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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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Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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