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Gartner: CIOs Must Define an Event-Centric Digital Business Strategy

Achieving broad competence in event-driven IT will be a top three priority for the majority of global enterprise CIOs by 2020, according to Gartner, Inc. Defining an event-centric digital business strategy will be key to delivering on the growth agenda that many CEOs see as their highest business priority.

"Event-driven architecture (EDA) is a key technology approach to delivering this goal," said Anne Thomas, VP and Distinguished Analyst at Gartner. "Digital business demands a rapid response to events. Organizations must be able to respond to and take advantage of 'business moments' and these real-time requirements are driving CIOs to make their application software more event-driven."

Define an Event-Centric Digital Business Strategy

Because CEOs are focused on growth via digital business, CIOs should focus on defining an event-centric digital business strategy and articulate the business value of EDA. According to the Gartner 2017 CEO survey, 58 percent of CEOs see growth as their highest business priority. CEOs achieve growth by adopting new business models, introducing new products and services, expanding into new markets and geographies, upselling to existing customers and stealing market share from competitors.

"Findings from the survey clearly indicate that CEOs view digital business as their No. 1 opportunity for growth," said Thomas. "Most CEOs also recognize a triangular relationship between technology, product improvement and growth. They recognize that technology is the fundamental enabler of digital transformation and leading digital companies have figured out that EDA is the 'secret sauce' that gives them a competitive edge."

Event-centric processing is the native architecture for digital business, and to enable growth through digital business, strategic parts of the application portfolio will need to become event-driven. CIOs can use EDA to foster growth by enabling digital business transformation, capitalizing on digital business moments, using modern technologies, accelerating business agility and enabling application modernization.

Use Innovative EDA-Based Technologies to Support Digital Business Transformation

"Event processing and analytics play a significant role in allowing organizations to capitalize on a business moment," said Thomas. "A convergence of events generates a business opportunity, and real-time analytics of those events, as well as current data and wider context data, can be used to influence a decision and generate a successful business outcome. But you can't capitalize on the business moment if you don't first recognize the convergence of events and the digital business opportunity."

This is why digital business is so dependent on EDA. The events generated by systems — customers, things and artificial intelligence (AI) — must be digitized so that they can be recognized and processed in real time. EDA will become an essential skill in supporting the transformation by 2018, meaning that application architecture and development teams must develop EDA competency now to prepare for next year's needs. CIOs should identify current projects where EDA can provide the most value to enable adoption of technology innovations such as microservices, the Internet of Things (IoT), AI, machine learning, blockchain and smart contracts.

Modernize Application Portfolios to Support Digital Business Transformation

A legacy application portfolio can be a significant inhibitor to digital business transformation. A digital business technology foundation must support continuous availability, massive scalability, automatic recovery and dynamic extensibility. Digital business applications must also use modern technologies to engage customers, support digital business ecosystems, capitalize on digital moments, and exploit AI and the IoT.

"Modernizing core application systems takes time, and few organizations are in a position to immediately move over to a replacement system," said Thomas. "Instead, they need to use EDA to stage their modernization efforts, and gradually migrate capabilities while implementing digital transformation."

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Gartner: CIOs Must Define an Event-Centric Digital Business Strategy

Achieving broad competence in event-driven IT will be a top three priority for the majority of global enterprise CIOs by 2020, according to Gartner, Inc. Defining an event-centric digital business strategy will be key to delivering on the growth agenda that many CEOs see as their highest business priority.

"Event-driven architecture (EDA) is a key technology approach to delivering this goal," said Anne Thomas, VP and Distinguished Analyst at Gartner. "Digital business demands a rapid response to events. Organizations must be able to respond to and take advantage of 'business moments' and these real-time requirements are driving CIOs to make their application software more event-driven."

Define an Event-Centric Digital Business Strategy

Because CEOs are focused on growth via digital business, CIOs should focus on defining an event-centric digital business strategy and articulate the business value of EDA. According to the Gartner 2017 CEO survey, 58 percent of CEOs see growth as their highest business priority. CEOs achieve growth by adopting new business models, introducing new products and services, expanding into new markets and geographies, upselling to existing customers and stealing market share from competitors.

"Findings from the survey clearly indicate that CEOs view digital business as their No. 1 opportunity for growth," said Thomas. "Most CEOs also recognize a triangular relationship between technology, product improvement and growth. They recognize that technology is the fundamental enabler of digital transformation and leading digital companies have figured out that EDA is the 'secret sauce' that gives them a competitive edge."

Event-centric processing is the native architecture for digital business, and to enable growth through digital business, strategic parts of the application portfolio will need to become event-driven. CIOs can use EDA to foster growth by enabling digital business transformation, capitalizing on digital business moments, using modern technologies, accelerating business agility and enabling application modernization.

Use Innovative EDA-Based Technologies to Support Digital Business Transformation

"Event processing and analytics play a significant role in allowing organizations to capitalize on a business moment," said Thomas. "A convergence of events generates a business opportunity, and real-time analytics of those events, as well as current data and wider context data, can be used to influence a decision and generate a successful business outcome. But you can't capitalize on the business moment if you don't first recognize the convergence of events and the digital business opportunity."

This is why digital business is so dependent on EDA. The events generated by systems — customers, things and artificial intelligence (AI) — must be digitized so that they can be recognized and processed in real time. EDA will become an essential skill in supporting the transformation by 2018, meaning that application architecture and development teams must develop EDA competency now to prepare for next year's needs. CIOs should identify current projects where EDA can provide the most value to enable adoption of technology innovations such as microservices, the Internet of Things (IoT), AI, machine learning, blockchain and smart contracts.

Modernize Application Portfolios to Support Digital Business Transformation

A legacy application portfolio can be a significant inhibitor to digital business transformation. A digital business technology foundation must support continuous availability, massive scalability, automatic recovery and dynamic extensibility. Digital business applications must also use modern technologies to engage customers, support digital business ecosystems, capitalize on digital moments, and exploit AI and the IoT.

"Modernizing core application systems takes time, and few organizations are in a position to immediately move over to a replacement system," said Thomas. "Instead, they need to use EDA to stage their modernization efforts, and gradually migrate capabilities while implementing digital transformation."

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...