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IT Has Proven Rapid Digital Transformation is Possible - What's Next?

Paul Davenport
AppNeta

The pandemic effectively "shocked" enterprises into pushing the gas on tech initiatives that, on the one hand, support a more flexible, decentralized workforce, but that were by-and-large already on the roadmap, regardless of whether businesses had been planning to support widespread work-from-home or not.

Retiring legacy, hardware-based applications and workflows that committed workers to sharing an office for more flexible and scalable cloud tools, for instance, was already in progress (though relatively slowly) at many businesses well before the pandemic made cloud migration a top priority. Showing business leaders that accelerated "digital transformations" like these could even be pulled off (let alone successfully) was just one business myth that was dispelled as part of the pandemic.

The second myth (at least among wary enterprise decision makers) was that IT teams couldn't successfully deploy network infrastructures that were fit to support widespread WFH. Not only has this been dispelled (again, many of the required changes to enable WFH go hand-in-hand with long-simmering digital overhauls), but many newly-remote teams are actually performing better in their new environment.

However, just because enterprise IT have proven in many cases that they can support an almost fully remote workforce doesn't mean that this will be the enterprise standard going forward.

A study conducted by workplace chat app Blind found that among the biggest Silicon Valley tech companies, for instance, pandemic-induced WFH is leading to workers feeling 68 percent more burnt out than they did last year. While the feeling is subjective, the increase can't be ignored. That said, workers in other industries like healthcare are seeing tangible benefits in conducting work at a distance.

So while WFH will never be a fit for every worker, now that both IT and knowledge workers have debunked the misconceptions of their most skeptical enterprise leaders, it'll be hard to convince everyone to "go back" to the old way once restrictions are finally lifted.

All of this goes to show that as much as we've learned about the positives of WFH in this global "experiment" in decentralization, it's too soon to fully say goodbye to the office as we knew it before the pandemic. Instead, companies will need to adapt to support a more fluid, "anywhere operations" model for work that will allow employees to enjoy similar experiences with the job wherever they log on.

For network operations teams going forward, the biggest challenge will be keeping up with the accelerated pace of change now that they've proven to skeptical business leaders their efficiency (and efficacy) in successfully transforming the network. This will require teams to put a greater emphasis on leveraging comprehensive visibility into end-user performance wherever users are located now that the footprint for potential errors has expanded with workers at home.

Supporting this "new normal" calls for enterprise IT teams to synchronize visibility across their rapidly evolving network footprint to ensure they can monitor and manage the digital experiences of users leveraging any app, from any location, at any point in time. With users logging onto the network from all over the map and adopting new technologies to stay in sync with their times, enterprise IT teams have to seek out visibility into network environments that they don't inherently have clear insights into or control over to ensure successful deployment.

Paul Davenport is Marketing Communications Manager at AppNeta

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IT Has Proven Rapid Digital Transformation is Possible - What's Next?

Paul Davenport
AppNeta

The pandemic effectively "shocked" enterprises into pushing the gas on tech initiatives that, on the one hand, support a more flexible, decentralized workforce, but that were by-and-large already on the roadmap, regardless of whether businesses had been planning to support widespread work-from-home or not.

Retiring legacy, hardware-based applications and workflows that committed workers to sharing an office for more flexible and scalable cloud tools, for instance, was already in progress (though relatively slowly) at many businesses well before the pandemic made cloud migration a top priority. Showing business leaders that accelerated "digital transformations" like these could even be pulled off (let alone successfully) was just one business myth that was dispelled as part of the pandemic.

The second myth (at least among wary enterprise decision makers) was that IT teams couldn't successfully deploy network infrastructures that were fit to support widespread WFH. Not only has this been dispelled (again, many of the required changes to enable WFH go hand-in-hand with long-simmering digital overhauls), but many newly-remote teams are actually performing better in their new environment.

However, just because enterprise IT have proven in many cases that they can support an almost fully remote workforce doesn't mean that this will be the enterprise standard going forward.

A study conducted by workplace chat app Blind found that among the biggest Silicon Valley tech companies, for instance, pandemic-induced WFH is leading to workers feeling 68 percent more burnt out than they did last year. While the feeling is subjective, the increase can't be ignored. That said, workers in other industries like healthcare are seeing tangible benefits in conducting work at a distance.

So while WFH will never be a fit for every worker, now that both IT and knowledge workers have debunked the misconceptions of their most skeptical enterprise leaders, it'll be hard to convince everyone to "go back" to the old way once restrictions are finally lifted.

All of this goes to show that as much as we've learned about the positives of WFH in this global "experiment" in decentralization, it's too soon to fully say goodbye to the office as we knew it before the pandemic. Instead, companies will need to adapt to support a more fluid, "anywhere operations" model for work that will allow employees to enjoy similar experiences with the job wherever they log on.

For network operations teams going forward, the biggest challenge will be keeping up with the accelerated pace of change now that they've proven to skeptical business leaders their efficiency (and efficacy) in successfully transforming the network. This will require teams to put a greater emphasis on leveraging comprehensive visibility into end-user performance wherever users are located now that the footprint for potential errors has expanded with workers at home.

Supporting this "new normal" calls for enterprise IT teams to synchronize visibility across their rapidly evolving network footprint to ensure they can monitor and manage the digital experiences of users leveraging any app, from any location, at any point in time. With users logging onto the network from all over the map and adopting new technologies to stay in sync with their times, enterprise IT teams have to seek out visibility into network environments that they don't inherently have clear insights into or control over to ensure successful deployment.

Paul Davenport is Marketing Communications Manager at AppNeta

The Latest

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 ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...