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Safeguard Healthcare Innovations with AIOps - Part 1

Sean McDermott
Windward Consulting Group

You've likely heard it before: every business is a digital business. That saying is increasingly true; however, some businesses and sectors digitize more quickly than others. Healthcare has traditionally been on the slower side of digital transformation and technology adoption, but that's changing.

A vast majority (81%) of worldwide healthcare executives say digital transformation is accelerating within their organizations, according to Accenture's Digital Health Technology Vision report. And 93% say they're innovating with urgency.

Even as a regular consumer, healthcare's digital transformation isn't hard to see. Readily available telehealth platforms connect patients and providers for more convenient and accessible healthcare services. And some caregivers use innovations like wearable devices to track patient health from afar.

Technology is also working behind the scenes to modernize healthcare organizations. Smart technologies can help this data-heavy industry modernize its internal systems, providing fast, accurate information on things like the number of available beds, patient status and supply inventory. Artificial intelligence (AI) can also do the heavy lifting typically involved in mundane administrative processes like paying bills, maintaining patient databases and scheduling appointments.

Many digital-first healthcare organizations are finding a new challenge as they embrace technology: businesses must guarantee seamless digital experiences. In other words, they must keep their apps and services always on and performing well.

Too often, there is so much attention on buying or developing apps and services that sustaining these innovations is overlooked. But system downtime can be costly for any business and particularly harmful for those in the healthcare industry.

As healthcare organizations roll out innovations at increasing velocity, they must build a long-term strategy for how they will maintain the uptime of their critical apps and services. And there's only one tool that can ensure this continuous availability in our modern IT ecosystems. Artificial Intelligence for IT Operations (AIOps) can help IT Operations teams ensure the uptime of critical apps and services.

How AIOps Helps Healthcare Systems

There's a common misconception: someone flips the technology "on" switch, and apps and services stay online and operate at peak performance. Unfortunately, this isn't the case.

Human IT Operations teams must operationalize healthcare technologies and then maintain them to provide reliable systems for patients, providers and other employees. After all, the systems, applications and networks behind the technologies that make our lives easier tend to be complex.

Maintaining uptime in these complex environments rides on monitoring and catching service-disrupting incidents before they impact the user. But humans can no longer perform this monitoring and detection alone because there is simply too much data for humans to process. Our modern systems prove too layered, interdependent and ephemeral. On top of this complexity, modern systems also spit out so much data that it's virtually impossible for human operators to handle, no matter how big the IT team.

The cadence of technology deployments and updates also makes uptime assurances more challenging. The very changes to the production environment that provide bigger and better technologies can also spark the service interruptions that lead to outages.

In short, the IT Operations teams charged with maintaining our modern IT ecosystems need help. And that's where AIOps comes in.

AIOps helps IT Operations teams simplify the management of ever complex and evolving IT systems. Through big data, automation and machine learning, a holistic AIOps solution detects potential service-disrupting incidents, identifies the problem and provides teams with the actionable insights they need to fix the problem — and keep it from happening again. If implemented correctly, these tools also automate the entire incident workflow to enable rapid responses that can catch issues early, before they impact the business.

Preventing outages is essential, but AIOps tools provide another advantage. With time added back into their days, engineering teams can focus on developing the kind of innovations that deliver tangible business value.

Go to: Safeguard Healthcare Innovations with AIOps - Part 2

Sean McDermott is the Founder of Windward Consulting Group and RedMonocle

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The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Safeguard Healthcare Innovations with AIOps - Part 1

Sean McDermott
Windward Consulting Group

You've likely heard it before: every business is a digital business. That saying is increasingly true; however, some businesses and sectors digitize more quickly than others. Healthcare has traditionally been on the slower side of digital transformation and technology adoption, but that's changing.

A vast majority (81%) of worldwide healthcare executives say digital transformation is accelerating within their organizations, according to Accenture's Digital Health Technology Vision report. And 93% say they're innovating with urgency.

Even as a regular consumer, healthcare's digital transformation isn't hard to see. Readily available telehealth platforms connect patients and providers for more convenient and accessible healthcare services. And some caregivers use innovations like wearable devices to track patient health from afar.

Technology is also working behind the scenes to modernize healthcare organizations. Smart technologies can help this data-heavy industry modernize its internal systems, providing fast, accurate information on things like the number of available beds, patient status and supply inventory. Artificial intelligence (AI) can also do the heavy lifting typically involved in mundane administrative processes like paying bills, maintaining patient databases and scheduling appointments.

Many digital-first healthcare organizations are finding a new challenge as they embrace technology: businesses must guarantee seamless digital experiences. In other words, they must keep their apps and services always on and performing well.

Too often, there is so much attention on buying or developing apps and services that sustaining these innovations is overlooked. But system downtime can be costly for any business and particularly harmful for those in the healthcare industry.

As healthcare organizations roll out innovations at increasing velocity, they must build a long-term strategy for how they will maintain the uptime of their critical apps and services. And there's only one tool that can ensure this continuous availability in our modern IT ecosystems. Artificial Intelligence for IT Operations (AIOps) can help IT Operations teams ensure the uptime of critical apps and services.

How AIOps Helps Healthcare Systems

There's a common misconception: someone flips the technology "on" switch, and apps and services stay online and operate at peak performance. Unfortunately, this isn't the case.

Human IT Operations teams must operationalize healthcare technologies and then maintain them to provide reliable systems for patients, providers and other employees. After all, the systems, applications and networks behind the technologies that make our lives easier tend to be complex.

Maintaining uptime in these complex environments rides on monitoring and catching service-disrupting incidents before they impact the user. But humans can no longer perform this monitoring and detection alone because there is simply too much data for humans to process. Our modern systems prove too layered, interdependent and ephemeral. On top of this complexity, modern systems also spit out so much data that it's virtually impossible for human operators to handle, no matter how big the IT team.

The cadence of technology deployments and updates also makes uptime assurances more challenging. The very changes to the production environment that provide bigger and better technologies can also spark the service interruptions that lead to outages.

In short, the IT Operations teams charged with maintaining our modern IT ecosystems need help. And that's where AIOps comes in.

AIOps helps IT Operations teams simplify the management of ever complex and evolving IT systems. Through big data, automation and machine learning, a holistic AIOps solution detects potential service-disrupting incidents, identifies the problem and provides teams with the actionable insights they need to fix the problem — and keep it from happening again. If implemented correctly, these tools also automate the entire incident workflow to enable rapid responses that can catch issues early, before they impact the business.

Preventing outages is essential, but AIOps tools provide another advantage. With time added back into their days, engineering teams can focus on developing the kind of innovations that deliver tangible business value.

Go to: Safeguard Healthcare Innovations with AIOps - Part 2

Sean McDermott is the Founder of Windward Consulting Group and RedMonocle

Hot Topics

The Latest

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...