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Accenture and Splunk Form Alliance

Accenture entered into an alliance relationship that integrates Splunk products and cloud services into Accenture’s application services, security and digital offerings.

Accenture is helping clients use Splunk solutions to improve business outcomes by mining vast amounts of application and operational data to identify trends and improvement opportunities that were previously difficult to detect.

Accenture is expanding its network of trained Splunk practitioners in order to meet significant client demand for operational intelligence solutions. Accenture and Splunk are also collaborating and bringing to market new packaged solutions, the first of which integrates Splunk analytics into Accenture’s Managed Security Services. Accenture will provide Security Information Event Management (SIEM) As-a-Service to clients, using Splunk Enterprise and Splunk Enterprise Security (ES) to deliver advanced threat detection, correlation, search and incident management capabilities. Additional solutions may be tailored to various business areas including digital, marketing and sales.

“Our alliance with Splunk is another strong example of how Accenture is impacting our clients’ businesses with ‘new IT.’ By mining and analyzing machine data from back-end systems, call centers, web traffic, inventory levels, shipments and more, IT can play a greater role in influencing business performance, not just IT performance,” said Bhaskar Ghosh, Group Chief Executive, Accenture Technology Services. “We’re integrating Splunk’s platform for operational intelligence into our global application service offerings and delivery teams, bringing robust new capabilities to our clients at scale. We can also deliver this capability through our new intelligent automation platform, Accenture myWizard, to help turn data into critical insights that drive improved business outcomes.”

“As one of the largest global systems integrators, Accenture will help broaden access to Splunk’s platform for operational intelligence to organizations that have not yet tapped the power of machine data,” said Doug Merritt, President and CEO, Splunk. “By analyzing machine data, organizations gain end-to-end visibility into operations and make better informed business decisions. We are thrilled to work with Accenture and leverage its innovative best in class technological experience to further deliver operational intelligence around the globe.”

Accenture Technology Services adopted Splunk internally, with a focus on helping IT organizations become more business-centric. Using Splunk Enterprise, Splunk Cloud, Splunk Enterprise Security, Splunk User Behavior Analytics and Splunk IT Service Intelligence, Accenture is developing and rolling out operational intelligence solutions that span the entire software development lifecycle. Additionally, any team can build their own Splunk-based application and host it with a central app store for other teams to use. Accenture has developed numerous Splunk applications to date, spanning software development, IT operations, security monitoring and business operations.

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Accenture and Splunk Form Alliance

Accenture entered into an alliance relationship that integrates Splunk products and cloud services into Accenture’s application services, security and digital offerings.

Accenture is helping clients use Splunk solutions to improve business outcomes by mining vast amounts of application and operational data to identify trends and improvement opportunities that were previously difficult to detect.

Accenture is expanding its network of trained Splunk practitioners in order to meet significant client demand for operational intelligence solutions. Accenture and Splunk are also collaborating and bringing to market new packaged solutions, the first of which integrates Splunk analytics into Accenture’s Managed Security Services. Accenture will provide Security Information Event Management (SIEM) As-a-Service to clients, using Splunk Enterprise and Splunk Enterprise Security (ES) to deliver advanced threat detection, correlation, search and incident management capabilities. Additional solutions may be tailored to various business areas including digital, marketing and sales.

“Our alliance with Splunk is another strong example of how Accenture is impacting our clients’ businesses with ‘new IT.’ By mining and analyzing machine data from back-end systems, call centers, web traffic, inventory levels, shipments and more, IT can play a greater role in influencing business performance, not just IT performance,” said Bhaskar Ghosh, Group Chief Executive, Accenture Technology Services. “We’re integrating Splunk’s platform for operational intelligence into our global application service offerings and delivery teams, bringing robust new capabilities to our clients at scale. We can also deliver this capability through our new intelligent automation platform, Accenture myWizard, to help turn data into critical insights that drive improved business outcomes.”

“As one of the largest global systems integrators, Accenture will help broaden access to Splunk’s platform for operational intelligence to organizations that have not yet tapped the power of machine data,” said Doug Merritt, President and CEO, Splunk. “By analyzing machine data, organizations gain end-to-end visibility into operations and make better informed business decisions. We are thrilled to work with Accenture and leverage its innovative best in class technological experience to further deliver operational intelligence around the globe.”

Accenture Technology Services adopted Splunk internally, with a focus on helping IT organizations become more business-centric. Using Splunk Enterprise, Splunk Cloud, Splunk Enterprise Security, Splunk User Behavior Analytics and Splunk IT Service Intelligence, Accenture is developing and rolling out operational intelligence solutions that span the entire software development lifecycle. Additionally, any team can build their own Splunk-based application and host it with a central app store for other teams to use. Accenture has developed numerous Splunk applications to date, spanning software development, IT operations, security monitoring and business operations.

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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 ...

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 ...

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.