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Gartner: Organizations Are Evolving D&A Operating Model Because of AI

A majority (61%) of organizations are forced to evolve or rethink their data and analytics (D&A) operating model because of the impact of disruptive artificial intelligence (AI) technologies, according to a new Gartner, Inc. survey.

"Responding to the rapid evolution of D&A and AI technologies, CDAOs are wasting no time in making changes to their operating model," said Alan D. Duncan, Distinguished VP Analyst at Gartner. CDAOs are doing it to support data-driven innovation and accelerate organizational agility, with data governance at the core.

When asked about changes CDAOs need to make to their D&A operating model to be fit for current and future purpose, 38% of CDAOs said that their D&A architecture will be overhauled over the next 12-18 months, and 29% said they will revamp how they manage data assets and adopt and apply governance policies, practices and standards.

CDAOs Are Expanding Responsibilities

"While the management of their organization's D&A operating model is increasing year over year, no other role than the CDAO has the responsibility of many of the key enablers of AI, which include data governance, D&A ethics, and data and AI literacy," said Duncan. "The scope of responsibilities of the CDAO role has also expanded as budget and resource constraints become even more of a problem."

Among the CDAO's key responsibilities are managing the D&A strategy (74%) and D&A governance (68%). Being accountable for AI is also high on the CDAO's agenda. The survey found that 49% of CDAOs said generative AI (GenAI) is within their scope of primary responsibilities. AI is within scope for 58% of CDAOs, which is an increase from 34% in 2023.

CDAOs to Negotiate the Way D&A Is Funded

The expansion of responsibilities entails a significant cost for CDAOs. Among CDAOs who report a year-over-year increase in their function's funding, 46% still report budget constraints as a challenge. "CDAOs who present better business cases to CFOs, receive better and quicker funding for their D&A initiatives. They also gain higher executive buy-in," said Duncan.

CDAOs must explain to the CFO how any change in D&A funding models aligns to the ratio of D&A value propositions as a utility, enabler or driver of the organization. "However, only 49% of surveyed CDAOs have established business outcome-driven metrics that allow stakeholders to track D&A value. In addition, 34% have not established business outcome metrics for D&A," said Duncan.

CDAOs need to grow their power and influence to make things happen. They also must understand the value levers and pain points of the organization end to end to showcase their value to the board. "If not, by 2026, 75% of CDAOs who fail to make organization-wide influence and measurable impact their top priority, will be assimilated into technology functions," said Duncan.

Methodology: The annual Gartner Chief Data & Analytics Officer (CDAO) survey was conducted from September through November 2023 among 479 chief data and analytics officers, chief data officers (CDO) and chief analytics officers (CAO) across the world.

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Gartner: Organizations Are Evolving D&A Operating Model Because of AI

A majority (61%) of organizations are forced to evolve or rethink their data and analytics (D&A) operating model because of the impact of disruptive artificial intelligence (AI) technologies, according to a new Gartner, Inc. survey.

"Responding to the rapid evolution of D&A and AI technologies, CDAOs are wasting no time in making changes to their operating model," said Alan D. Duncan, Distinguished VP Analyst at Gartner. CDAOs are doing it to support data-driven innovation and accelerate organizational agility, with data governance at the core.

When asked about changes CDAOs need to make to their D&A operating model to be fit for current and future purpose, 38% of CDAOs said that their D&A architecture will be overhauled over the next 12-18 months, and 29% said they will revamp how they manage data assets and adopt and apply governance policies, practices and standards.

CDAOs Are Expanding Responsibilities

"While the management of their organization's D&A operating model is increasing year over year, no other role than the CDAO has the responsibility of many of the key enablers of AI, which include data governance, D&A ethics, and data and AI literacy," said Duncan. "The scope of responsibilities of the CDAO role has also expanded as budget and resource constraints become even more of a problem."

Among the CDAO's key responsibilities are managing the D&A strategy (74%) and D&A governance (68%). Being accountable for AI is also high on the CDAO's agenda. The survey found that 49% of CDAOs said generative AI (GenAI) is within their scope of primary responsibilities. AI is within scope for 58% of CDAOs, which is an increase from 34% in 2023.

CDAOs to Negotiate the Way D&A Is Funded

The expansion of responsibilities entails a significant cost for CDAOs. Among CDAOs who report a year-over-year increase in their function's funding, 46% still report budget constraints as a challenge. "CDAOs who present better business cases to CFOs, receive better and quicker funding for their D&A initiatives. They also gain higher executive buy-in," said Duncan.

CDAOs must explain to the CFO how any change in D&A funding models aligns to the ratio of D&A value propositions as a utility, enabler or driver of the organization. "However, only 49% of surveyed CDAOs have established business outcome-driven metrics that allow stakeholders to track D&A value. In addition, 34% have not established business outcome metrics for D&A," said Duncan.

CDAOs need to grow their power and influence to make things happen. They also must understand the value levers and pain points of the organization end to end to showcase their value to the board. "If not, by 2026, 75% of CDAOs who fail to make organization-wide influence and measurable impact their top priority, will be assimilated into technology functions," said Duncan.

Methodology: The annual Gartner Chief Data & Analytics Officer (CDAO) survey was conducted from September through November 2023 among 479 chief data and analytics officers, chief data officers (CDO) and chief analytics officers (CAO) across the world.

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For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...