Krishna Roy is a senior research analyst in the 451 Research technology research group at S&P Global. She leads the data science and analytics coverage areas for the Data, AI & Analytics channel. Krishna’s recent areas of concentration include data-driven decision-making, generative AI’s role in data science and analytics, and agentic AI. Prior to this, Krishna was a research analyst in the Data, AI & Analytics channel covering business intelligence and data management, including data integration and data warehousing. Krishna arrived at S&P Global through its 2019 acquisition of 451 Research, where she was a senior research analyst. During her 20-year tenure with 451 Research, she was responsible for many coverage areas, including business applications and business intelligence. Prior to joining 451 Research, Krishna held several journalist roles in London, New York and San Francisco. Krishna holds a Bachelor of Arts, First Class Honors Degree, in English literature and American studies from Brunel University, London.
Decision optimization has emerged as a common AI use case, which could lead to the assumption that organizations now use AI to make decisions autonomously without human involvement. However, the reality is more complex and likely to remain so.
Organizations can struggle to get their AI projects into production. ModelOp is looking to address the need for effective deployment, governance and monitoring of business use cases involving a variety of model types, including large language models, for Fortune 500 organizations.
The adoption of generative AI to assist users with data analysis tasks has led to a narrative that business intelligence dashboards are dead. However, our survey findings show a more nuanced state of play as more than two-thirds of surveyed organizations deploy dashboards, even though slightly more than one-third have adopted GenAI.
This report highlights key topics for 2026 in data, AI and analytics. Generative AI continues to permeate all aspects of the modern IT stack, supporting functions that rely on high-quality data, user-friendly tools and robust infrastructure. While some organizations continue to experiment with GenAI, an increasing number are moving into full-scale adoption and considering the business impacts and outcomes of their GenAI investments.
The vendor is seeking to democratize the use of Python for visual analysis with its Plotly Studio desktop application, which can be deployed on the new SaaS-based Plotly Cloud or its existing on-premises Dash Enterprise platform. Studio utilizes an LLM to autogenerate analytical apps that are primarily composed of visualizations.
While the vendor has built a business by providing embedded analytics for SaaS app developers using AWS' cloud, it has been eyeing a broader market opportunity with a rearchitected offering able to run on multiple cloud platforms. Qrvey is applying agentic AI to help further facilitate self-service analytics within SaaS apps.
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