features are still under development or in pre-release mode. GenAI is making conversational analytics more common and more capable than it is today. It will enable better support for multilingual capabilities currently lacking in most analytics products and likely lead to increased automation in data preparation processes and in creating initial analyses, making analysts much more productive.

More products will also offer AutoML capabilities. Among the software providers we evaluated, AutoML is most often used to generate forecasts and perform customer segmentation analyses. Over time, AutoML capabilities will expand to support more types of analyses and produce models with improved accuracy. The exact intersection between AutoML in GenAI analytics products and the models produced from more sophisticated AI/ML products remains to be seen. Today, some GenAI analytics products can work with these models, but it is still a loosely coupled process.

Enterprises should be aware of the changes going on in the market. Understand the capabilities and compare current software with what other providers have available. In evaluating GenAI analytics, one must consider the underlying analytics capabilities. GenAI can only do so much if the foundation of underlying analytics is weak. Consequently, this Buyers Guide combines an assessment of GenAI analytics capabilities with core analytics capabilities to determine the provider’s overall rankings. Organizations can then use this report to help guide purchasing decisions but also to guide conversations with software providers about the roadmap for GenAI analytics. The market is still evolving rapidly, but organizations can realize value today that will improve analytics processes.

The ISG Buyers Guide™ for Generative AI Analytics evaluates software providers and products in the three key areas of data, analytics and communications. It includes a wide variety of the criteria used in our Overall Analytics and Data Buyers Guide but places emphasis on assistance and automation in data and analytics processes.

This research evaluates the following analytics and data software providers that offer products that include key elements of GenAI analytics as we define it: Alibaba Cloud, Amazon Web Services, Cloud Software Group, Domo, GoodData, Google Cloud, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Qlik, SAP, SAS, Sisense, Salesforce (Tableau), ThoughtSpot and Zoho.

Buyers Guide Overview

For over two decades, ISG Research has conducted market research in a spectrum of areas across business applications, tools and technologies. We have designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of the business requirements in any enterprise. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research undertaking contribute to our comprehensive approach to rating software providers in a manner that is based on the assessments completed by an enterprise.

The ISG Buyers Guide™ for GenAI Analytics is the distillation of over a year of market and product research efforts. It is an assessment of how well software providers’ offerings address enterprises’ requirements for GenAI analytics software. The index is structured to support a request for information (RFI) that could be used in the request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. An effective product and customer experience with a provider can ensure the best long-term relationship and value achieved from a resource and financial investment.

In this Buyers Guide, ISG Research evaluates the software in seven key categories that are weighted to reflect buyers’ needs based on our expertise and research. Five are product-experience related: Adaptability, Capability, Manageability, Reliability, and Usability. In addition, we consider two customer-experience categories: Validation, and Total Cost of Ownership/Return on Investment (TCO/ROI). To assess functionality, one of the components of Capability, we applied the ISG Research Value Index methodology and blueprint, which links the personas and processes for GenAI analytics to an enterprise’s requirements.

The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of GenAI analytics technology can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its full performance potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on a short list of software providers that does not represent a best fit for your enterprise.

ISG Research believes that an objective review of software providers and products is a critical business strategy for the adoption and implementation of GenAI analytics software and applications. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating GenAI analytics systems and tools and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.

How To Use This Buyers Guide

Evaluating Software Providers: The Process

We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes.

1. Define the business case and goals.
   Define the mission and business case for investment and the expected outcomes from your organizational and technology efforts. 
2. Specify the business needs.
   Defining the business requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
3. Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the organization from executives to front line workers and determine the needs of each. 
4. Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan. 
5. Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your organization’s requirements. 
6. Establish technology vendor evaluation criteria.
Utilize the product experience: Adaptability, Capability, Manageability, Reliability and Usability, and the customer experience in TCO/ROI and Validation. 
7. Evaluate and select the technology properly.
Weight the categories in the technology evaluation criteria to reflect your organization’s priorities to determine the short list of vendors and products.
8. Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources. 

The Findings

All of the products we evaluated are feature-rich, but not all the capabilities offered by a software provider are equally valuable to types of workers or support everything needed to manage products on a continuous basis. Moreover, the existence of too many capabilities may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a larger number of features in the product is a plus, especially if some of them match your enterprise’s established practices or support an initiative that is driving the purchase of new software.

Factors beyond features and functions or software provider assessments may become a deciding factor. For example, an enterprise may face budget constraints such that the TCO evaluation can tip the balance to one provider or another. This is where the Value Index methodology and the appropriate category weighting can be applied to determine the best fit of software providers and products to your specific needs.

