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Steps Every Business Must Take to Digitize and Survive

Mark Banfield
LogicMonitor

In 2020, our society is undergoing massive upheaval and businesses are being forced to adapt on the fly. During this period of crisis, the companies that make the necessary adjustments the quickest will succeed. We're already seeing it happen in the accelerated push toward digitization, as companies that smoothly digitize their customer experiences move forward and those that don't get left behind.


Of course, digitization is not new, but rather an evergreen topic of discussion at board and executive-level meetings. What is new, however, is the speed at which the gap between the digital haves and have-nots is widening amid the COVID-19 crisis.

The global pandemic has magnified the urgency of digitization, and it has exposed the businesses that are still struggling to manage even the most basic of digital interactions with their customers and employees. Organizations everywhere are under enormous pressure to accelerate digital transformation, expand cloud services and do whatever else it takes to stay connected with customers and workers.

What's striking, however, is that only 39% of IT professionals have a high level of confidence in their organization's ability to seamlessly deliver digital services in the midst of a crisis, according to a new survey we conducted here at LogicMonitor.

I've experienced this disconnect firsthand in my interactions with a number of businesses. For instance, I recently bought a house overseas and the real estate agent wanted to fax me the closing documents. When I told the agent I didn't have a fax machine (who has a fax machine anymore?), he offered to mail them to me so I could sign and send back to him. Who knows how long that would have taken? Fax machines are a relic of the past when services like DocuSign exist, which digitize transactions like these for an expedited and much better customer experience.

The reality is that there are millions of companies today that have not yet created digital experiences for their customers and, as a result, are still mired in manual processes that hamper the customer experience and put the entire business at risk. Here are just a few things every business can do to digitize operations and ultimately stay relevant in the market.

Create a Strategic Plan for Digitizing the Customer and Employee Experience

Start by putting together a game plan and identifying the processes within your business that can be digitized.

If you're a real estate agent, for example, how can you digitize the process of buying or selling a house?

If you're a medical office, how can you better deliver remote care?

If you're a government office, instead of relying on in-person services and paper forms, how can you deliver information and services to your customers quickly while they remain within the comfort of their own homes?

Basically, any service you offer that can be digitized and moved to the cloud should be digitized and moved to the cloud. Especially these days, when a limited number of employees are going into the office and on-premises technologies are likely collecting dust.

The good news is that many businesses are now getting the message and making the appropriate adjustments. Our survey found that organizations are increasingly embracing the cloud, with 87% of IT leaders stating that the COVID-19 pandemic and the need to work remotely has accelerated their cloud migrations.

Embrace Intelligent Automation

Of course, issues with digital experiences will invariably arise. When they do, companies need to have the visibility and capability to quickly identify the root of the problem and fix it. These days, companies are aggressively investing in artificial intelligence (AI) and other next-generation technologies to identify and resolve technical issues effectively and automatically, with minimal human intervention.

That's probably why IT leaders progressively believe that greater automation is the key to maintaining business continuity in the face of a crisis. According to our survey, 74% of IT leaders employ intelligent systems like AI and machine learning to provide insight into their IT infrastructure. Additionally, 93% say automation is essential because it allows their IT teams to focus on strategic initiatives and operate more effectively — all of which are critical in a time of crisis.

Specifically, AI can serve as an early-warning system, automatically piecing together patterns and trends to detect red flags and nip any emerging issues in the bud. A monitoring system powered by AI can help prevent outages, save time and money, provide greater insight into user behavior, and deliver the digital experiences customers expect.

No business today is complete without a digitization strategy. The bottom line is that every business must learn to ride the wave of digital change or risk being swept away by it.

Mark Banfield is CRO at LogicMonitor

The Latest

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Steps Every Business Must Take to Digitize and Survive

Mark Banfield
LogicMonitor

In 2020, our society is undergoing massive upheaval and businesses are being forced to adapt on the fly. During this period of crisis, the companies that make the necessary adjustments the quickest will succeed. We're already seeing it happen in the accelerated push toward digitization, as companies that smoothly digitize their customer experiences move forward and those that don't get left behind.


Of course, digitization is not new, but rather an evergreen topic of discussion at board and executive-level meetings. What is new, however, is the speed at which the gap between the digital haves and have-nots is widening amid the COVID-19 crisis.

The global pandemic has magnified the urgency of digitization, and it has exposed the businesses that are still struggling to manage even the most basic of digital interactions with their customers and employees. Organizations everywhere are under enormous pressure to accelerate digital transformation, expand cloud services and do whatever else it takes to stay connected with customers and workers.

What's striking, however, is that only 39% of IT professionals have a high level of confidence in their organization's ability to seamlessly deliver digital services in the midst of a crisis, according to a new survey we conducted here at LogicMonitor.

I've experienced this disconnect firsthand in my interactions with a number of businesses. For instance, I recently bought a house overseas and the real estate agent wanted to fax me the closing documents. When I told the agent I didn't have a fax machine (who has a fax machine anymore?), he offered to mail them to me so I could sign and send back to him. Who knows how long that would have taken? Fax machines are a relic of the past when services like DocuSign exist, which digitize transactions like these for an expedited and much better customer experience.

The reality is that there are millions of companies today that have not yet created digital experiences for their customers and, as a result, are still mired in manual processes that hamper the customer experience and put the entire business at risk. Here are just a few things every business can do to digitize operations and ultimately stay relevant in the market.

Create a Strategic Plan for Digitizing the Customer and Employee Experience

Start by putting together a game plan and identifying the processes within your business that can be digitized.

If you're a real estate agent, for example, how can you digitize the process of buying or selling a house?

If you're a medical office, how can you better deliver remote care?

If you're a government office, instead of relying on in-person services and paper forms, how can you deliver information and services to your customers quickly while they remain within the comfort of their own homes?

Basically, any service you offer that can be digitized and moved to the cloud should be digitized and moved to the cloud. Especially these days, when a limited number of employees are going into the office and on-premises technologies are likely collecting dust.

The good news is that many businesses are now getting the message and making the appropriate adjustments. Our survey found that organizations are increasingly embracing the cloud, with 87% of IT leaders stating that the COVID-19 pandemic and the need to work remotely has accelerated their cloud migrations.

Embrace Intelligent Automation

Of course, issues with digital experiences will invariably arise. When they do, companies need to have the visibility and capability to quickly identify the root of the problem and fix it. These days, companies are aggressively investing in artificial intelligence (AI) and other next-generation technologies to identify and resolve technical issues effectively and automatically, with minimal human intervention.

That's probably why IT leaders progressively believe that greater automation is the key to maintaining business continuity in the face of a crisis. According to our survey, 74% of IT leaders employ intelligent systems like AI and machine learning to provide insight into their IT infrastructure. Additionally, 93% say automation is essential because it allows their IT teams to focus on strategic initiatives and operate more effectively — all of which are critical in a time of crisis.

Specifically, AI can serve as an early-warning system, automatically piecing together patterns and trends to detect red flags and nip any emerging issues in the bud. A monitoring system powered by AI can help prevent outages, save time and money, provide greater insight into user behavior, and deliver the digital experiences customers expect.

No business today is complete without a digitization strategy. The bottom line is that every business must learn to ride the wave of digital change or risk being swept away by it.

Mark Banfield is CRO at LogicMonitor

The Latest

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...