Top Concerns for Tech Decision Makers

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra.

Notably, eight in 10 decision makers (85%) also said that data ownership has changed over the last year with the emergence of AI.

"AI will continue to disrupt and reshape the future of work," said Collibra Stijn "Stan" Christiaens, co-founder and Chief Data Citizen at Collibra. "As organizations look to integrate AI more into the workplace, it is ever more critical to connect data owners with privacy and compliance teams to balance AI innovation with trust and ensure data privacy."

Despite concerns around data privacy and ROI, the survey indicates a strong overall momentum towards AI adoption, with 86% of organizations planning to proceed with their AI initiatives. However, this enthusiasm varies by company size. While nearly all large companies (96%) intend to forge ahead with their AI plans despite the evolving landscape, smaller (78%) and medium-sized (79%) organizations are exhibiting a more measured approach.

The survey also found that nine in 10 employees at larger organizations (1,000+) say their company encourages the use of AI in the workplace and provides the necessary tools to support their work. The same percentage also said that their company has issued an AI use policy or guidelines to their employees.

In addition, the survey found that nearly nine in 10 decision-makers (88%) say they have a lot or a great deal of trust in their own companies' approach to shaping the future of AI, with three quarters (75%) agreeing that their company prioritizes AI training and upskilling, with decision-makers at large companies (1000+ employees) more likely than those at small companies (1-99 employees) to agree (87% vs. 55%).

"As Al continues to be adopted across Corporate America, organizations need to centralize visibility of AI models and agents across AI platforms and ensure traceability between AI use cases and the data that feeds them," stated Christiaens. "By adopting an approach to AI governance that connects models, data, and policies, organizations can protect critical data while ensuring confidentiality measures."

Methodology: The Harris Poll surveyed more than 300 US adults ages 21+ who are employed full-time as data management, privacy and/or AI decision makers at their current companies.

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Top Concerns for Tech Decision Makers

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra.

Notably, eight in 10 decision makers (85%) also said that data ownership has changed over the last year with the emergence of AI.

"AI will continue to disrupt and reshape the future of work," said Collibra Stijn "Stan" Christiaens, co-founder and Chief Data Citizen at Collibra. "As organizations look to integrate AI more into the workplace, it is ever more critical to connect data owners with privacy and compliance teams to balance AI innovation with trust and ensure data privacy."

Despite concerns around data privacy and ROI, the survey indicates a strong overall momentum towards AI adoption, with 86% of organizations planning to proceed with their AI initiatives. However, this enthusiasm varies by company size. While nearly all large companies (96%) intend to forge ahead with their AI plans despite the evolving landscape, smaller (78%) and medium-sized (79%) organizations are exhibiting a more measured approach.

The survey also found that nine in 10 employees at larger organizations (1,000+) say their company encourages the use of AI in the workplace and provides the necessary tools to support their work. The same percentage also said that their company has issued an AI use policy or guidelines to their employees.

In addition, the survey found that nearly nine in 10 decision-makers (88%) say they have a lot or a great deal of trust in their own companies' approach to shaping the future of AI, with three quarters (75%) agreeing that their company prioritizes AI training and upskilling, with decision-makers at large companies (1000+ employees) more likely than those at small companies (1-99 employees) to agree (87% vs. 55%).

"As Al continues to be adopted across Corporate America, organizations need to centralize visibility of AI models and agents across AI platforms and ensure traceability between AI use cases and the data that feeds them," stated Christiaens. "By adopting an approach to AI governance that connects models, data, and policies, organizations can protect critical data while ensuring confidentiality measures."

Methodology: The Harris Poll surveyed more than 300 US adults ages 21+ who are employed full-time as data management, privacy and/or AI decision makers at their current companies.

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Understanding Zero-Day Vulnerabilities: Why They Matter and How to Stay Protected

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

Data Center Outages Becoming Less Frequent

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Instrumentation Score: Quantifying Telemetry Quality

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

Automating While Keeping Humans in the Loop

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

AI Factories: Scaling Intelligence with Observability, Reliability and Efficiency

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...

Think You've Heard Everything About the Debate over RTO? Here's the Big Thing Leaders Are Missing

Almost half (48%) of employees admit they resent their jobs but stay anyway, according to research from Ivanti ... This has obvious consequences across the business, but we're overlooking the massive impact of resenteeism and presenteeism on IT. For IT professionals tasked with managing the backbone of modern business operations, these numbers spell big trouble ...

Beyond the MACH Hype: Why Your Commerce Platform Is Not Helping You Win DX or CX

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

Effective FinOps: Moving from Recommendations to Risks

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

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While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...