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AI Advances Analytics Software from Reporting to Action, ISG says
Rapid adoption of AI capabilities helps enterprises prepare data, automate workflows, expand access to insights, new research says
STAMFORD, Conn., August 27, 2026–(BUSINESS WIRE)–Analytics software is becoming the foundation of AI-enabled workflows that not only interpret data and make recommendations but help to execute actions, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG) (Nasdaq: III).
The 2026 ISG Buyers Guides™ for Analytics report that AI and machine learning are now standard capabilities for generating insights that are delivered through business intelligence tools. With agentic AI, these systems are beginning to link analysis directly to execution by coordinating actions required to implement decisions.
“Analytics and business intelligence software increasingly run on AI,” said Kathy Rudy, partner, ISG Data, Analytics and Technology Office. “By 2028, almost all providers will use AI agents to automate and accelerate analytics processes. This trend is transforming and quickly expanding how enterprises analyze and use data.”
The ISG Buyers Guide research provides the rankings and ratings of 60 software providers and their products for enabling organizations to use data for tactical and strategic purposes. The series includes guides to AI-based analytics software, platforms for healthcare, manufacturing and retail organizations and products from emerging providers.
Advances in computing power over several decades have made analytics software more interactive and able to process larger datasets, ISG says. In step with this evolution, enterprise needs have grown from reporting aggregated information to planning, forecasting and using new forms of visualization. Analytics is used in a growing range of activities, including cost monitoring, supplier performance evaluation and development of staffing plans. Organizations are striving to make analytics more accessible to all employees, leading to its integration into business applications and everyday workflows.
AI and ML are extending the capabilities of analytics software in several areas, the research finds. Generative AI helps enterprises streamline data preparation, the most time-consuming step in analytics, with self-service tools that suggest ways to construct semantic models and combine datasets. Natural language interfaces, copilots and AI-based assistants allow non-technical users to generate insights. ML can analyze product usage data and anticipate user needs, and organizations say it has increased sales and enabled faster responses to opportunities.
