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How Hyperautomation Builds Steam and Breaks Down IT Silos

Marcus Rebelo
Resolve

Hyperautomation topped Gartner's recent list of Top 10 Strategic Technology Trends, but is this just another new buzzword to further complicate our increasingly complex IT world?

Over the last decade, many IT teams have unknowingly implemented various forms of hyperautomation. By orchestrating more advanced automated processes and workflows, they've essentially cracked the code on this trend already. But what exactly do we mean by hyperautomation?

Gartner describes business-driven hyperautomation as: "an approach in which organizations rapidly identify, vet and automate as many approved business and IT processes as possible through a disciplined approach. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms (inclusive of, but not limited to, AI, machine learning, event-driven software architecture, RPA, iPaaS, packaged software and other types of decision, process and/or task automation tools)."

So, what's changed that would cause Gartner to introduce this new term now? We believe the answer lies in the ability to incorporate more advanced, newer technologies into the automation toolchain today — namely artificial intelligence, machine learning, and natural language processing, along with advanced analytics and data mining, which leverage all of the above. In the coming year, we'll see hyperautomation further evolve, building momentum, and contributing to the inevitable erosion of silos in enterprise IT.

Improving Digital Experience Demands Hyperautomation

Regardless of the name, hyperautomation's capacity to integrate and orchestrate various technologies is here to stay. Ultimately, it highlights the fact that siloed IT functions are being relegated to the IT graveyard. Like it or not, the needs of our in-house users and customers alike demand that all of our tools work together to serve broader, strategic business objectives — a fact that has been further amplified by the pandemic.

When all your systems are interoperative, independent silos are not just unnecessary, they impede business objectives. The widespread adoption of APIs is indicative of this drive toward interoperability. Further, Gartner estimates that over 70% of commercial enterprises have dozens of hyperautomation initiatives underway. Unfortunately, many of these will likely languish or fail because they're siloed, lack alignment to business outcomes, or overlap with other efforts. This results in more technical debt, unsustainable IT architectures, and data issues.

Hyperautomation, by default, is starting to break through the silo walls, building incremental connections between them, and in doing so, improving overall capabilities. While it will take years before siloed architectures fade for good, hyperautomation is moving in the right direction.

Hyperautomation in Action

To gain a better understanding of how hyperautomation is already in play for many enterprise IT teams, let's look at a few examples.

Combining intelligent automation with common chat tools like Slack or Microsoft Teams delivers valuable self-service capabilities, allowing end users to perform simple tasks on their own, like resetting passwords, or more complex ones, like interactive, multi-step PC troubleshooting. A more sophisticated example might be server provisioning, which would incorporate additional steps, like automating entitlement checks.

To support these types of hyperautomation use cases, service desk teams tie chat tools into a backend system that permits the actions to occur, plus another system that has the ability to perform the automated actions on behalf of the user. Where there are multiple chat tools deployed in an organization, capabilities can be deployed across all of them with a robust orchestrator on the back end. The end user never knows whether there are two or ten different tools involved in capturing, approving, executing, and responding to their request. Better yet, the automated processes can be structured in such a way that corporate compliance and governance standards are enforced at every turn.

For organizations with multiple automation tools — usually requiring different skillsets — hyperautomation can unify this ecosystem and enable these tools to seamlessly interact with one another to execute end-to-end processes autonomously. This eliminates the time consuming, labor-intensive, baton-passing between departments to complete certain responsibilities, representing a significant savings in costs and man hours.

Let's also explore the chain of custody for new applications. In most organizations, DevOps has its own set of tools to spin up new applications in the development environment. When a new application is deployed, one engineer might run some scripts to tie it into the domain and bring it online, ensure it is patched, and perform post-deployment testing activities.

Then a security engineer might implement some anti-malware tools and confirm that the application meets the corporate build and hardening standards.

Finally, post-deployment, another team might be tasked with keeping the application up and running, tracking and maintaining change requests, and managing configuration items, along with all of their associated relationships.

Each of the users described above would likely have their own scripts and automation tools to complete their part of the deployment process. With hyperautomation, the task-based automation tools are connected by one master orchestrator, which transforms disparate steps into a seamless, unified process.

Overcoming the Challenges of Hyperautomation

The most obvious challenge to surmount with hyperautomation: no one wants to give up their walled garden. However, it's a process that occurs incrementally where one brick at a time is removed. With each brick, people gain productivity and trust in hyperautomation, and every tool becomes more valuable by extension.

Who stands to benefit? Everyone — regardless of whether you look after the network, service desk, databases, security, or systems, you'll get time back in your day. You're also going to benefit from better quality of service scores from the users that you support.

Determining which processes to target with hyperautomation can also be a challenge. The first step is to identify the most time-consuming, repetitive processes in your organization and then balance that against the complexity to automate those processes. Pick the low hanging fruit first — prioritize some processes that can be easily automated to get quick wins, then progress to the more complex use cases, or those that are less frequent but consume significant resources.

A clearly developed strategy for hyperautomation and those early quick wins will secure buy-in and investment in additional initiatives. Starting with simple ties between tools and processes brings quick value and trust, which opens up increasingly more opportunity to hyperautomate more complex processes much faster. The business benefits snowball from there.

Hyperautomation has the potential to deliver real and meaningful ROI over the coming months and years, as well as transforming the way we approach IT operations forever.

