Insights From 200 Senior IT Leaders

CIOs: See How You Stack Up With Modern Analytics

Demystifying the Modern Data Stack in the Era of GenAI

We surveyed 200 senior analytics and IT leaders on GenAI, tech stack and tooling, data challenges, and more. Get the full report for the realities of “modern” analytics today to turn blockers into benefits.

Get the Survey Results

88% of IT Leaders Do Not Have Specific Tools/Processes for Managing LLMs

There are mounting complexities when it comes to scaling GenAI (think managing costs of LLMs, achieving AI regulatory compliance, lack of governance, and more). Our survey revealed that nearly all (88%) of respondents lack specific tools and processes for managing LLMs, a process that gets unwieldy (and riskier!) fast without the right tools.

“This maturing phase is a welcome development because it gives CIOs an opportunity to turn GenAI’s promise into business value … Ultimately, getting the full value from GenAI requires companies to rewire how they work, and putting in place a scalable technology foundation is a key part of that process.”

– McKinsey Technology and QuantumBlack AI

by McKinsey

The Story of the Not-So-Modern Data Stack

Steps CIOs Can Take to Navigate This New World

Question Your GenAI Spend if You Cannot Execute

We know CIOs and IT leaders are spending on GenAI, but they also must ensure that the costs don’t eclipse the value they’re providing to the organization.

Combat the New Layers of Operational Risk

31% of respondents have faced barriers to using LLMs in the way that they would like, so it’s time to move work to a governed environment and leverage investments in the latest cloud data and GenAI to drive more projects and value.

Simplify Your Tech Stack and Maintain Optionality

32% of respondents think their organization has too many data tools. Do you? It’s time to tame that explosion of tools to the ones that best serve the organization.

Keep Working on Data Quality (But Don’t Let It Stop You)

Data quality beat out data access, data security, and compute scalability as the greatest data infrastructure challenge. Don’t let it halt your analytics and AI efforts for perfect data quality.