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Gartner: Funding for Tech Purchases Moving Outside IT

Almost three-fourths (74%) of technology purchases are funded, at least partially, by business units (BUs) outside of IT, according to a recent Gartner survey.

Only 26% of technology investments are funded entirely by the IT organization.

In November and December 2021, Gartner surveyed 1,120 manager-level or higher respondents in organizations with at least $1 million in annual revenue in North America, Western Europe and Asia/Pacific to understand how organizations approach large-scale buying efforts for enterprise technology.

"As technology becomes more critical to and embedded across the business, buying team dynamics continue to evolve. In the past, it was relatively easy to predict who buyers were, but all that has changed," said Derry N. Finkeldey, Research VP at Gartner.

"Gartner research found that 41% of employees are business technologists, creating technology or analytics capabilities for internal or external business use and reporting outside of IT departments. In a world where most technologists work outside the corporate IT department, literally anyone could be a technology buyer for their organization."

The survey found that across large purchases in every major technology category, organizations take varying approaches to funding:

■ The most common funding approach for hardware, technology services and managed services is for IT to fund the entire purchase, followed by funding coming from multiple departments or BUs and IT.

■ The most common funding model for software and integrated solutions flip these two: Funding by multiple departments and IT is most common, followed by IT-only funding.

■ IT is providing at least part of the funding in 70% of the purchases studied.

■ 75% of respondents using shared funding approaches experienced delays reaching agreement on the budget allocation between groups.

"High-tech providers need new approaches to identify not only whom to engage, but also how to engage B2B buyers across all BUs, with confidence that their approaches will be effective and their roadmaps compelling. Product leaders need to coach teams tasked with discovering budget availability to extend that research to also include the funding approach," said Finkeldey.

Even as the role of business technologists grows, product leaders should not bypass central IT representatives even when addressing an industry- or line-of-business-specific use case with an identified business champion, because in nearly every case, IT will continue to provide at least partial funding.

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Gartner: Funding for Tech Purchases Moving Outside IT

Almost three-fourths (74%) of technology purchases are funded, at least partially, by business units (BUs) outside of IT, according to a recent Gartner survey.

Only 26% of technology investments are funded entirely by the IT organization.

In November and December 2021, Gartner surveyed 1,120 manager-level or higher respondents in organizations with at least $1 million in annual revenue in North America, Western Europe and Asia/Pacific to understand how organizations approach large-scale buying efforts for enterprise technology.

"As technology becomes more critical to and embedded across the business, buying team dynamics continue to evolve. In the past, it was relatively easy to predict who buyers were, but all that has changed," said Derry N. Finkeldey, Research VP at Gartner.

"Gartner research found that 41% of employees are business technologists, creating technology or analytics capabilities for internal or external business use and reporting outside of IT departments. In a world where most technologists work outside the corporate IT department, literally anyone could be a technology buyer for their organization."

The survey found that across large purchases in every major technology category, organizations take varying approaches to funding:

■ The most common funding approach for hardware, technology services and managed services is for IT to fund the entire purchase, followed by funding coming from multiple departments or BUs and IT.

■ The most common funding model for software and integrated solutions flip these two: Funding by multiple departments and IT is most common, followed by IT-only funding.

■ IT is providing at least part of the funding in 70% of the purchases studied.

■ 75% of respondents using shared funding approaches experienced delays reaching agreement on the budget allocation between groups.

"High-tech providers need new approaches to identify not only whom to engage, but also how to engage B2B buyers across all BUs, with confidence that their approaches will be effective and their roadmaps compelling. Product leaders need to coach teams tasked with discovering budget availability to extend that research to also include the funding approach," said Finkeldey.

Even as the role of business technologists grows, product leaders should not bypass central IT representatives even when addressing an industry- or line-of-business-specific use case with an identified business champion, because in nearly every case, IT will continue to provide at least partial funding.

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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 ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...