Marcus Rebelo is Director of Sales Engineering, Americas, at Resolve

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A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

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Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

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How Hyperautomation Builds Steam and Breaks Down IT Silos

Marcus Rebelo
Resolve

Hyperautomation topped Gartner's recent list of Top 10 Strategic Technology Trends, but is this just another new buzzword to further complicate our increasingly complex IT world?

Over the last decade, many IT teams have unknowingly implemented various forms of hyperautomation. By orchestrating more advanced automated processes and workflows, they've essentially cracked the code on this trend already. But what exactly do we mean by hyperautomation?

Gartner describes business-driven hyperautomation as: "an approach in which organizations rapidly identify, vet and automate as many approved business and IT processes as possible through a disciplined approach. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms (inclusive of, but not limited to, AI, machine learning, event-driven software architecture, RPA, iPaaS, packaged software and other types of decision, process and/or task automation tools)."

So, what's changed that would cause Gartner to introduce this new term now? We believe the answer lies in the ability to incorporate more advanced, newer technologies into the automation toolchain today — namely artificial intelligence, machine learning, and natural language processing, along with advanced analytics and data mining, which leverage all of the above. In the coming year, we'll see hyperautomation further evolve, building momentum, and contributing to the inevitable erosion of silos in enterprise IT.

Improving Digital Experience Demands Hyperautomation

Regardless of the name, hyperautomation's capacity to integrate and orchestrate various technologies is here to stay. Ultimately, it highlights the fact that siloed IT functions are being relegated to the IT graveyard. Like it or not, the needs of our in-house users and customers alike demand that all of our tools work together to serve broader, strategic business objectives — a fact that has been further amplified by the pandemic.

When all your systems are interoperative, independent silos are not just unnecessary, they impede business objectives. The widespread adoption of APIs is indicative of this drive toward interoperability. Further, Gartner estimates that over 70% of commercial enterprises have dozens of hyperautomation initiatives underway. Unfortunately, many of these will likely languish or fail because they're siloed, lack alignment to business outcomes, or overlap with other efforts. This results in more technical debt, unsustainable IT architectures, and data issues.

Hyperautomation, by default, is starting to break through the silo walls, building incremental connections between them, and in doing so, improving overall capabilities. While it will take years before siloed architectures fade for good, hyperautomation is moving in the right direction.

Hyperautomation in Action

To gain a better understanding of how hyperautomation is already in play for many enterprise IT teams, let's look at a few examples.

Combining intelligent automation with common chat tools like Slack or Microsoft Teams delivers valuable self-service capabilities, allowing end users to perform simple tasks on their own, like resetting passwords, or more complex ones, like interactive, multi-step PC troubleshooting. A more sophisticated example might be server provisioning, which would incorporate additional steps, like automating entitlement checks.

To support these types of hyperautomation use cases, service desk teams tie chat tools into a backend system that permits the actions to occur, plus another system that has the ability to perform the automated actions on behalf of the user. Where there are multiple chat tools deployed in an organization, capabilities can be deployed across all of them with a robust orchestrator on the back end. The end user never knows whether there are two or ten different tools involved in capturing, approving, executing, and responding to their request. Better yet, the automated processes can be structured in such a way that corporate compliance and governance standards are enforced at every turn.

For organizations with multiple automation tools — usually requiring different skillsets — hyperautomation can unify this ecosystem and enable these tools to seamlessly interact with one another to execute end-to-end processes autonomously. This eliminates the time consuming, labor-intensive, baton-passing between departments to complete certain responsibilities, representing a significant savings in costs and man hours.

Let's also explore the chain of custody for new applications. In most organizations, DevOps has its own set of tools to spin up new applications in the development environment. When a new application is deployed, one engineer might run some scripts to tie it into the domain and bring it online, ensure it is patched, and perform post-deployment testing activities.

Then a security engineer might implement some anti-malware tools and confirm that the application meets the corporate build and hardening standards.

Finally, post-deployment, another team might be tasked with keeping the application up and running, tracking and maintaining change requests, and managing configuration items, along with all of their associated relationships.

Each of the users described above would likely have their own scripts and automation tools to complete their part of the deployment process. With hyperautomation, the task-based automation tools are connected by one master orchestrator, which transforms disparate steps into a seamless, unified process.

Overcoming the Challenges of Hyperautomation

The most obvious challenge to surmount with hyperautomation: no one wants to give up their walled garden. However, it's a process that occurs incrementally where one brick at a time is removed. With each brick, people gain productivity and trust in hyperautomation, and every tool becomes more valuable by extension.

Who stands to benefit? Everyone — regardless of whether you look after the network, service desk, databases, security, or systems, you'll get time back in your day. You're also going to benefit from better quality of service scores from the users that you support.

Determining which processes to target with hyperautomation can also be a challenge. The first step is to identify the most time-consuming, repetitive processes in your organization and then balance that against the complexity to automate those processes. Pick the low hanging fruit first — prioritize some processes that can be easily automated to get quick wins, then progress to the more complex use cases, or those that are less frequent but consume significant resources.

A clearly developed strategy for hyperautomation and those early quick wins will secure buy-in and investment in additional initiatives. Starting with simple ties between tools and processes brings quick value and trust, which opens up increasingly more opportunity to hyperautomate more complex processes much faster. The business benefits snowball from there.

Hyperautomation has the potential to deliver real and meaningful ROI over the coming months and years, as well as transforming the way we approach IT operations forever.

Marcus Rebelo is Director of Sales Engineering, Americas, at Resolve

The Latest

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...