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2026 Data, AI & Analytics Trends Survey Report + Podcast Series

Insights from 100 enterprise leaders on fragmentation, AI readiness, and the unification imperative.
Download the reportListen to the podcasts
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Large enterprises have invested heavily in modernizing analytics and preparing for AI at scale. Yet the landscape that emerges is one defined by fragmentation, inconsistent semantic layers, and persistent gaps in governance and observability. 

We surveyed 100 senior data and technology leaders (CIOs, CDOs, CTOs, and heads of AI/analytics) at organizations with $2B+ revenue and 5,000+ employees across financial services, retail, technology, manufacturing, and healthcare. The findings are clear: semantic drift is no longer a “messy data” problem at the edges. It is the operating system most enterprises are still running on. 

Key findings include:

  • 99% of leaders struggle with defining consistent business metrics across tools and departments
  • 87% demand greater visibility into how AI uses and interprets their data
  • Nearly 80% of data teams spend more than half their time on data preparation rather than insight generation
  • Top 3–5 year priorities: scalability across sources (92%), data & metric portability (83%), and AI governance & observability (82%)

The report reveals the execution gap between ambition and reality, and shows why independent semantic layers, governed AI, and portable data foundations are now strategic imperatives.

Podcast Series Unpacking the Survey: Expert Conversations on Data, AI & Analytics

In this three-part series, Strategy Inc. leaders dive into the survey results with CIO Dive. Hear directly from our product experts on why data consistency remains one of the hardest problems in enterprise analytics, and exactly what it takes to solve it.

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Episode 1 - The Cost of Fragmentation: Why Data Consistency Still Fails

Saurabh Abhyankar, Chief Product Officer, Strategy Inc. 

Despite decades of investment, many enterprises remain trapped in a cycle of data inconsistency and mistrust. This episode dives into just how widespread semantic fragmentation still is, and why true alignment depends on culture, ownership, and the creation of a unified semantic foundation. 

Listen now
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Episode 2 - Capabilities That Count: Building the Foundation for Scalable, Trusted AI

Erika Moreno, Vice President of Product, Strategy Inc. 

AI success begins with the fundamentals, but most enterprises are still in the early stages of achieving consistent, governed, and AI-ready data. This episode breaks down what “AI-readiness” really means and the capabilities that matter most: unified business definitions, robust governance, and scalability across tools and platforms. 

Listen now
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Episode 3 - What Is AI Doing With Your Data? The New Imperative of Observability

Juliana Schoettler, Senior Product Manager for AI, Strategy Inc. 

Do you truly know what AI does with your data? With confidence in AI transparency alarmingly low, this episode explains why AI observability must include lineage, explainability, and accountability. Learn how to make trustworthy decisions, strengthen security and compliance, and what “trustworthy AI” could look like in five years. 

Listen now

Fix data fragmentation before AI scales

See what leading enterprises are changing in 2026.
Download the reportListen to the podcasts