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Responding to Cybersecurity Incidents Still a Major Challenge

A study conducted by Ponemon Institute and sponsored by IBM Resilient found that 77 percent of respondents admit they do not have a formal cyber security incident response plan (CSIRP) applied consistently across their organization.

Nearly half of the respondents reported that their incident response plan is either informal/ad hoc or completely non-existent.

Despite this lack of formal planning, 72 percent of organizations report feeling more Cyber Resilient today than they were last year. Highly resilient organizations (61 percent) attribute their confidence to their ability to hire skilled personnel — but organizations need both technology and people to be Cyber Resilient. In fact, 60 percent of respondents consider a lack of investment in AI and machine learning as the biggest barrier to Cyber Resilience.

This confidence may be misplaced, with the analysis revealing that 57 percent of respondents said the time to resolve an incident has increased, while 65 percent reported the severity of the attacks has increased. These areas represent some of the key factors impacting overall cyber resiliency. These problems are further compounded by just 31 percent of those surveyed having an adequate Cyber Resilience budget in place and difficulty retaining and hiring IT Security professionals (77 percent).

“Organizations may be feeling more Cyber Resilient today, and the biggest reason why was hiring skilled personnel,” said Ted Julian, VP of Product Management and Co-Founder, IBM Resilient. “Having the right staff in place is critical but arming them with the most modern tools to augment their work is equally as important. A response plan that orchestrates human intelligence with machine intelligence is the only way security teams are going to get ahead of the threat and improve overall Cyber Resilience.”

The lack of a consistent CSIRP is a persistent trend each year despite a key finding from IBM’s 2017 Cost of a Data Breach Study. The cost of a data breach was nearly $1 million lower on average when organizations were able to contain the breach in less than thirty days — highlighting the value and importance of having a strong CSIRP.

“A sharp focus in a few crucial areas can make a big difference when it comes to Cyber Resilience,” said Dr. Larry Ponemon. “Ensuring the security function is equipped with a proper incident response plan, staffing, and budget will lead to a stronger security posture and better overall Cyber Resilience.”

About the Study: Conducted by the Ponemon Institute and sponsored by IBM Resilient, The 2018 Cyber Resilient Organization is the third annual benchmark study on Cyber Resilience — an organization’s ability to maintain its core purpose and integrity in the face of cyberattacks. The global survey features insight from more than 2,800 security and IT professionals from around the world, including the United States, United Kingdom, France, Germany, Brazil, Asia-Pacific, Middle East, and Australia.

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Responding to Cybersecurity Incidents Still a Major Challenge

A study conducted by Ponemon Institute and sponsored by IBM Resilient found that 77 percent of respondents admit they do not have a formal cyber security incident response plan (CSIRP) applied consistently across their organization.

Nearly half of the respondents reported that their incident response plan is either informal/ad hoc or completely non-existent.

Despite this lack of formal planning, 72 percent of organizations report feeling more Cyber Resilient today than they were last year. Highly resilient organizations (61 percent) attribute their confidence to their ability to hire skilled personnel — but organizations need both technology and people to be Cyber Resilient. In fact, 60 percent of respondents consider a lack of investment in AI and machine learning as the biggest barrier to Cyber Resilience.

This confidence may be misplaced, with the analysis revealing that 57 percent of respondents said the time to resolve an incident has increased, while 65 percent reported the severity of the attacks has increased. These areas represent some of the key factors impacting overall cyber resiliency. These problems are further compounded by just 31 percent of those surveyed having an adequate Cyber Resilience budget in place and difficulty retaining and hiring IT Security professionals (77 percent).

“Organizations may be feeling more Cyber Resilient today, and the biggest reason why was hiring skilled personnel,” said Ted Julian, VP of Product Management and Co-Founder, IBM Resilient. “Having the right staff in place is critical but arming them with the most modern tools to augment their work is equally as important. A response plan that orchestrates human intelligence with machine intelligence is the only way security teams are going to get ahead of the threat and improve overall Cyber Resilience.”

The lack of a consistent CSIRP is a persistent trend each year despite a key finding from IBM’s 2017 Cost of a Data Breach Study. The cost of a data breach was nearly $1 million lower on average when organizations were able to contain the breach in less than thirty days — highlighting the value and importance of having a strong CSIRP.

“A sharp focus in a few crucial areas can make a big difference when it comes to Cyber Resilience,” said Dr. Larry Ponemon. “Ensuring the security function is equipped with a proper incident response plan, staffing, and budget will lead to a stronger security posture and better overall Cyber Resilience.”

About the Study: Conducted by the Ponemon Institute and sponsored by IBM Resilient, The 2018 Cyber Resilient Organization is the third annual benchmark study on Cyber Resilience — an organization’s ability to maintain its core purpose and integrity in the face of cyberattacks. The global survey features insight from more than 2,800 security and IT professionals from around the world, including the United States, United Kingdom, France, Germany, Brazil, Asia-Pacific, Middle East, and Australia.

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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.