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HPE Completes Spin-off and Merger of its Enterprise Services Business with CSC

Hewlett Packard Enterprise (HPE) has successfully completed the previously announced separation of its Enterprise Services business and merged it with Computer Sciences Corporation (CSC) to create DXC Technology.

As planned, HPE will now execute a clear and ambitious strategy based on three key pillars: First, making hybrid IT simple through secure, software-defined offerings that enable customers to move data seamlessly across their traditional data centers, private and public cloud environments. Second, redefining IT outside of the data center by powering the emerging intelligent edge that will run campus, branch, and Industrial IoT applications. Third, providing the world-class expertise and flexible consumption models to help customers transform their IT environments.

“The close of this transaction leaves HPE with a crystal clear mission, tied directly to the solutions our customers and partners tell us they want most,” said Meg Whitman, President and CEO of Hewlett Packard Enterprise. “I am also particularly proud that this transaction will deliver approximately $13.5 billion in value to HPE and its stockholders, which is almost sixty percent higher than when it was first announced last year.”

To provide the expertise and financial services support customers need, HPE will retain and continue to invest in Pointnext, its technology services organization that draws on the expertise of more than 25,000 specialists in 80 countries to support customers across Advisory and Transformation Services, Professional Services and Operational Services. These teams collaborate with businesses worldwide to speed their adoption of emerging technologies, including cloud computing and hybrid IT, big data and analytics, the Intelligent Edge and Internet of Things (IoT).

HPE will also maintain a strong relationship with DXC, with agreements in place to support current customers and to grow business over time. Meg Whitman will join the board of DXC. In addition, HPE will build valuable new partnerships with other leading IT services companies.

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HPE Completes Spin-off and Merger of its Enterprise Services Business with CSC

Hewlett Packard Enterprise (HPE) has successfully completed the previously announced separation of its Enterprise Services business and merged it with Computer Sciences Corporation (CSC) to create DXC Technology.

As planned, HPE will now execute a clear and ambitious strategy based on three key pillars: First, making hybrid IT simple through secure, software-defined offerings that enable customers to move data seamlessly across their traditional data centers, private and public cloud environments. Second, redefining IT outside of the data center by powering the emerging intelligent edge that will run campus, branch, and Industrial IoT applications. Third, providing the world-class expertise and flexible consumption models to help customers transform their IT environments.

“The close of this transaction leaves HPE with a crystal clear mission, tied directly to the solutions our customers and partners tell us they want most,” said Meg Whitman, President and CEO of Hewlett Packard Enterprise. “I am also particularly proud that this transaction will deliver approximately $13.5 billion in value to HPE and its stockholders, which is almost sixty percent higher than when it was first announced last year.”

To provide the expertise and financial services support customers need, HPE will retain and continue to invest in Pointnext, its technology services organization that draws on the expertise of more than 25,000 specialists in 80 countries to support customers across Advisory and Transformation Services, Professional Services and Operational Services. These teams collaborate with businesses worldwide to speed their adoption of emerging technologies, including cloud computing and hybrid IT, big data and analytics, the Intelligent Edge and Internet of Things (IoT).

HPE will also maintain a strong relationship with DXC, with agreements in place to support current customers and to grow business over time. Meg Whitman will join the board of DXC. In addition, HPE will build valuable new partnerships with other leading IT services companies.

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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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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 ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.