Overall Scoring of Software Providers Across Categories

The research finds Oracle atop the list, followed by SAP and Domo. Providers that place in the top three of a category earn the designation of Leader. Oracle has done so in five categories, Amazon Web Services in one, Domo in one, Google in one, IBM in one, Microsoft in four, MicroStrategy in one, Qlik in one, SAP in five and Zoho in one category.

The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have a higher weighted performance to the axis in aggregate of the five product categories place farther to the right, while the performance and weighting for the two Customer Experience categories determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.

The research places software providers into one of four overall categories: Assurance, Exemplary, Merit or Innovative. This representation classifies providers’ overall weighted performance.

Exemplary: The categorization and placement of software providers in Exemplary (upper right) represent those that performed the best in meeting the overall Product and Customer Experience requirements. The providers rated Exemplary are: Domo, IBM, Microsoft, MicroStrategy, Oracle, Qlik, Salesforce, SAP, ThoughtSpot and Zoho.

Innovative: The categorization and placement of software providers in Innovative (lower right) represent those that performed the best in meeting the overall Product Experience requirements but did not achieve the highest levels of requirements in Customer Experience. The provider rated Innovative is: AWS.

Assurance: The categorization and placement of software providers in Assurance (upper left) represent those that achieved the highest levels in the overall Customer Experience requirements but did not achieve the highest levels of Product Experience. The provider rated Assurance is Infor.

Merit: The categorization of software providers in Merit (lower left) represents those that did not exceed the median of performance in Customer or Product Experience or surpass the threshold for the other three categories. The providers rated Merit are: Alibaba Cloud, Cloud Software Group, GoodData, Google, Idera, Incorta, insightsoftware, SAS and Sisense.

We warn that close provider placement proximity should not be taken to imply that the packages evaluated are functionally identical or equally well suited for use by every enterprise or for a specific process. Although there is a high degree of commonality in how enterprises handle GenAI analytics, there are many idiosyncrasies and differences in how they do these functions that can make one software provider’s offering a better fit than another’s for a particular enterprise’s needs.

We advise enterprises to assess and evaluate software providers based on organizational requirements and use this research as a supplement to internal evaluation of a provider and products.

Product Experience

The process of researching products to address an enterprise’s needs should be comprehensive. Our Value Index methodology examines Product Experience and how it aligns with an enterprise’s life cycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future, which are flawed since they do not represent an enterprise’s requirements but how the provider operates. As more software providers orient to a complete product experience, evaluations will be more robust.

The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Usability (15%), Capability (50%), Reliability (5%), Adaptability (5%) and Manageability (5%). This weighting impacted the resulting overall ratings in this research. Oracle, Domo and SAP were designated Product Experience Leaders.

Customer Experience

The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The advancement of the Customer Experience and the entire life cycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. Technology providers that have chief customer officers are more likely to have greater investments in the customer relationship and focus more on their success. These leaders also need to take responsibility for ensuring this commitment is made abundantly clear on the website and in the buying process and customer journey.

The research results in Customer Experience are ranked at 20%, or one-fifth, using the specific underlying weighted category performance as it relates to the framework of commitment and value to the software provider-customer relationship. The two evaluation categories are Validation (10%) and TCO/ROI (10%), which are weighted to represent their importance to the overall research.

The software providers that evaluated the highest overall in the aggregated and weighted Customer Experience categories are Oracle, SAP and IBM. These category leaders best communicate commitment and dedication to customer needs. While not Leaders, Domo and Microsoft were also found to meet a broad range of enterprise customer experience requirements.

Software providers that did not perform well in this category were unable to provide sufficient customer case studies to demonstrate success or articulate their commitment to customer experience and an enterprise’s journey. The selection of a software provider means a continuous investment by the enterprise, so a holistic evaluation must include examination of how they support their customer experience.

Appendix: Software Provider Inclusion

For inclusion in the ISG Buyers Guide™ for GenAI Analytics in 2024, a software provider must be in good standing financially and ethically, have more than 50 dedicated workers, at least $50 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents and have at least 100 customers. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the past 12 months. The product must be actively marketed as an analytics product that includes generative AI and machine learning capabilities to support the analytics processes within an organization, including assisting with data access and preparation, automated analyses and insights, and natural language query or chat interfaces.

The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.

All software providers that offer relevant GenAI analytics products and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.

Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.

Products Evaluated

Providers of Promise

We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”